Datafication. Platformisation. Metaverse. Global Internet Policy or a Fractured Communication Future?
Special Issue Call for Papers, Volume 15, Issue 4
Datafication. Platformization. Metaverse. What is the state of global internet policy? Within our current online and hyper-connected lives, is it possible to have such a thing as global internet policy? Building off the 2022 Policy & Internet Conference, this special issue addresses the complex and multiple perspectives of internet policy from around the globe.
As we evolve through the Anthropocene and attempt to navigate the significant challenges humanity currently faces, we are consistently reminded of the most pressing critical issues of our epoch. Economic systems are the point of breaking, industrial action mobilised by unions is at an all-time high, inflation is rising, workers’ pay continues to fall, and the stability of our political systems has come into question. Our health systems are under unfathomable stress, refugee numbers are increasing through displacement, and the war in Ukraine continues, all of which adds to the growing global societal, economic and political pressures. And yet, concurrently, our connectivity through digital media and its surrounding environments is at an all-time high, arguably from the rise of technology players providing suites of social media platforms and its supporting infrastructures that enable a seamless and convenient, always-on lifestyle. The same app that enables us to chat with our friends and family can also book our rideshares, order our food, pay for our purchases and tempt us to become internet celebrities. What was once framed as user generated content activity has now become a normalised cultural pastime, as TikTok influencers feed the demotic turn that sees ordinary folk become internet superstars in rather small timeframes.
At the same time, policymakers are reforming legislation to address the incomprehensible imbalance of power that is generated by technology giants. One of the immediate issues concerning users is their online privacy. In many instances, governments continue to struggle with bringing large-scale social media platforms to account, and seeking mutually beneficial outcomes. TikTok especially has raised concerns with user privacy as many cybersecurity agencies who advise governments have no clear answers on how to maintain its use while not knowing what will happen to user data. Alongside user data issues, in some countries the relationship between technology providers and governments is blurred, where regulation is becoming a weaponized approach to citizen control. To counter these sorts of power imbalances, advocacy groups are consistently calling for safe, inclusive, affordable and reliable internet connectivity, as the digital divide continues to increase. The urgency for healthy online civic spaces has been highlighted as a key focus for advocacy groups, while ensuring the safety of its users has also been highlighted.
This special issue asks for responses to these contemporary issues and seeks to understand if a global internet policy is possible. How might we incorporate co-design, open dialogues, increased governance, interoperability and user-centred discussions into policy discussions? What are the immediate issues for policymakers?
We welcome research that addresses the following areas of interest (but not limited to):
Takedowns, shadowbanning, throttling
Non-western approaches towards internet policy
Internet governance and infrastructures
Regulatory responses that address the growing digital divide
Communication and technology for positive economic development
Building strong communication systems during times of high societal pressure
Social media and labour concerns
Emerging digital communication for marginalised groups and individuals
Digital communication that bridges regional legislation
Communication and technology through comparative media systems
Regulation for diversity across media systems
Media automation for the next 10 years and beyond
Young people and social media
Innovative empirical examples of positive digital communication and/or technology development
Please send through your title and 150-200 word abstract to Jonathon Hutchinson [firstname.lastname@example.org] and Milly Stilinovic [email@example.com] with the subject line: Policy & Internet Special Issue by October 31 2022.
In this post, Helen Margetts, Cosmina Dorobantu, Florian Ostmann, and Christina Hitrova discuss the focus on ‘technological solutions’ in the context of the Irish border debate — arguing that it is becoming a red herring and a distraction from the political choices ahead. They write:
Technology is increasingly touted as an alternative to the Irish backstop, especially in light of the government’s difficulty to find a Brexit strategy that can command a majority in the House of Commons. As academics, we have been following the debate around the role of technology in monitoring the border with interest, but also scepticism and frustration. Technology can foster government innovation in countless ways and digital technologies, in particular, have the potential to transform the way in which the government makes policy and designs public services. Yet, in the context of the Irish border debate, the focus on ‘technological solutions’ is becoming a red herring and distracts from the political choices ahead. Technology cannot solve the Irish border problem and it is time to face the facts.
1: Technology cannot ensure a ‘frictionless border’
Any legal or regulatory restrictions on the movement of goods or people between the UK and the Republic of Ireland post-Brexit will make border-related friction inevitable. Setting the restrictions is a matter of political agreements. Technology can help enforce the legal or regulatory restrictions, but it cannot prevent the introduction of friction compared to the status quo. For example, technology may speed up documentation, processing, and inspections, but it cannot eliminate the need for these procedures, whose existence will mean new burdens on those undergoing them.
2: There will be a need for new infrastructure at or near the border
Technology may make it possible for some checks to be carried out away from the border. For example, machine learning algorithms can assist in identifying suspicious vehicles and police forces can stop and inspect them away from the border. Regardless of where the relevant inspections are carried out, however, there will be a need for new infrastructure at or near the border, such as camera systems that record the identity of the vehicles crossing the frontier. The amount of new infrastructure needed will depend on how strict the UK and the EU decide to be in enforcing restrictions on the movement of goods and people. At a minimum, cameras will have to be installed at the border. Stricter enforcement regimes will require additional infrastructure such as sensors, scanners, boom barriers or gates.
3: ‘Frictionless’ solutions are in direct conflict with the Brexit goal to ‘take back control’ over borders
There is a fundamental conflict between the goals of minimising friction and enforcing compliance. For example, friction for Irish and UK citizens traveling across the Irish border could be reduced by a system that allows passenger vehicles registered within the Common Travel Area to cross the border freely. This approach, however, would make it difficult to monitor whether registered vehicles are used to facilitate unauthorised movements of people or goods across the border. More generally, the more effective the border management system is in detecting and preventing non-compliant movements of goods or people across the border, the more friction there will be.
4: Technology has known imperfections
Many of the ‘technological solutions’ that have been proposed as ways to minimise friction have blind spots when it comes to monitoring and enforcing compliance – a fact quietly acknowledged through comments about the solutions’ ‘dependence on trust’. Automated licence plate recognition systems, for example, can easily be tricked by using stolen or falsified number plates. Probabilistic algorithmic tools to identify the ‘high risk’ vehicles selected for inspections will fail to identify some cases of non-compliance. Technological tools may lead to improvements over risk-based approaches that rely on human judgment alone, but they cannot, on their own, monitor the border safely.
5: Government will struggle to develop the relevant technological tools
Suggestions that the border controversy may find a last-minute solution by relying on technology seem dangerously detached from the realities of large-scale technology projects, especially in the public sector. In addition to considerable expertise and financial investments, such projects need time, a resource that is quickly running out as March 29 draws closer. The history of government technology projects is littered with examples of failures to meet expectations, enormous cost overruns, and troubled relationships with computer services providers.
A recent example is the mobile phone app meant to facilitate the registration of the 3.7 million EU nationals living in the UK that cannot work on iPhones. Private companies will be keen to sell technological solutions to the backstop problem, with firms like Fujitsu and GSM already signalling their interest in addressing this technological challenge. Under time pressure, government will struggle to evaluate the feasibility of the technological solutions proposed by these private providers, negotiate a favourable contract, and ensure that the resulting technology is fit for purpose.
Technological tools can help implement customs rules, but they cannot fill the current political vacuum. The design, development, and implementation of border management tools require regulatory clarity—prior knowledge of the rules whose monitoring and enforcement the technical tools are meant to support. What these rules will be for the UK-Ireland border following Brexit is a political question. The recent focus on ‘technological solutions’, rather than informing the debate around this question, seems to have served as a strategy for avoiding substantive engagement with it. It is time for government to accept that technology cannot solve the Irish border problem and move on to find real, feasible alternatives.
Professor Helen Margetts, Professor of Society and the Internet, Oxford Internet institute, University of Oxford; Director of the Public Policy Programme, The Alan Turing Institute
Dr Cosmina Dorobantu, Research Associate, Oxford Internet Institute, University of Oxford; Deputy Director of the Public Policy Programme, The Alan Turing Institute
Dr Florian Ostmann, Policy Fellow, Public Policy Programme, The Alan Turing Institute
Christina Hitrova, Digital Ethics Research Assistant, Public Policy Programme, The Alan Turing Institute
Disclaimer: The views expressed in this article are those of the listed members of The Alan Turing Institute’s Public Policy Programme in their individual academic capacities, and do not represent a formal view of the Institute.
As innovations like social media and open government initiatives have become an integral part of politics in the twenty-first century, there is increasing interest in the possibility of citizens directly participating in the drafting of legislation. Indeed, there is a clear trend of greater public participation in the process of constitution making, and with the growth of e-democracy tools, this trend is likely to continue. However, this view is certainly not universally held, and a number of recent studies have been much more skeptical about the value of public participation, questioning whether it has any real impact on the text of a constitution.
Following the banking crisis, and a groundswell of popular opposition to the existing political system in 2009, the people of Iceland embarked on a unique process of constitutional reform. Having opened the entire drafting process to public input and scrutiny, these efforts culminated in Iceland’s 2011 draft crowdsourced constitution: reputedly the world’s first. In his Policy & Internet article “When Does Public Participation Make a Difference? Evidence From Iceland’s Crowdsourced Constitution”, Alexander Hudson examines the impact that the Icelandic public had on the development of the draft constitution. He finds that almost 10 percent of the written proposals submitted generated a change in the draft text, particularly in the area of rights.
This remarkably high number is likely explained by the isolation of the drafters from both political parties and special interests, making them more reliant on and open to input from the public. However, although this would appear to be an example of successful public crowdsourcing, the new constitution was ultimately rejected by parliament. Iceland’s experiment with participatory drafting therefore demonstrates the possibility of successful online public engagement — but also the need to connect the masses with the political elites. It was the disconnect between these groups that triggered the initial protests and constitutional reform, but also that led to its ultimate failure.
We caught up with Alexander to discuss his findings.
Ed: We know from Wikipedia (and other studies) that group decisions are better, and crowds can be trusted. However, I guess (re: US, UK) I also feel increasingly nervous about the idea of “the public” having a say over anything important and binding. How do we distribute power and consultation, while avoiding populist chaos?
Alexander: That’s a large and important question, which I can probably answer only in part. One thing we need to be careful of is what kind of public we are talking about. In many cases, we view self-selection as a bad thing — it can’t be representative. However, in cases like Wikipedia, we see self-selected individuals with specialised knowledge and an uncommon level of interest collaborating. I would suggest that there is an important difference between the kind of decisions that are made by careful and informed participants in citizens’ juries, deliberative polls, or Wikipedia editing, and the oversimplified binary choices that we make in elections or referendums.
So, while there is research to suggest that large numbers of ordinary people can make better decisions, there are some conditions in terms of prior knowledge and careful consideration attached to that. I have high hopes for these more deliberative forms of public participation, but we are right to be cautious about referendums. The Icelandic constitutional reform process actually involved several forms of public participation, including two randomly selected deliberative fora, self-selected online participation, and a popular referendum with several questions.
Ed: A constitution is a very technical piece of text: how much could non-experts realistically contribute to its development — or was there also contribution from specialised interest groups? Presumably there was a team of lawyers and drafters managing the process?
Alexander: All of these things were going on in Iceland’s drafting process. In my research here and on a few other constitution-making processes in other countries, I’ve been impressed by the ability of citizens to engage at a high level with fundamental questions about the nature of the state, constitutional rights, and legal theory. Assuming a reasonable level of literacy, people are fully capable of reading some literature on constitutional law and political philosophy, and writing very well-informed submissions that express what they would like to see in the constitutional text. A small, self-selected set of the public in many countries seeks to engage in spirited and for the most part respectful debate on these issues. In the Icelandic case, these debates have continued from 2009 to the present.
I would also add that public interest is not distributed uniformly across all the topics that constitutions cover. Members of the public show much more interest in discussing issues of human rights, and have more success in seeing proposals on that theme included in the draft constitution. Some NGOs were involved in submitting proposals to the Icelandic Constitutional Council, but interest groups do not appear to have been a major factor in the process. Unlike some constitution-making processes, the Icelandic Constitutional Council had a limited staff, and the drafters themselves were very engaged with the public on social media.
Ed: I guess Iceland is fairly small, but also unusually homogeneous. That helps, presumably, in creating a general consensus across a society? Or will party / political leaning always tend to trump any sense of common purpose and destiny, when defining the form and identity of the nation?
Alexander: You are certainly right that Iceland is unusual in these respects, and this raises important questions of what this is a case of, and how the findings here can inform us about what might happen in other contexts. I would not say that the Icelandic people reached any sort of broad, national-level consensus about how the constitution should change. During the early part of the drafting process, it seems that those who had strong disagreements with what was taking place absented themselves from the proceedings. They did turn up later to some extent (especially after the 2012 referendum), and sought to prevent this draft from becoming law.
Where the small size and homogeneous population really came into play in Iceland is through the level of knowledge that those who participated had of one another before entering into the constitution-making process. While this has been over emphasised in some discussions of Iceland, there are communities of shared interests where people all seem to know each other, or at least know of each other. This makes forming new societies, NGOs, or interest groups easier, and probably helped to launch the constitution-making project in the first place.
Ed: How many people were involved in the process — and how were bad suggestions rejected, discussed, or improved? I imagine there must have been divisive issues, that someone would have had to arbitrate?
Alexander: The number of people who interacted with the process in some way, either by attending one of the public forums that took place early in the process, voting in the election for the Constitutional Council, or engaging with the process on social media, is certainly in the tens of thousands. In fact, one of the striking things about this case is that 522 people stood for election to the 25 member Constitutional Council which drafted the new constitution. So there was certainly a high level of interest in participating in this process.
My research here focused on the written proposals that were posted to the Constitutional Council’s website. 204 individuals participated in that more intensive way. As the members of the Constitutional Council tell it, they would read some of the comments on social media, and the formal submissions on their website during their committee meetings, and discuss amongst themselves which ideas should be carried forward into the draft. The vast majority of the submissions were well-informed, on topic, and conveyed a collegial tone. In this case at least, there was very little of the kind of abusive participation that we observe in some online networks.
Ed: You say that despite the success in creating a crowd-sourced constitution (that passed a public referendum), it was never ratified by parliament — why is that? And what lessons can we learn from this?
Alexander: Yes, this is one of the most interesting aspects of the whole thing for scholars, and certainly a source of some outrage for those Icelanders who are still active in trying to see this draft constitution become law. Some of this relates to the specifics of Iceland’s constitutional amendment process (which disincentives parliament from approving changes in between elections), but I think that there are also a couple of broadly applicable things going on here. First, the constitution-making process arose as a response to the way that the Icelandic government was perceived to have failed in governing the financial system in the late 2000s. By the time a last-ditch attempt to bring the draft constitution up for a vote in parliament occurred right before the 2013 election, almost five years had passed since the crisis that began this whole saga, and the economic situation had begun to improve. So legislators were not feeling pressure to address those issues any more.
Second, since political parties were not active in the drafting process, too few members of parliament had a stake in the issue. If one of the larger parties had taken ownership of this draft constitution, we might have seen a different outcome. I think this is one of the most important lessons from this case: if the success of the project depends on action by elite political actors, they should be involved in the earlier stages of the process. For various reasons, the Icelanders chose to exclude professional politicians from the process, but that meant that the Constitutional Council had too few friends in parliament to ratify the draft.
Online activism has become increasingly visible, with social media platforms being used to express protest and dissent from the Arab Spring to #MeToo. Scholarly interest in online activism has grown with its use, together with disagreement about its impact. Do social media really challenge traditional politics? Some claim that social media have had a profound and positive effect on modern protest — the speed of information sharing making online networks highly effective in building revolutionary movements. Others argue that this activity is merely symbolic: online activism has little or no impact, dilutes offline activism, and weakens social movements. Given online activity doesn’t involve the degree of risk, trust, or effort required on the ground, they argue that it can’t be considered to be “real” activism. In this view, the Arab Spring wasn’t simply a series of “Twitter revolutions”.
Despite much work on offline social movements and coalition building, few studies have used social network analysis to examine the influence of brokers of online activists (i.e. those who act as a bridge between different ideological groups), or their role in information diffusion across a network. In her Policy & Internet article “Brokerage Roles and Strategic Positions in Twitter Networks of the 2011 Egyptian Revolution”, Deena Abul-Fottouh tests whether social movements theory of networks and coalition building — developed to explain brokerage roles in offline networks, between established parties and organisations — can also be used to explain what happens online.
Social movements theory suggests that actors who occupy an intermediary structural position between different ideological groups are more influential than those embedded only in their own faction. That is, the “bridging ties” that link across political ideologies have a greater impact on mobilisation than the bonding ties within a faction. Indeed, examining the Egyptian revolution and ensuing crisis, Deena finds that these online brokers were more evident during the first phase of movement solidarity between liberals, islamists, and socialists than in the period of schism and crisis (2011-2014) that followed the initial protests. However, she also found that the online brokers didn’t match the brokers on the ground: they played different roles, complementing rather than mirroring each other in advancing the revolutionary movement.
We caught up with Deena to discuss her findings:
Ed: Firstly: is the “Arab Spring” a useful term? Does it help to think of the events that took place across parts of the Middle East and North Africa under this umbrella term — which I suppose implies some common cause or mechanism?
Deena: Well, I believe it’s useful to an extent. It helps describe some positive common features that existed in the region such as dissatisfaction with the existing regimes, a dissatisfaction that was transformed from the domain of advocacy to the domain of high-risk activism, a common feeling among the people that they can make a difference, even though it did not last long, and the evidence that there are young people in the region who are willing to sacrifice for their freedom. On the other hand, structural forces in the region such as the power of deep states and the forces of counter-revolution were capable of halting this Arab Spring before it burgeoned or bore fruit, so maybe the term “Spring” is no longer relevant.
Ed: Revolutions have been happening for centuries, i.e. they obviously don’t need Twitter or Facebook to happen. How significant do you think social media were in this case, either in sparking or sustaining the protests? And how useful are these new social media data as a means to examine the mechanisms of protest?
Deena: Social media platforms have proven to be useful in facilitating protests such as by sharing information in a speedy manner and on a broad range across borders. People in Egypt and other places in the region were influenced by Tunisia, and protest tactics were shared online. In other words, social media platforms definitely facilitate diffusion of protests. They are also hubs to create a common identity and culture among activists, which is crucial for the success of social movements. I also believe that social media present activists with various ways to circumvent policing of activism (e.g. using pseudonyms to hide the identity of the activists, sharing information about places to avoid in times of protests, many platforms offer the possibility for activists to form closed groups where they have high privacy to discuss non-public matters, etc.).
However, social media ties are weak ties. These platforms are not necessarily efficient in building the trust needed to bond social movements, especially in times of schism and at the level of high-risk activism. That is why, as I discuss in my article, we can see that the type of brokerage that is formed online is brokerage that is built on weak ties, not necessarily the same as offline brokerage that usually requires high trust.
Ed: It’s interesting that you could detect bridging between groups. Given schism seems to be fairly standard in society (Cf filter bubbles etc.), has enough attention been paid to this process of temporary shifting alignments, to advance a common cause? And are these incidental, or intentional acts of brokerage?
Deena: I believe further studies need to be made on the concepts of solidarity, schism and brokerage within social movements both online and offline. Little attention has been given to how movements come together or break apart online. The Egyptian revolution is a rich case to study these concepts as the many changes that happened in the path of the revolution in its first five years and the intervention of different forces have led to multiple shifts of alliances that deserve study. Acts of brokerage do not necessarily have to be intentional. In social movements studies, researchers have studied incidental acts that could eventually lead to formation of alliances, such as considering co-members of various social movements organisations as brokers between these organisations.
I believe that the same happens online. Brokerage could start with incidental acts such as activists following each other on Twitter for example, which could develop into stronger ties through mentioning each other. This could also build up to coordinating activities online and offline. In the case of the Egyptian revolution, many activists who met in protests on the ground were also friends online. The same happened in Moldova where activists coordinated tactics online and met on the ground. Thus, incidental acts that start with following each other online could develop into intentional coordinated activism offline. I believe further qualitative interviews need to be conducted with activists to study how they coordinate between online and offline activism, as there are certain mechanisms that cannot be observed through just studying the public profiles of activists or their structural networks.
Ed: The “Arab Spring” has had a mixed outcome across the region — and is also now perhaps a bit forgotten in the West. There have been various network studies of the 2011 protests: but what about the time between visible protests, isn’t that in a way more important? What would a social network study of the current situation in Egypt look like, do you think?
Deena: Yes, the in-between times of waves of protests are as important to study as the waves themselves as they reveal a lot about what could happen, and we usually study them retroactively after the big shocks happen. A social network of the current situation in Egypt would probably include many “isolates” and tiny “components”, if I would use social network analysis terms. This started showing in 2014 as the effects of schism in the movement. I believe this became aggravated over time as the military coup d’état got a stronger grip over the country, suppressing all opposition. Many activists are either detained or have left the country. A quick look at their online profiles does not reveal strong communication between them. Yet, this is what apparently shows from public profiles. One of the levers that social media platforms offer is the ability to create private or “closed” groups online.
I believe these groups might include rich data about activists’ communication. However, it is very difficult, almost impossible to study these groups, unless you are a member or they give you permission. In other words, there might be some sort of communication occurring between activists but at a level that researchers unfortunately cannot access. I think we might call it the “underground of online activism”, which I believe is potentially a very rich area of study.
Ed: A standard criticism of “Twitter network studies” is that they aren’t very rich — they may show who’s following whom, but not necessarily why, or with what effect. Have there been any larger, more detailed studies of the Arab Spring that take in all sides: networks, politics, ethnography, history — both online and offline?
Deena: To my knowledge, there haven’t been studies that have included all these aspects together. Yet there are many studies that covered each of them separately, especially the politics, ethnography, and history of the Arab Spring (see for example: Egypt’s Tahrir Revolution 2013, edited by D. Tschirgi, W. Kazziha and S. F. McMahon). Similarly, very few studies have tried to compare the online and offline repertoires (see for example: Weber, Garimella and Batayneh 2013, Abul-Fottouh and Fetner 2018). In my doctoral dissertation (2018 from McMaster University), I tried to include many of these elements.
We are calling for articles for a Special Issue of the journal Policy & Internet on “Online Extremism: Government, Private Sector, and Civil Society Responses”, edited by Jonathan Bright and Bharath Ganesh, to be published in 2019. The submission deadline is October 30, 2018.
Governments, the private sector, and civil society are beginning to work together to challenge extremist exploitation of digital communications. Both Islamic and right-wing extremists use websites, blogs, social media, encrypted messaging, and filesharing websites to spread narratives and propaganda, influence mainstream public spheres, recruit members, and advise audiences on undertaking attacks.
Across the world, public-private partnerships have emerged to counter this problem. For example, the Global Internet Forum to Counter Terrorism (GIFCT) organized by the UN Counter-Terrorism Executive Directorate has organized a “shared hash database” that provides “digital fingerprints” of ISIS visual content to help platforms quickly take down content. In another case, the UK government funded ASI Data Science to build a tool to accurately detect jihadist content. Elsewhere, Jigsaw (a Google-owned company) has developed techniques to use content recommendations on YouTube to “redirect” viewers of extremist content to content that might challenge their views.
While these are important and admirable efforts, their impacts and effectiveness is unclear. The purpose of this special issue is to map and evaluate emerging public-private partnerships, technologies, and responses to online extremism. There are three main areas of concern that the issue will address:
(1) the changing role of content moderation, including taking down content and user accounts, as well as the use of AI techniques to assist;
(2) the increasing focus on “counter-narrative” campaigns and strategic communication; and
(3) the inclusion of global civil society in this agenda.
This mapping will contribute to understanding how power is distributed across these actors, the ways in which technology is expected to address the problem, and the design of the measures currently being undertaken.
Topics of Interest
Papers exploring one or more of the following areas are invited for consideration:
Efficacy of user and content takedown (and effects it has on extremist audiences);
Navigating the politics of freedom of speech in light of the proliferation of hateful and extreme speech online;
Development of content and community guidelines on social media platforms;
Effect of government policy, recent inquiries, and civil society on content moderation practices by the private sector (e.g. recent laws in Germany, Parliamentary inquiries in the UK);
Role and efficacy of Artificial Intelligence (AI) and machine learning in countering extremism.
Counter-narrative Campaigns and Strategic Communication
Effectiveness of counter-narrative campaigns in dissuading potential extremists;
Formal and informal approaches to counter narratives;
Emerging governmental or parastatal bodies to produce and disseminate counter-narratives;
Involvement of media and third sector in counter-narrative programming;
Research on counter-narrative practitioners;
Use of technology in supporting counter-narrative production and dissemination.
Inclusion of Global Civil Society
Concentration of decision making power between government, private sector, and civil society actors;
Diversity of global civil society actors involved in informing content moderation and counter-narrative campaigns;
Extent to which inclusion of diverse civil society/third sector actors improves content moderation and counter-narrative campaigns;
Challenges and opportunities faced by global civil society in informing agendas to respond to online extremism.
A significant part of political deliberation now takes place on online forums and social networking sites, leading to the idea that collective action might be evolving into “connective action”. The new level of connectivity (particularly of social media) raises important questions about its role in the political process. but understanding important phenomena, such as social influence, social forces, and digital divides, requires analysis of very large social systems, which traditionally has been a challenging task in the social sciences.
In their Policy & Internet article “Understanding Popularity, Reputation, and Social Influence in the Twitter Society“, David Garcia, Pavlin Mavrodiev, Daniele Casati, and Frank Schweitzer examine popularity, reputation, and social influence on Twitter using network information on more than 40 million users. They integrate measurements of popularity, reputation, and social influence to evaluate what keeps users active, what makes them more popular, and what determines their influence in the network.
Popularity in the Twitter social network is often quantified as the number of followers of a user. That implies that it doesn’t matter why some user follows you, or how important she is, your popularity only measures the size of your audience. Reputation, on the other hand, is a more complicated concept associated with centrality. Being followed by a highly reputed user has a stronger effect on one’s reputation than being followed by someone with low reputation. Thus, the simple number of followers does not capture the recursive nature of reputation.
In their article, the authors examine the difference between popularity and reputation on the process of social influence. They find that there is a range of values in which the risk of a user becoming inactive grows with popularity and reputation. Popularity in Twitter resembles a proportional growth process that is faster in its strongly connected component, and that can be accelerated by reputation when users are already popular. They find that social influence on Twitter is mainly related to popularity rather than reputation, but that this growth of influence with popularity is sublinear. In sum, global network metrics are better predictors of inactivity and social influence, calling for analyses that go beyond local metrics like the number of followers.
We caught up with the authors to discuss their findings:
Ed.: Twitter is a convenient data source for political scientists, but they tend to get criticised for relying on something that represents only a tiny facet of political activity. But is Twitter presumably very useful as a way of uncovering more fundamental / generic patterns of networked human interaction?
David: Twitter as a data source to study human behaviour is both powerful and limited. Powerful because it allows us to quantify and analyse human behaviour at scales and resolutions that are simply impossible to reach with traditional methods, such as experiments or surveys. But also limited because not every aspect of human behaviour is captured by Twitter and using its data comes with significant methodological challenges, for example regarding sampling biases or platform changes. Our article is an example of an analysis of general patterns of popularity and influence that are captured by spreading information in Twitter, which only make sense beyond the limitations of Twitter when we frame the results with respect to theories that link our work to previous and future scientific knowledge in the social sciences.
Ed.: How often do theoretical models (i.e. describing the behaviour of a network in theory) get linked up with empirical studies (i.e. of a network like Twitter in practice) but also with qualitative studies of actual Twitter users? And is Twitter interesting enough in itself for anyone to attempt to develop an overall theoretico-empirico-qualitative theory about it?
David: The link between theoretical models and large-scale data analyses of social media is less frequent than we all wish. But the gap between disciplines seems to be narrowing in the last years, with more social scientists using online data sources and computer scientists referring better to theories and previous results in the social sciences. What seems to be quite undeveloped is an interface with qualitative methods, specially with large-scale analyses like ours.
Qualitative methods can provide what data science cannot: questions about important and relevant phenomena that then can be explained within a wider theory if validated against data. While this seems to me as a fertile ground for interdisciplinary research, I doubt that Twitter in particular should be the paragon of such combination of approaches. I advocate for starting research from the aspect of human behaviour that is the subject of study, and not from a particularly popular social media platform that happens to be used a lot today, but might not be the standard tomorrow.
Ed.: I guess I’ve seen a lot of Twitter networks in my time, but not much in the way of directed networks, i.e. showing direction of flow of content (i.e. influence, basically) — or much in the way of a time element (i.e. turning static snapshots into dynamic networks). Is that fair, or am I missing something? I imagine it would be fun to see how (e.g.) fake news or political memes propagate through a network?
David: While Twitter provides amazing volumes of data, its programming interface is notorious for the absence of two key sources: the date when follower links are created and the precise path of retweets. The reason for the general picture of snapshots over time is that researchers cannot fully trace back the history of a follower network, they can only monitor it with certain frequency to overcome the fact that links do not have a date attached.
The generally missing picture of flows of information is because when looking up a retweet, we can see the original tweet that is being retweeted, but not if the retweet is of a retweet of a friend. This way, without special access to Twitter data or alternative sources, all information flows look like stars around the original tweet, rather than propagation trees through a social network that allow the precise analysis of fake news or memes.
Ed.: Given all the work on Twitter, how well-placed do you think social scientists would be to advise a political campaign on “how to create an influential network” beyond just the obvious (Tweet well and often, and maybe hire a load of bots). i.e. are there any “general rules” about communication structure that would be practically useful to campaigning organisations?
David: When we talk about influence on Twitter, we usually talk about rather superficial behaviour, such as retweeting content or clicking on a link. This should not be mistaken as a more substantial kind of influence, the kind that makes people change their opinion or go to vote. Evaluating the real impact of Twitter influence is a bottleneck for how much social scientists can advise a political campaign. I would say that rather than providing general rules that can be applied everywhere, social scientists and computer scientists can be much more useful when advising, tracking, and optimising individual campaigns that take into account the details and idiosyncrasies of the people that might be influenced by the campaign.
Ed.: Random question: but where did “computational social science” emerge from – is it actually quite dependent on Twitter (and Wikipedia?), or are there other commonly-used datasets? And are computational social science, “big data analytics”, and (social) data science basically describing the same thing?
David: Tracing back the meaning and influence of “computational social science” could take a whole book! My impression is that the concept started few decades ago as a spin on “sociophysics”, where the term “computational” was used as in “computational model”, emphasising a focus on social science away from toy model applications from physics. Then the influential Science article by David Lazer and colleagues in 2009 defined the term as the application of digital trace datasets to test theories from the social sciences, leaving the whole computational modelling outside the frame. In that case, “computational” was used more as it is used in “computational biology”, to refer to social science with increased power and speed thanks to computer-based technologies. Later it seems to have converged back into a combination of both the modelling and the data analysis trends, as in the “Manifesto of computational social science” by Rosaria Conte and colleagues in 2012, inspired by the fact that we need computational modelling techniques from complexity science to understand what we observe in the data.
The Twitter and Wikipedia dependence of the field is just a path dependency due to the ease and open access to those datasets, and a key turning point in the field is to be able to generalise beyond those “model organisms”, as Zeynep Tufekci calls them. One can observe these fads in the latest computer science conferences, with the rising ones being Reddit and Github, or when looking at earlier research that heavily used product reviews and blog datasets. Computational social science seems to be maturing as a field, make sense out of those datasets and not just telling cool data-driven stories about one website or another. Perhaps we are beyond the peak of inflated expectations of the hype curve and the best part is yet to come.
With respect to big data and social data science, it is easy to get lost in the field of buzzwords. Big data analytics only deals with the technologies necessary to process large volumes of data, which could come from any source including social networks but also telescopes, seismographs, and any kind of sensor. These kind of techniques are only sometimes necessary in computational social science, but are far from the core of topics of the field.
Social data science is closer, but puts a stronger emphasis on problem-solving rather than testing theories from the social sciences. When using “data science” we usually try to emphasise a predictive or explorative aspect, rather than the confirmatory or generative approach of computational social science. The emphasis on theory and modelling of computational social science is the key difference here, linking back to my earlier comment about the role of computational modelling and complexity science in the field.
Ed.: Finally, how successful do you think computational social scientists will be in identifying any underlying “social patterns” — i.e. would you agree that the Internet is a “Hadron Collider” for social science? Or is society fundamentally too chaotic and unpredictable?
David: As web scientists like to highlight, the Web (not the Internet, which is the technical infrastructure connecting computers) is the largest socio-technical artefact ever produced by humanity. Rather than as a Hadron Collider, which is a tool to make experiments, I would say that the Web can be the Hubble telescope of social science: it lets us observe human behaviour at an amazing scale and resolution, not only capturing big data but also, fast, long, deep, mixed, and weird data that we never imagined before.
While I doubt that we will be able to predict society in some sort of “psychohistory” manner, I think that the Web can help us to understand much more about ourselves, including our incentives, our feelings, and our health. That can be useful knowledge to make decisions in the future and to build a better world without the need to predict everything.
Political parties have been criticised for failing to link citizen preferences to political decision-making. But in an attempt to enhance policy representation, many political parties have established online platforms to allow discussion of policy issues and proposals, and to open up their decision-making processes. The Internet—and particularly the social web—seems to provide an obvious opportunity to strengthen intra-party democracy and mobilise passive party members. However, these mobilising capacities are limited, and in most instances, participation has been low.
In their Policy & Internet article “Does the Internet Encourage Political Participation? Use of an Online Platform by Members of a German Political Party,” Katharina Gerl, Stefan Marschall, and Nadja Wilker examine the German Greens’ online collaboration platform to ask why only some party members and supporters use it. The platform aims to improve the inclusion of party supporters and members in the party’s opinion-formation and decision-making process, but it has failed to reach inactive members. Instead, those who have already been active in the party also use the online platform. It also seems that classical resources such as education and employment status do not (directly) explain differences in participation; instead, participation is motivated by process-related and ideological incentives.
We caught up with the authors to discuss their findings:
Ed.: You say “When it comes to explaining political online participation within parties, we face a conceptual and empirical void.” Can you explain briefly what the offline models are, and why they don’t work for the Internet age?
Katharina / Stefan / Nadja: According to Verba et al. (1995) the reasons for political non-participation can be boiled down to three factors: (1) citizens do not want to participate, (2) they cannot, (3) nobody asked them to. Speaking model-wise we can distinguish three perspectives: Citizens need certain resources like education, information, time and civic skills to participate (resource model and civic voluntarism model). The social psychological model looks at the role of attitudes and political interest that are supposed to increase participation. In addition to resources and attitudes, the general incentives model analyses how motives, costs and benefits influence participation.
These models can be applied to online participation as well, but findings for the online context indicate that the mechanisms do not always work like in the offline context. For example, age plays out differently for online participation. Generally, the models have to be specified for each participation context. This especially applies for the online context as forms of online participation sometimes demand different resources, skills or motivational factors. Therefore, we have to adapt and supplemented the models with additional online factors like internet skills and internet sophistication.
Ed.: What’s the value to a political party of involving its members in policy discussion? (i.e. why go through the bother?)
Katharina / Stefan / Nadja: Broadly speaking, there are normative and rational reasons for that. At least for the German parties, intra-party democracy plays a crucial role. The involvement of members in policy discussion can serve as a means to strengthen the integration and legitimation power of a party. Additionally, the involvement of members can have a mobilising effect for the party on the ground. This can positively influence the linkage between the party in central office, the party on the ground, and the societal base. Furthermore, member participation can be a way to react on dissatisfaction within a party.
Ed.: Are there any examples of successful “public deliberation” — i.e. is this maybe just a problem of getting disparate voices to usefully engage online, rather than a failure of political parties per se?
Katharina / Stefan / Nadja: This is definitely not unique to political parties. The problems we observe regarding online public deliberation in political parties also apply to other online participation platforms: political participation and especially public deliberation require time and effort for participants, so they will only be willing to engage if they feel they benefit from it. But the benefits of participation may remain unclear as public deliberation – by parties or other initiators – often takes place without a clear goal or a real say in decision-making for the participants. Initiators of public deliberation often fail to integrate processes of public deliberation into formal and meaningful decision-making procedures. This leads to disappointment for potential participants who might have different expectations concerning their role and scope of influence. There is a risk of a vicious circle and disappointed expectations on both sides.
Ed.: Based on your findings, what would you suggest that the Greens do in order to increase participation by their members on their platform?
Katharina / Stefan / Nadja: Our study shows that the members of the Greens are generally willing to participate online and appreciate this opportunity. However, the survey also revealed that the most important incentive for them is to have an influence on the party’s decision-making. We would suggest that the Greens create an actual cause for participation, meaning to set clear goals and to integrate it into specific and relevant decisions. Participation should not be an end in itself!
Ed.: How far do political parties try to harness deliberation where it happens in the wild e.g. on social media, rather than trying to get people to use bespoke party channels? Or might social media users see this as takeover by the very “establishment politics” they might have abandoned, or be reacting against?
Katharina / Stefan / Nadja: Parties do not constrain their online activities to their own official platforms and channels but also try to develop strategies for influencing discourses in the wild. However, this works much better and has much more authenticity as well as credibility if it isn’t parties as abstract organisations but rather individual politicians such as members of parliament who engage in person on social media, for example by using Twitter.
Ed.: How far have political scientists understood the reasons behind the so-called “crisis of democracy”, and how to address it? And even if academics came up with “the answer” — what is the process for getting academic work and knowledge put into practice by political parties?
Katharina / Stefan / Nadja: The alleged “crisis of democracy” is in first line seen as a crisis of representation in which the gap between political elites and the citizens has widened drastically within the last years, giving room to populist movements and parties in many democracies. Our impression is that facing the rise of populism in many countries, politicians have become more and more attentive towards discussions and findings in political science which have been addressing the linkage problems for years. But perhaps this is like shutting the stable door after the horse has bolted.
There are a many instances of crowdsourcing in both local and national governance across the world, as governments implement crowdsourcing as part of their open government practices aimed at fostering civic engagement and knowledge discovery for policies. But is crowdsourcing conducive to deliberation among citizens or is it essentially just a consulting mechanism for information gathering? Second, if it is conducive to deliberation, what kind of deliberation is it? (And is it democratic?) Third, how representative are the online deliberative exchanges of the wishes and priorities of the larger population?
In their Policy & Internet article “Crowdsourced Deliberation: The Case of the Law on Off-Road Traffic in Finland”, Tanja Aitamurto and Hélène Landemore examine a partially crowdsourced reform of the Finnish off-road traffic law. The aim of the process was to search for knowledge and ideas from the crowd, enhance people’s understanding of the law, and to increase the perception of the policy’s legitimacy. The participants could propose ideas on the platform, vote others’ ideas up or down, and comment.
The authors find that despite the lack of explicit incentives for deliberation in the crowdsourced process, crowdsourcing indeed functioned as a space for democratic deliberation; that is, an exchange of arguments among participants characterised by a degree of freedom, equality, and inclusiveness. An important finding, in particular, is that despite the lack of statistical representativeness among the participants, the deliberative exchanges reflected a diversity of viewpoints and opinions, tempering to a degree the worry about the bias likely introduced by the self-selected nature of citizen participation.
They introduce the term “crowdsourced deliberation” to mean the deliberation that happens (intentionally or unintentionally) in crowdsourcing, even when the primary aim is to gather knowledge rather than to generate deliberation. In their assessment, crowdsourcing in the Finnish experiment was conducive to some degree of democratic deliberation, even though, strikingly, the process was not designed for it.
We caught up with the authors to discuss their findings:
Ed.: There’s a lot of discussion currently about “filter bubbles” (and indeed fake news) damaging public deliberation. Do you think collaborative crowdsourced efforts (that include things like Wikipedia) help at all more generally, or are we all damned to our individual echo chambers?
Tanja and Hélène: Deliberation, whether taking place within a crowdsourced policymaking process or in another context, has a positive impact on society, when the participants exchange knowledge and arguments. While all deliberative processes are, to a certain extent, their own microcosms, there is typically at least some cross-cutting exposure of opinions and perspectives among the crowd. The more diverse the participant crowd is and the larger the number of participants, the more likely there is diversity also in the opinions, preventing strictly siloed echo chambers.
Moreover, it all comes down to design and incentives in the end. In our crowdsourcing platform we did not particularly try to attract a cross-cutting section of the population so there was a risk of having only a relatively homogenous population self-selecting into the process, which is what happened to a degree, demographically at last (over 90% of our participants were educated male professionals). In terms of ideas though, the pool was much more diverse than the demography would have suggested, and techniques we used (like clustering) helped maintain the visibility (to the researchers) of the minority views.
That said, if what you are is after is maximal openness and cross-cutting exposure, nothing beats random selection, like the one used in mini-publics of all kinds, from citizens’ juries to deliberative polls to citizens’ assemblies. That’s what Facebook and Twitter should use in order to break the filter bubbles in which people lock themselves: algorithms that randomise the content of our newsfeed and expose us to a vast range of opinions, rather than algorithms that maximise similarity with what we already like.
But for us the goal was different and so our design was different. Our goal was to gather knowledge and ideas and for this self-selection (the sort also at play in Wikipedia) is better than random-selection: whereas with random selection you shut the door on most people, in crowdsourcing platform you just let the door open to anyone who can self-identify as having a relevant form of knowledge and has the motivation to participate. The remarkable thing in our case is that even though we didn’t design the process for democratic deliberation, it occurred anyway, between the cracks of the design so to speak.
Ed.: I suppose crowdsourcing won’t work unless there is useful cooperation: do you think these successful relationships self-select on a platform, or do things perhaps work precisely because people may NOT be discussing other, divisive things (like immigration) when working together on something apparently unrelated, like an off-road law?
Tanja and Hélène: There is a varying degree of collaboration in crowdsourcing. In crowdsourced policymaking, the crowd does not typically collaborate on drafting the law (unlike the crowd does in Wikipedia writing), but they rather respond to the crowdsourcer’s, in this case, the government’s prompts. In this type of crowdsourcing, which was the case in the crowdsourced off-road traffic law reform, the crowd members don’t need to collaborate with each other in order the process to achieve its goal of finding new knowledge. The crowd can, of course, decide not to collaborate with the government and not answer the prompts, or start sabotaging the process.
The degree and success of collaboration will depend on the design and the goals of your experiment. In our case, crowdsourcing might have worked even without collaboration because our goal was to gather knowledge and information, which can be done by harvesting the contributions of the individual members of the crowd without them interacting with each other. But if what you are after is co-creation or deliberation, then yes you need to create the background conditions and incentives for cooperation.
Cooperation may require bracketing some sensitive topics or else learning to disagree in respectful ways. Deliberation, and more broadly cooperation are social skills — human technologies you might say — that we still don’t know how to use very well. This comes in part from the fact that our school systems do not teach those skills, focused as they are on promoting individual rather than collaborative success and creating an eco-system of zero-sum competition between students, when in the real world there is almost nothing you can do all by yourself and we would be much better off nurturing collaborative skills and the art or technology of deliberation.
Ed.: Have there been any other examples in Finland — i.e. is crowdsourcing (and deliberation) something that is seen as useful and successful by the government?
Tanja and Hélène: Yes, there has been several crowdsourced policymaking processes in Finland. One is a crowdsourced Limited Liability Housing Company Law reform, organised by the Ministry of Justice in the Finland government. We examined the quality of deliberation in the case, and the findings show that the quality of deliberation, as measured by Discourse Quality Index, was pretty good.
Advocates of deliberative democracy have always hoped that the Internet would provide the means for an improved public sphere. But what particular platform features should we look to, to promote deliberative debate online? In their Policy & Internet article “Design Matters! An Empirical Analysis of Online Deliberation on Different News Platforms“, Katharina Esau, Dennis Friess, and Christiane Eilders show how differences in the design of various news platforms result in significant variation in the quality of deliberation; measured as rationality, reciprocity, respect, and constructiveness.
The empirical findings of their comparative analysis across three types of news platforms broadly support the assumption that platform design affects the level of deliberative quality of user comments. Deliberation was most likely to be found in news fora, which are of course specifically designed to initiate user discussions. News websites showed a lower level of deliberative quality, with Facebook coming last in terms of meeting deliberative design criteria and sustaining deliberation. However, while Facebook performed poorly in terms of overall level of deliberative quality, it did promote a high degree of general engagement among users.
The study’s findings suggest that deliberative discourse in the virtual public sphere of the Internet is indeed possible, which is good news for advocates of deliberative theory. However, this will only be possible by carefully considering how platforms function, and how they are designed. Some may argue that the “power of design” (shaped by organisers like media companies), contradicts the basic idea of open debate amongst equals where the only necessary force is Habermas’s “forceless force of the better argument”. These advocates of an utterly free virtual public sphere may be disappointed, given it’s clear that deliberation is only likely to emerge if the platform is designed in a particular way.
We caught up with the authors to discuss their findings:
Ed: Just briefly: what design features did you find helped support public deliberation, i.e. reasoned, reciprocal, respectful, constructive discussion?
Katharina / Dennis / Christiane: There are several design features which are known to influence online deliberation. However, in this study we particularly focus on moderation, asynchronous discussion, clear topic definition, and the availability of information, which we have found to have a positive influence on the quality of online deliberation.
Ed.: I associate “Internet as a deliberative space” with Habermas, but have never read him: what’s the short version of what he thinks about “the public sphere” — and how the Internet might support this?
Katharina / Dennis / Christiane: Well, Habermas describes the public sphere as a space where free and equal people discuss topics of public import in a specific way. The respectful exchange of rational reasons is crucial in this normative ideal. Due to its open architecture, the Internet has often been presented as providing the infrastructure for large scale deliberation processes. However, Habermas himself is very sceptical as to whether online spaces support his ideas on deliberation. Ironically, he is one of the most influential authors in online deliberation scholarship.
Ed.: What do advocates of the Internet as a “deliberation space” hope for — simply that people will feel part of a social space/community if they can like things or comment on them (and see similar viewpoints); or that it will result in actual rational debate, and people changing their minds to “better” viewpoints, whatever they may be? I can personally see a value for the former, but I can’t imagine the latter ever working, i.e. given people basically don’t change?
Katharina / Dennis / Christiane: We are thinking that both hopes are present in the current debate, and we partly agree with your perception that changing minds seems to be difficult. But we may also be facing some methodological or empirical issues here, because changing of minds is not an easy thing to measure. We know from other studies that deliberation can indeed cause changes of opinion. However, most of this probably takes place within the individual’s mind. Robert E. Goodin has called this process “deliberation within” and this is not accessible through content analysis. People do not articulate “Oh, thanks for this argument, I have changed my mind,” but they probably take something away from online discussions which makes them more open minded.
Ed.: Does Wikipedia provide an example where strangers have (oddly!) come together to create something of genuine value — but maybe only because they’re actually making a specific public good? Is the basic problem of the idea of the “Internet supporting public discourse” that this is just too aimless an activity, with no obvious individual or collective benefit?
Katharina / Dennis / Christiane: We think Wikipedia is a very particular case. However, we can learn from this case that the collective goal plays a very important role for the quality of contributions. We know from empirical research that if people have the intention of contributing to something meaningful, discussion quality is significantly higher than in online spaces without that desire to have an impact.
Ed.: I wonder, isn’t Twitter the place where “deliberation” now takes place? How does it fit into, or inform, the deliberation literature, which I am assuming has largely focused on things like discussion fora?
Katharina / Dennis / Christiane: This depends on the definition of the term “deliberation”. We would argue that the limitation to 280 characters is probably not the best design feature for meaningful deliberation. However, we may have to think about deliberation in less complex contexts in order to reach more people; but this is a polarising debate.
Ed.: You say that “outsourcing discussions to social networking sites such as Facebook is not advisable due to the low level of deliberative quality compared to other news platforms.” Facebook has now decided that instead of “connecting the world” it’s going to “bring people closer together” — what would you recommend that they do to support this, in terms of the design of the interactive (or deliberative) features of the platform?
Katharina / Dennis / Christiane: This is a difficult one! We think that the quality of deliberation on Facebook would strongly benefit from moderators, which should be more present on the platform to structure the discussions. By this we do not only mean professional moderators but also participative forms of moderation, which could be encouraged more by mechanisms which support such behaviour.
After its initial appearance as a cynical but safe device by Teresa May to ratchet up the Conservative majority, the UK general election of 2017 turned out to be one of the most exciting and unexpected of all time. One of the many things for which it will be remembered is as the first election where it was the social media campaigns that really made the difference to the relative fortunes of the parties, rather than traditional media. And it could be the first election where the right wing tabloids finally ceded their influence to new media, their power over politics broken according to some.
Social media have been part of the UK electoral landscape for a while. In 2015, many of us attributed the Conservative success in part to their massive expenditure on targeted Facebook advertising, 10 times more than Labour, whose ‘bottom-up’ Twitter campaign seemed mainly to have preached to the converted. Social media advertising was used more successfully by Leave.EU than Remain in the referendum (although some of us cautioned against blaming social media for Brexit). But in both these campaigns, the relentless attack of the tabloid press was able to strike at the heart of the Labour and Remain campaigns and was widely credited for having influenced the result, as in so many elections from the 1930s onwards.
However, in 2017 Labour’s campaign was widely regarded as having made a huge positive difference to the party’s share of the vote—unexpectedly rising by 10 percentage points on 2015—in the face of a typically sustained and viscious attack by the Daily Mail, the Sun and the Daily Express. Why? There are (at least) three reasons.
First, increased turnout of young people is widely regarded to have driven Labour’s improved share of the vote—and young people do not in general read newspapers not even online. Instead, they spend increasing proportions of their time on social media platforms on mobile phones, particularly Instagram (with 10 million UK users, mostly under 30) and Snapchat (used by half of 18-34 year olds), both mobile-first platforms. On these platforms, although they may see individual stories that are shared or appear on their phone’s news portal, they may not even see the front page headlines that used to make politicians shake.
Meanwhile, what people do pay attention to and share on these platforms are videos and music, so popular artists amass huge followings. Some of the most popular came out in favour of Labour under the umbrella hashtag #Grime4Corbyn, with artists like Stormzy, JME (whose Facebook interview with Corbyn was viewed 2.5 million times) and Skepta with over a million followers on Instagram alone.
A leaflet from Croydon pointing out that ‘Even your Dad has more Facebook friends’ than the 2015 vote difference between Conservative and Labour and showing Stormzy saying ‘Vote Labour!’ was shared millions of times. Obviously we don’t know how much difference these endorsements made—but by sharing videos and images, they certainly spread the idea of voting for Corbyn across huge social networks.
Second, Labour have overtaken the Tories in reaching out across social platforms used by young people with an incredibly efficient advertising strategy. There is no doubt that in 2017 the Conservatives ran a relentless campaign of anti-Corbyn attack ads on Facebook and Instagram. But for the Conservatives, social media are just for elections. Instead, Labour have been using these channels for two years now—Corbyn has been active on Snapchat since becoming Labour leader in 2015 (when some of us were surprised to hear our teenage offspring announcing brightly ‘I’m friends with Jeremy Corbyn on Snapchat’).
That means that by the time of the election Corbyn and various fiercely pro-Labour online-only news outlets like the Canary had acquired a huge following among this demographic, meaning not having to pay for ads. And if you have followers to spread your message, you can be very efficient with advertising spend. While the Conservatives spent more than £1m on direct advertising with Facebook etc., nearly 10 million people watched pro-Labour videos on Facebook that cost less than £2K to make. Furthermore, there is some evidence that the relentless negativity of the Conservative advertising campaign actually put young people off particularly. After all, the advertising guidelines for Instagram advise ‘Images should tell a story/be inspirational!’
On the day before the election, the Daily Mail ran a front page headline ‘Apologists for Terror’, with a photo of Diane Abbot along with Corbyn and John McDonnell. But that morning Labour announced that Abbot’s standing aside due to illness. The paper circulating around the networks and sitting on newsstands was already out of date. Digital natives are used to real-time information, they are never going to be swayed by something so clearly past its sell-by-date.
Likewise, the Sun’s election day image—a grotesque image of Jeremy “Corbinned” in a dustbin was Photoshopped to replace Corbyn with an equally grotesque photograph of May taking his place in the dustbin, before the first editions landed. It won’t have reached the same audience, perhaps, but it will have reached a lot of people.
It will be a long time before we can really assess the influence of social media in the 2017 election, and some things we may never know. That is because all the data that would allow us to do so is held by the platforms themselves—Facebook, Instagram, Snapchat and so on. That is a crucial issue for the future of our democracy, already bringing calls for some transparency in political advertising both by social media platforms and the parties themselves. Under current conditions the Electoral Commission is incapable of regulating election advertising effectively, or judging (for example) how much national parties spend on targeted advertising locally. This is something that urgently needs addressing in the coming months, especially given Britain’s current penchant for elections.
The secret and often dark world of personalised political advertising on social media, where strong undercurrents of support remain hidden to the outside world, is one reason why polls fail to predict election results until after the election has taken place. Having the data to understand the social media election would also explain some of the volatility in elections these days, as explored in our book Political Turbulence: How Social Media Shape Collective Action. By investigating large-scale data on political activity my co-authors and I showed that social media are injecting the same sort of instability into politics as they have into cultural markets, where most artists gain no traction at all but a (probably unpredictable) few become massively popular—the young singer Ed Sheeran’s ‘The Shape of You’ has been streamed one billion times on Spotify alone.
In 2017, Stormzy and co. provided a more direct link between political and music markets, and this kind of development will ensure that politics in the age of social media will remain turbulent and unpredictable. We can’t claim to have predicted Labour’s unexpected success in this election, but we can claim to have foreseen that it couldn’t be predicted.