Stormzy 1: The Sun 0 — Three Reasons Why #GE2017 Was the Real Social Media Election

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 frontpage 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 news-stands 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 personalized 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.

Stormzy 1: The Sun 0 — Three Reasons Why #GE2017 Was the Real Social Media Election

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 frontpage 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 news-stands 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 personalized 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.

Could Voting Advice Applications force politicians to keep their manifesto promises?

In many countries, Voting Advice Applications (VAAs) have become an almost indispensable part of the electoral process, playing an important role in the campaigning activities of parties and candidates, an essential element of media coverage of the elections, and being widely used by citizens. A number of studies have shown that VAA use has an impact on the cognitive behaviour of users, on their likelihood to participate in elections, and on the choice of the party they vote for.

These applications are based on the idea of issue and proximity voting — the parties and candidates recommended by VAAs are those with the highest number of matching positions on a number of political questions and issues. Many of these questions are much more specific and detailed than party programs and electoral platforms, and show the voters exactly what the party or candidates stand for and how they will vote in parliament once elected. In his Policy & Internet article “Do VAAs Encourage Issue Voting and Promissory Representation? Evidence From the Swiss Smartvote,” Andreas Ladner examines the extent to which VAAs alter the way voters perceive the meaning of elections, and encourage them to hold politicians to account for election promises.

His main hypothesis is that VAAs lead to “promissory representation” — where parties and candidates are elected for their promises and sanctioned by the electorate if they don’t keep them. He suggests that as these tools become more popular, the “delegate model” is likely to increase in popularity: i.e. one in which politicians are regarded as delegates voted into parliament to keep their promises, rather than being voted a free mandate to act how they see fit (the “trustee model”).

We caught up with Andreas to discuss his findings:

Ed.: You found that issue-voters were more likely (than other voters) to say they would sanction a politician who broke their election promises. But also that issue voters are less politically engaged. So is this maybe a bit moot: i.e. if the people most likely to force the “delegate model” system are the least likely to enforce it?

Andreas: It perhaps looks a bit moot in the first place, but what happens if the less engaged are given the possibility to sanction them more easily or by default. Sanctioning a politician who breaks an election promise is not per se a good thing, it depends on the reason why he or she broke it, on the situation, and on the promise. VAA can easily provide information to what extent candidates keep their promises — and then it gets very easy to sanction them simply for that without taking other arguments into consideration.

Ed.: Do voting advice applications work best in complex, multi-party political systems? (I’m not sure anyone would need one to distinguish between Trump / Clinton, for example?)

Andreas: Yes, I believe that in very complex systems – like for example in the Swiss case where voters not only vote for parties but also for up to 35 different candidates – VAAs are particularly useful since they help to process a huge amount of information. If the choice is only between two parties or two candidates which are completely different, than VAAs are less helpful.

Ed.: I guess the recent elections / referendum I am most familiar with (US, UK, France) have been particularly lurid and nasty: but I guess VAAs rely on a certain quiet rationality to work as intended? How do you see your Swiss results (and Swiss elections, generally) comparing with these examples? Do VAAs not just get lost in the noise?

Andreas: The idea of VAAs is to help voters to make better informed choices. This is, of course, opposed to decisions based on emotions. In Switzerland, elections are not of outmost importance, due to specific features of our political system such as direct democracy and power sharing, but voters seem to appreciate the information provided by smartvote. Almost 20% of the voter cast their vote after having consulted the website.

Ed.: Macron is a recent example of someone who clearly sought (and received) a general mandate, rather than presenting a detailed platform of promises. Is that unusual? He was criticised in his campaign for being “too vague,” but it clearly worked for him. What use are manifesto pledges in politics — as opposed to simply making clear to the electorate where you stand on the political spectrum?

Andreas: Good VAAs combine electoral promises on concrete issues as well as more general political positions. Voters can base their decisions on either of them, or on a combination of both of them. I am not arguing in favour of one or the other, but they clearly have different implications. The former is closer to the delegate model, the latter to the trustee model. I think good VAAs should make the differences clear and should even allow the voters to choose.

Ed.: I guess Trump is a contrasting example of someone whose campaign was all about promises (while also seeking a clear mandate to “make America great again”), but who has lied, and broken these (impossible) promises seemingly faster than people can keep track of them. Do you think his supporters care, though?

Andreas: His promises were too far away from what he can possibly keep. Quite a few of his voters, I believe, do not want them to be fully realized but rather that the US move a bit more into this direction.

Ed.: I suppose another example of an extremely successful quasi-pledge was the Brexit campaign’s obviously meaningless — but hugely successful — “We send the EU £350 million a week; let’s fund our NHS instead.” Not to sound depressing, but do promises actually mean anything? Is it the candidate / issue that matters (and the media response to that), or the actual pledges?

Andreas: I agree that the media play an important role and not always into the direction they intend to do. I do not think that it is the £350 million a week which made the difference. It is much more a general discontent and a situation which was not sufficiently explained and legitimized which led to this unexpected decision. If you lose the support for your policy than it gets much easier for your opponents. It is difficult to imagine that you can get a majority built on nothing.

Ed.: I’ve read all the articles in the Policy & Internet special issue on VAAs: one thing that struck me is that there’s lots of incomplete data, e.g. no knowledge of how people actually voted in the end (or would vote in future). What are the strengths and weaknesses of VAAs as a data source for political research?

Andreas: The quality of the data varies between countries and voting systems. We have a self-selection bias in the use of VAAs and often also into the surveys conducted among the users. In general we don’t know how they voted, and we have to believe them what they tell us. In many respects the data does not differ that much from what we get from classic electoral studies, especially since they also encounter difficulties in addressing a representative sample. VAAs usually have much larger Ns on the side of the voters, generate more information about their political positions and preferences, and provide very interesting information about the candidates and parties.

Read the full article: Ladner, A. (2016) Do VAAs Encourage Issue Voting and Promissory Representation? Evidence From the Swiss Smartvote. Policy & Internet 8 (4). DOI: doi:10.1002/poi3.137.


Andreas Ladner was talking to blog editor David Sutcliffe.

Five Pieces You Should Probably Read On: Fake News and Filter Bubbles

This is the second post in a series that will uncover great writing by faculty and students at the Oxford Internet Institute, things you should probably know, and things that deserve to be brought out for another viewing. This week: Fake News and Filter Bubbles!

Fake news, post-truth, “alternative facts”, filter bubbles — this is the news and media environment we apparently now inhabit, and that has formed the fabric and backdrop of Brexit (“£350 million a week”) and Trump (“This was the largest audience to ever witness an inauguration — period”). Do social media divide us, hide us from each other? Are you particularly aware of what content is personalised for you, what it is you’re not seeing? How much can we do with machine-automated or crowd-sourced verification of facts? And are things really any worse now than when Bacon complained in 1620 about the false notions that “are now in possession of the human understanding, and have taken deep root therein”?

 

1. Bernie Hogan: How Facebook divides us [Times Literary Supplement]

27 October 2016 / 1000 words / 5 minutes

“Filter bubbles can create an increasingly fractured population, such as the one developing in America. For the many people shocked by the result of the British EU referendum, we can also partially blame filter bubbles: Facebook literally filters our friends’ views that are least palatable to us, yielding a doctored account of their personalities.”

Bernie Hogan says it’s time Facebook considered ways to use the information it has about us to bring us together across political, ideological and cultural lines, rather than hide us from each other or push us into polarized and hostile camps. He says it’s not only possible for Facebook to help mitigate the issues of filter bubbles and context collapse; it’s imperative, and it’s surprisingly simple.

 

2. Luciano Floridi: Fake news and a 400-year-old problem: we need to resolve the ‘post-truth’ crisis [the Guardian]

29 November 2016 / 1000 words / 5 minutes

“The internet age made big promises to us: a new period of hope and opportunity, connection and empathy, expression and democracy. Yet the digital medium has aged badly because we allowed it to grow chaotically and carelessly, lowering our guard against the deterioration and pollution of our infosphere. […] some of the costs of misinformation may be hard to reverse, especially when confidence and trust are undermined. The tech industry can and must do better to ensure the internet meets its potential to support individuals’ wellbeing and social good.”

The Internet echo chamber satiates our appetite for pleasant lies and reassuring falsehoods, and has become the defining challenge of the 21st century, says Luciano Floridi. So far, the strategy for technology companies has been to deal with the ethical impact of their products retrospectively, but this is not good enough, he says. We need to shape and guide the future of the digital, and stop making it up as we go along. It is time to work on an innovative blueprint for a better kind of infosphere.

 

3. Philip Howard: Facebook and Twitter’s real sin goes beyond spreading fake news

3 January 2017 / 1000 words / 5 minutes

“With the data at their disposal and the platforms they maintain, social media companies could raise standards for civility by refusing to accept ad revenue for placing fake news. They could let others audit and understand the algorithms that determine who sees what on a platform. Just as important, they could be the platforms for doing better opinion, exit and deliberative polling.”

Only Facebook and Twitter know how pervasive fabricated news stories and misinformation campaigns have become during referendums and elections, says Philip Howard — and allowing fake news and computational propaganda to target specific voters is an act against democratic values. But in a time of weakening polling systems, withholding data about public opinion is actually their major crime against democracy, he says.

 

4. Brent Mittelstadt: Should there be a better accounting of the algorithms that choose our news for us?

7 December 2016 / 1800 words / 8 minutes

“Transparency is often treated as the solution, but merely opening up algorithms to public and individual scrutiny will not in itself solve the problem. Information about the functionality and effects of personalisation must be meaningful to users if anything is going to be accomplished. At a minimum, users of personalisation systems should be given more information about their blind spots, about the types of information they are not seeing, or where they lie on the map of values or criteria used by the system to tailor content to users.”

A central ideal of democracy is that political discourse should allow a fair and critical exchange of ideas and values. But political discourse is unavoidably mediated by the mechanisms and technologies we use to communicate and receive information, says Brent Mittelstadt. And content personalization systems and the algorithms they rely upon create a new type of curated media that can undermine the fairness and quality of political discourse.

 

5. Heather Ford: Verification of crowd-sourced information: is this ‘crowd wisdom’ or machine wisdom?

19 November 2013 / 1400 words / 6 minutes

“A key question being asked in the design of future verification mechanisms is the extent to which verification work should be done by humans or non-humans (machines). Here, verification is not a binary categorisation, but rather there is a spectrum between human and non-human verification work, and indeed, projects like Ushahidi, Wikipedia and Galaxy Zoo have all developed different verification mechanisms.”

‘Human’ verification, a process of checking whether a particular report meets a group’s truth standards, is an acutely social process, says Heather Ford. If code is law and if other aspects in addition to code determine how we can act in the world, it is important that we understand the context in which code is deployed. Verification is a practice that determines how we can trust information coming from a variety of sources — only by illuminating such practices and the variety of impacts that code can have in different environments can we begin to understand how code regulates our actions in crowdsourcing environments.

 

.. and just to prove we’re capable of understanding and acknowledging and assimilating multiple viewpoints on complex things, here’s Helen Margetts, with a different slant on filter bubbles: “Even if political echo chambers were as efficient as some seem to think, there is little evidence that this is what actually shapes election results. After all, by definition echo chambers preach to the converted. It is the undecided people who (for example) the Leave and Trump campaigns needed to reach. And from the research, it looks like they managed to do just that.”

 

The Authors

Bernie Hogan is a Research Fellow at the OII; his research interests lie at the intersection of social networks and media convergence.

Luciano Floridi is the OII’s Professor of Philosophy and Ethics of Information. His  research areas are the philosophy of Information, information and computer ethics, and the philosophy of technology.

Philip Howard is the OII’s Professor of Internet Studies. He investigates the impact of digital media on political life around the world.

Brent Mittelstadt is an OII Postdoc His research interests include the ethics of information handled by medical ICT, theoretical developments in discourse and virtue ethics, and epistemology of information.

Heather Ford completed her doctorate at the OII, where she studied how Wikipedia editors write history as it happens. She is now a University Academic Fellow in Digital Methods at the University of Leeds. Her forthcoming book “Fact Factories: Wikipedia’s Quest for the Sum of All Human Knowledge” will be published by MIT Press.

Helen Margetts is the OII’s Director, and Professor of Society and the Internet. She specialises in digital era government, politics and public policy, and data science and experimental methods. Her most recent book is Political Turbulence (Princeton).

 

Coming up! .. It’s the economy, stupid / Augmented reality and ambient fun / The platform economy / Power and development / Internet past and future / Government / Labour rights / The disconnected / Ethics / Staying critical

Five Pieces You Should Probably Read On: The US Election

This is the first post in a series that will uncover great writing by faculty and students at the Oxford Internet Institute, things you should probably know, and things that deserve to be brought out for another viewing. This week: The US Election.

This was probably the nastiest Presidential election in recent memory: awash with Twitter bots and scandal, polarisation and filter bubbles, accusations of interference by Russia and the Director of the FBI, and another shock result. We have written about electoral prediction elsewhere: instead, here are five pieces that consider the interaction of social media and democracy — the problems, but also potential ways forward.

 

1. James Williams: The Clickbait Candidate

10 October 2016 / 2700 words / 13 minutes

“Trump is very straightforwardly an embodiment of the dynamics of clickbait: he is the logical product (though not endpoint) in the political domain of a media environment designed to invite, and indeed incentivize, relentless competition for our attention […] Like clickbait or outrage cascades, Donald Trump is merely the sort of informational packet our media environment is designed to select for.”

James Williams says that now is probably the time to have that societal conversation about the design ethics of the attention economy — because in our current media environment, attention trumps everything.

 

2. Sam Woolley, Philip Howard: Bots Unite to Automate the Presidential Election [Wired]

15 May 2016 / 850 words / 4 minutes

“Donald Trump understands minority communities. Just ask Pepe Luis Lopez, Francisco Palma, and Alberto Contreras […] each tweeted in support of Trump after his victory in the Nevada caucuses earlier this year. The problem is, Pepe, Francisco, and Alberto aren’t people. They’re bots.”

It’s no surprise that automated spam accounts (or bots) are creeping into election politics, say Sam Woolley and Philip Howard. Demanding bot transparency would at least help clean up social media — which, for better or worse, is increasingly where presidents get elected.

 

3. Phil Howard: Is Social Media Killing Democracy?

15 November 2016 / 1100 words / 5 minutes

“This is the big year for computational propaganda — using immense data sets to manipulate public opinion over social media. Both the Brexit referendum and US election have revealed the limits of modern democracy, and social media platforms are currently setting those limits […] these technologies permit too much fake news, encourage our herding instincts, and aren’t expected to provide public goods.”

Phil Howard discusses ways to address fake news, audit social algorithms, and deal with social media’s “moral pass” — social media is damaging democracy, he says, but can also be used to save it.

 

4. Helen Margetts: Don’t Shoot the Messenger! What part did social media play in 2016 US e­lection?

15 November 2016 / 600 words / 3 minutes

“Rather than seeing social media solely as the means by which Trump ensnared his presidential goal, we should appreciate how they can provide a wealth of valuable data to understand the anger and despair that the polls missed, and to analyse political behaviour and opinion in the times ahead.”

New social information and visibility brings change to social behaviour, says Helen Margetts — ushering in political turbulence and unpredictability. Social media made visible what could have remain a country’s dark secret (hatred of women, rampant racism, etc.), but it will also underpin any radical counter-movement that emerges in the future.

 

5. Helen Margetts: Of course social media is transforming politics. But it’s not to blame for Brexit and Trump

9 January 2017 / 1700 words / 8 minutes

“Even if political echo chambers were as efficient as some seem to think, there is little evidence that this is what actually shapes election results. After all, by definition echo chambers preach to the converted. It is the undecided people who (for example) the Leave and Trump campaigns needed to reach. And from the research, it looks like they managed to do just that.”

Politics is a lot messier in the social media era than it used to be, says Helen Margetts, but rather than blaming social media for undermining democracy, we should be thinking about how we can improve the (inevitably major) part that it plays.

 

The Authors

James Williams is an OII doctoral candidate, studying the ethics of attention and persuasion in technology design.

Sam Woolley is a Research Assistant on the OII’s Computational Propaganda project; he is interested in political bots, and the intersection of political communication and automation.

Philip Howard is the OII’s Professor of Internet Studies and PI of the Computational Propaganda project. He investigates the impact of digital media on political life around the world.

Helen Margetts is the OII’s Director, and Professor of Society and the Internet. She specialises in digital era government, politics and public policy, and data science and experimental methods. Her most recent book is Political Turbulence (Princeton).

 

Coming up .. Fake news and filter bubbles / It’s the economy, stupid / Augmented reality and ambient fun / The platform economy / Power and development / Internet past and future / Government / Labour rights / The disconnected / Ethics / Staying critical

#5OIIPieces

Five Pieces You Should Probably Read On: The US Election

This is the first post in a series that will uncover great writing by faculty and students at the Oxford Internet Institute, things you should probably know, and things that deserve to be brought out for another viewing. This week: The US Election.

This was probably the nastiest Presidential election in recent memory: awash with Twitter bots and scandal, polarisation and filter bubbles, accusations of interference by Russia and the Director of the FBI, and another shock result. We have written about electoral prediction elsewhere: instead, here are five pieces that consider the interaction of social media and democracy — the problems, but also potential ways forward.

 

1. James Williams: The Clickbait Candidate

10 October 2016 / 2700 words / 13 minutes

“Trump is very straightforwardly an embodiment of the dynamics of clickbait: he is the logical product (though not endpoint) in the political domain of a media environment designed to invite, and indeed incentivize, relentless competition for our attention […] Like clickbait or outrage cascades, Donald Trump is merely the sort of informational packet our media environment is designed to select for.”

James Williams says that now is probably the time to have that societal conversation about the design ethics of the attention economy — because in our current media environment, attention trumps everything.

 

2. Sam Woolley, Philip Howard: Bots Unite to Automate the Presidential Election [Wired]

15 May 2016 / 850 words / 4 minutes

“Donald Trump understands minority communities. Just ask Pepe Luis Lopez, Francisco Palma, and Alberto Contreras […] each tweeted in support of Trump after his victory in the Nevada caucuses earlier this year. The problem is, Pepe, Francisco, and Alberto aren’t people. They’re bots.”

It’s no surprise that automated spam accounts (or bots) are creeping into election politics, say Sam Woolley and Philip Howard. Demanding bot transparency would at least help clean up social media — which, for better or worse, is increasingly where presidents get elected.

 

3. Phil Howard: Is Social Media Killing Democracy?

15 November 2016 / 1100 words / 5 minutes

“This is the big year for computational propaganda — using immense data sets to manipulate public opinion over social media. Both the Brexit referendum and US election have revealed the limits of modern democracy, and social media platforms are currently setting those limits […] these technologies permit too much fake news, encourage our herding instincts, and aren’t expected to provide public goods.”

Phil Howard discusses ways to address fake news, audit social algorithms, and deal with social media’s “moral pass” — social media is damaging democracy, he says, but can also be used to save it.

 

4. Helen Margetts: Don’t Shoot the Messenger! What part did social media play in 2016 US e­lection?

15 November 2016 / 600 words / 3 minutes

“Rather than seeing social media solely as the means by which Trump ensnared his presidential goal, we should appreciate how they can provide a wealth of valuable data to understand the anger and despair that the polls missed, and to analyse political behaviour and opinion in the times ahead.”

New social information and visibility brings change to social behaviour, says Helen Margetts — ushering in political turbulence and unpredictability. Social media made visible what could have remain a country’s dark secret (hatred of women, rampant racism, etc.), but it will also underpin any radical counter-movement that emerges in the future.

 

5. Helen Margetts: Of course social media is transforming politics. But it’s not to blame for Brexit and Trump

9 January 2017 / 1700 words / 8 minutes

“Even if political echo chambers were as efficient as some seem to think, there is little evidence that this is what actually shapes election results. After all, by definition echo chambers preach to the converted. It is the undecided people who (for example) the Leave and Trump campaigns needed to reach. And from the research, it looks like they managed to do just that.”

Politics is a lot messier in the social media era than it used to be, says Helen Margetts, but rather than blaming social media for undermining democracy, we should be thinking about how we can improve the (inevitably major) part that it plays.

 

The Authors

James Williams is an OII doctoral candidate, studying the ethics of attention and persuasion in technology design.

Sam Woolley is a Research Assistant on the OII’s Computational Propaganda project; he is interested in political bots, and the intersection of political communication and automation.

Philip Howard is the OII’s Professor of Internet Studies and PI of the Computational Propaganda project. He investigates the impact of digital media on political life around the world.

Helen Margetts is the OII’s Director, and Professor of Society and the Internet. She specialises in digital era government, politics and public policy, and data science and experimental methods. Her most recent book is Political Turbulence (Princeton).

 

Coming up .. Fake news and filter bubbles / It’s the economy, stupid / Augmented reality and ambient fun / The platform economy / Power and development / Internet past and future / Government / Labour rights / The disconnected / Ethics / Staying critical

#5OIIPieces

Of course social media is transforming politics. But it’s not to blame for Brexit and Trump

After Brexit and the election of Donald Trump, 2016 will be remembered as the year of cataclysmic democratic events on both sides of the Atlantic. Social media has been implicated in the wave of populism that led to both these developments.

Attention has focused on echo chambers, with many arguing that social media users exist in ideological filter bubbles, narrowly focused on their own preferences, prey to fake news and political bots, reinforcing polarization and leading voters to turn away from the mainstream. Mark Zuckerberg has responded with the strange claim that his company (built on $5 billion of advertising revenue) does not influence people’s decisions.

So what role did social media play in the political events of 2016?

Political turbulence and the new populism

There is no doubt that social media has brought change to politics. From the waves of protest and unrest in response to the 2008 financial crisis, to the Arab spring of 2011, there has been a generalized feeling that political mobilization is on the rise, and that social media had something to do with it.

Our book investigating the relationship between social media and collective action, Political Turbulence, focuses on how social media allows new, “tiny acts” of political participation (liking, tweeting, viewing, following, signing petitions and so on), which turn social movement theory around. Rather than identifying with issues, forming collective identity and then acting to support the interests of that identity – or voting for a political party that supports it – in a social media world, people act first, and think about it, or identify with others later, if at all.

These tiny acts of participation can scale up to large-scale mobilizations, such as demonstrations, protests or campaigns for policy change. But they almost always don’t. The overwhelming majority (99.99%) of petitions to the UK or US governments fail to get the 100,000 signatures required for a parliamentary debate (UK) or an official response (US).

The very few that succeed do so very quickly on a massive scale (petitions challenging the Brexit and Trump votes immediately shot above 4 million signatures, to become the largest petitions in history), but without the normal organizational or institutional trappings of a social or political movement, such as leaders or political parties – the reason why so many of the Arab Spring revolutions proved disappointing.

This explosive rise, non-normal distribution and lack of organization that characterizes contemporary politics can explain why many political developments of our time seem to come from nowhere. It can help to understand the shock waves of support that brought us the Italian Five Star Movement, Podemos in Spain, Jeremy Corbyn, Bernie Sanders, and most recently Brexit and Trump – all of which have campaigned against the “establishment” and challenged traditional political institutions to breaking point.

Each successive mobilization has made people believe that challengers from outside the mainstream are viable – and that is in part what has brought us unlikely results on both sides of the Atlantic. But it doesn’t explain everything.

We’ve had waves of populism before – long before social media (indeed many have made parallels between the politics of 2016 and that of the 1930s). While claims that social media feeds are the biggest threat to democracy, leading to the “disintegration of the general will” and “polarization that drives populism” abound, hard evidence is more difficult to find.

The myth of the echo chamber

The mechanism that is most often offered for this state of events is the existence of echo chambers or filter bubbles. The argument goes that first social media platforms feed people the news that is closest to their own ideological standpoint (estimated from their previous patterns of consumption) and second, that people create their own personalized information environments through their online behaviour, selecting friends and news sources that back up their world view.

Once in these ideological bubbles, people are prey to fake news and political bots that further reinforce their views. So, some argue, social media reinforces people’s current views and acts as a polarizing force on politics, meaning that “random exposure to content is gone from our diets of news and information”.

Really? Is exposure less random than before? Surely the most perfect echo chamber would be the one occupied by someone who only read the Daily Mail in the 1930s – with little possibility of other news – or someone who just watches Fox News? Can our new habitat on social media really be as closed off as these environments, when our digital networks are so very much larger and more heterogeneous than anything we’ve had before?

Research suggests not. A recent large-scale survey (of 50,000 news consumers in 26 countries) shows how those who do not use social media on average come across news from significantly fewer different online sources than those who do. Social media users, it found, receive an additional “boost” in the number of news sources they use each week, even if they are not actually trying to consume more news. These findings are reinforced by an analysis of Facebook data, where 8.8 billion posts, likes and comments were posted through the US election.

Recent research published in Science shows that algorithms play less of a role in exposure to attitude-challenging content than individuals’ own choices and that “on average more than 20% of an individual’s Facebook friends who report an ideological affiliation are from the opposing party”, meaning that social media exposes individuals to at least some ideologically cross-cutting viewpoints: “24% of the hard content shared by liberals’ friends is cross-cutting, compared to 35% for conservatives” (the equivalent figures would be 40% and 45% if random).

In fact, companies have no incentive to create hermetically sealed (as I have heard one commentator claim) echo chambers. Most of social media content is not about politics (sorry guys) – most of that £5 billion advertising revenue does not come from political organizations. So any incentives that companies have to create echo chambers – for the purposes of targeted advertising, for example – are most likely to relate to lifestyle choices or entertainment preferences, rather than political attitudes.

And where filter bubbles do exist they are constantly shifting and sliding – easily punctured by a trending cross-issue item (anybody looking at #Election2016 shortly before polling day would have seen a rich mix of views, while having little doubt about Trump’s impending victory).

And of course, even if political echo chambers were as efficient as some seem to think, there is little evidence that this is what actually shapes election results. After all, by definition echo chambers preach to the converted. It is the undecided people who (for example) the Leave and Trump campaigns needed to reach.

And from the research, it looks like they managed to do just that. A barrage of evidence suggests that such advertising was effective in the 2015 UK general election (where the Conservatives spent 10 times as much as Labour on Facebook advertising), in the EU referendum (where the Leave campaign also focused on paid Facebook ads) and in the presidential election, where Facebook advertising has been credited for Trump’s victory, while the Clinton campaign focused on TV ads. And of course, advanced advertising techniques might actually focus on those undecided voters from their conversations. This is not the bottom-up political mobilization that fired off support for Podemos or Bernie Sanders. It is massive top-down advertising dollars.

Ironically however, these huge top-down political advertising campaigns have some of the same characteristics as the bottom-up movements discussed above, particularly sustainability. Former New York Governor Mario Cuomo’s dictum that candidates “campaign in poetry and govern in prose” may need an update. Barack Obama’s innovative campaigns of online social networks, micro-donations and matching support were miraculous, but the extent to which he developed digital government or data-driven policy-making in office was disappointing. Campaign digitally, govern in analogue might be the new mantra.

Chaotic pluralism

Politics is a lot messier in the social media era than it used to be – whether something takes off and succeeds in gaining critical mass is far more random than it appears to be from a casual glance, where we see only those that succeed.

In Political Turbulence, we wanted to identify the model of democracy that best encapsulates politics intertwined with social media. The dynamics we observed seem to be leading us to a model of “chaotic pluralism”, characterized by diversity and heterogeneity – similar to early pluralist models – but also by non-linearity and high interconnectivity, making liberal democracies far more disorganized, unstable and unpredictable than the architects of pluralist political thought ever envisaged.

Perhaps rather than blaming social media for undermining democracy, we should be thinking about how we can improve the (inevitably major) part that it plays.

Within chaotic pluralism, there is an urgent need for redesigning democratic institutions that can accommodate new forms of political engagement, and respond to the discontent, inequalities and feelings of exclusion – even anger and alienation – that are at the root of the new populism. We should be using social media to listen to (rather than merely talk at) the expression of these public sentiments, and not just at election time.

Many political institutions – for example, the British Labour Party, the US Republican Party, and the first-past-the-post electoral system shared by both countries – are in crisis, precisely because they have become so far removed from the concerns and needs of citizens. Redesign will need to include social media platforms themselves, which have rapidly become established as institutions of democracy and will be at the heart of any democratic revival.

As these platforms finally start to admit to being media companies (rather than tech companies), we will need to demand human intervention and transparency over algorithms that determine trending news; factchecking (where Google took the lead); algorithms that detect fake news; and possibly even “public interest” bots to counteract the rise of computational propaganda.

Meanwhile, the only thing we can really predict with certainty is that unpredictable things will happen and that social media will be part of our political future.

Discussing the echoes of the 1930s in today’s politics, the Wall Street Journal points out how Roosevelt managed to steer between the extremes of left and right because he knew that “public sentiments of anger and alienation aren’t to be belittled or dismissed, for their causes can be legitimate and their consequences powerful”. The path through populism and polarization may involve using the opportunity that social media presents to listen, understand and respond to these sentiments.

This piece draws on research from Political Turbulence: How Social Media Shape Collective Action (Princeton University Press, 2016), by Helen Margetts, Peter John, Scott Hale and Taha Yasseri.

It is cross-posted from the World Economic Forum, where it was first published on 22 December 2016.

Can we predict electoral outcomes from Wikipedia traffic?

As digital technologies become increasingly integrated into the fabric of social life their ability to generate large amounts of information about the opinions and activities of the population increases. The opportunities in this area are enormous: predictions based on socially generated data are much cheaper than conventional opinion polling, offer the potential to avoid classic biases inherent in asking people to report their opinions and behaviour, and can deliver results much quicker and be updated more rapidly.

In their article published in EPJ Data Science, Taha Yasseri and Jonathan Bright develop a theoretically informed prediction of election results from socially generated data combined with an understanding of the social processes through which the data are generated. They can thereby explore the predictive power of socially generated data while enhancing theory about the relationship between socially generated data and real world outcomes. Their particular focus is on the readership statistics of politically relevant Wikipedia articles (such as those of individual political parties) in the time period just before an election.

By applying these methods to a variety of different European countries in the context of the 2009 and 2014 European Parliament elections they firstly show that the relative change in number of page views to the general Wikipedia page on the election can offer a reasonable estimate of the relative change in election turnout at the country level. This supports the idea that increases in online information seeking at election time are driven by voters who are considering voting.

Second, they show that a theoretically informed model based on previous national results, Wikipedia page views, news media mentions, and basic information about the political party in question can offer a good prediction of the overall vote share of the party in question. Third, they present a model for predicting change in vote share (i.e., voters swinging towards and away from a party), showing that Wikipedia page-view data provide an important increase in predictive power in this context.

This relationship is exaggerated in the case of newer parties — consistent with the idea that voters don’t seek information uniformly about all parties at election time. Rather, they behave like ‘cognitive misers’, being more likely to seek information on new political parties with which they do not have previous experience and being more likely to seek information only when they are actually changing the way they vote.

In contrast, there was no evidence of a ‘media effect’: there was little correlation between news media mentions and overall Wikipedia traffic patterns. Indeed, the news media and Wikipedia appeared to be biased towards different things: with the news favouring incumbent parties, and Wikipedia favouring new ones.

Read the full article: Yasseri, T. and Bright, J. (2016) Wikipedia traffic data and electoral prediction: towards theoretically informed models. EPJ Data Science. 5 (1).

We caught up with the authors to explore the implications of the work.

Ed: Wikipedia represents a vast amount of not just content, but also user behaviour data. How did you access the page view stats — but also: is anyone building dynamic visualisations of Wikipedia data in real time?

Taha and Jonathan: Wikipedia makes its page view data available for free (in the same way as it makes all of its information available!). You can find the data here, along with some visualisations

Ed: Why did you use Wikipedia data to examine election prediction rather than (the I suppose the more fashionable) Twitter? How do they compare as data sources?

Taha and Jonathan: One of the big problems with using Twitter to predict things like elections is that contributing on social media is a very public thing and people are quite conscious of this. For example, some parties are seen as unfashionable so people might not make their voting choice explicit. Hence overall social media might seem to be saying one thing whereas actually people are thinking another.

By contrast, looking for information online on a website like Wikipedia is an essentially private activity so there aren’t these social biases. In other words, on Wikipedia we can directly have access to transactional data on what people do, rather than what they say or prefer to say.

Ed: How did these results and findings compare with the social media analysis done as part of our UK General Election 2015 Election Night Data Hack? (long title..)

Taha and Jonathan: The GE2015 data hack looked at individual politicians. We found that having a Wikipedia page is becoming increasingly important — over 40% of Labour and Conservative Party candidates had an individual Wikipedia page. We also found that this was highly correlated with Twitter presence — being more active on one network also made you more likely to be active on the other one. And we found some initial evidence that social media reaction was correlated with votes, though there is a lot more work to do here!

Ed: Can you see digital social data analysis replacing (or maybe just complementing) opinion polling in any meaningful way? And what problems would need to be addressed before that happened: e.g. around representative sampling, data cleaning, and weeding out bots?

Taha and Jonathan: Most political pundits are starting to look at a range of indicators of popularity — for example, not just voting intention, but also ratings of leadership competence, economic performance, etc. We can see good potential for social data to become part of this range of popularity indicator. However we don’t think it will replace polling just yet; the use of social media is limited to certain demographics. Also, the data collected from social media are often very shallow, not allowing for validation. In the case of Wikipedia, for example, we only know how many times each page is viewed, but we don’t know by how many people and from where.

Ed: You do a lot of research with Wikipedia data — has that made you reflect on your own use of Wikipedia?

Taha and Jonathan: It’s interesting to think about this activity of getting direct information about politicians — it’s essentially a new activity, something you couldn’t do in the pre-digital age. I know that I personally [Jonathan] use it to find out things about politicians and political parties — it would be interesting to know more about why other people are using it as well. This could have a lot of impacts. One thing Wikipedia has is a really long memory, in a way that other means of getting information on politicians (such as newspapers) perhaps don’t. We could start to see this type of thing becoming more important in electoral politics.

[Taha] .. since my research has been mostly focused on Wikipedia edit wars between human and bot editors, I have naturally become more cautious about the information I find on Wikipedia. When it comes to sensitive topics, sach as politics, Wikipedia is a good point to start, but not a great point to end the search!


Taha Yasseri and Jonathan Bright were talking to blog editor David Sutcliffe.

Is Social Media Killing Democracy?

Donald Trump in Reno, Nevada, by Darron Birgenheier (Flickr).
Donald Trump in Reno, Nevada, by Darron Birgenheier (Flickr).

This is the big year for computational propaganda — using immense data sets to manipulate public opinion over social media. Both the Brexit referendum and US election have revealed the limits of modern democracy, and social media platforms are currently setting those limits.

Platforms like Twitter and Facebook now provide a structure for our political lives. We’ve always relied on many kinds of sources for our political news and information. Family, friends, news organizations, charismatic politicians certainly predate the internet. But whereas those are sources of information, social media now provides the structure for political conversation. And the problem is that these technologies permit too much fake news, encourage our herding instincts, and aren’t expected to provide public goods.

First, social algorithms allow fake news stories from untrustworthy sources to spread like wildfire over networks of family and friends. Many of us just assume that there is a modicum of truth-in-advertising. We expect this from advertisements for commercial goods and services, but not from politicians and political parties. Occasionally a political actor gets punished for betraying the public trust through their misinformation campaigns. But in the United States “political speech” is completely free from reasonable public oversight, and in most other countries the media organizations and public offices for watching politicians are legally constrained, poorly financed, or themselves untrustworthy. Research demonstrates that during the campaigns for Brexit and the U.S. presidency, large volumes of fake news stories, false factoids, and absurd claims were passed over social media networks, often by Twitter’s highly automated accounts and Facebook’s algorithms.

Second, social media algorithms provide very real structure to what political scientists often call “elective affinity” or “selective exposure”. When offered the choice of who to spend time with or which organizations to trust, we prefer to strengthen our ties to the people and organizations we already know and like. When offered a choice of news stories, we prefer to read about the issues we already care about, from pundits and news outlets we’ve enjoyed in the past. Random exposure to content is gone from our diets of news and information. The problem is not that we have constructed our own community silos — humans will always do that. The problem is that social media networks take away the random exposure to new, high-quality information.

This is not a technological problem. We are social beings and so we will naturally look for ways to socialize, and we will use technology to socialize each other. But technology could be part of the solution. A not-so-radical redesign might occasionally expose us to new sources of information, or warn us when our own social networks are getting too bounded.

The third problem is that technology companies, including Facebook and Twitter, have been given a “moral pass” on the obligations we hold journalists and civil society groups to.

In most democracies, the public policy and exit polling systems have been broken for a decade. Many social scientists now find that big data, especially network data, does a better job of revealing public preferences than traditional random digit dial systems. So Facebook actually got a moral pass twice this year. Their data on public opinion would have certainly informed the Brexit debate, and their data on voter preferences would certainly have informed public conversation during the US election.

Facebook has run several experiments now, published in scholarly journals, demonstrating that they have the ability to accurately anticipate and measure social trends. Whereas journalists and social scientists feel an obligation to openly analyze and discuss public preferences, we do not expect this of Facebook. The network effects that clearly were unmeasured by pollsters were almost certainly observable to Facebook. When it comes to news and information about politics, or public preferences on important social questions, Facebook has a moral obligation to share data and prevent computational propaganda. The Brexit referendum and US election have taught us that Twitter and Facebook are now media companies. Their engineering decisions are effectively editorial decisions, and we need to expect more openness about how their algorithms work. And we should expect them to deliberate about their editorial decisions.

There are some ways to fix these problems. Opaque software algorithms shape what people find in their news feeds. We’ve all noticed fake news stories (often called clickbait), and while these can be an entertaining part of using the internet, it is bad when they are used to manipulate public opinion. These algorithms work as “bots” on social media platforms like Twitter, where they were used in both the Brexit and US presidential campaign to aggressively advance the case for leaving Europe and the case for electing Trump. Similar algorithms work behind the scenes on Facebook, where they govern what content from your social networks actually gets your attention.

So the first way to strengthen democratic practices is for academics, journalists, policy makers and the interested public to audit social media algorithms. Was Hillary Clinton really replaced by an alien in the final weeks of the 2016 campaign? We all need to be able to see who wrote this story, whether or not it is true, and how it was spread. Most important, Facebook should not allow such stories to be presented as news, much less spread. If they take ad revenue for promoting political misinformation, they should face the same regulatory punishments that a broadcaster would face for doing such a public disservice.

The second problem is a social one that can be exacerbated by information technologies. This means it can also be mitigated by technologies. Introducing random news stories and ensuring exposure to high quality information would be a simple — and healthy — algorithmic adjustment to social media platforms. The third problem could be resolved with moral leadership from within social media firms, but a little public policy oversight from elections officials and media watchdogs would help. Did Facebook see that journalists and pollsters were wrong about public preferences? Facebook should have told us if so, and shared that data.

Social media platforms have provided a structure for spreading around fake news, we users tend to trust our friends and family, and we don’t hold media technology firms accountable for degrading our public conversations. The next big thing for technology evolution is the Internet of Things, which will generate massive amounts of data that will further harden these structures. Is social media damaging democracy? Yes, but we can also use social media to save democracy.