Menu

Methods

Articles from Policy & Internet, Democracy, Methods, Politics & Government

Do online consultations make citizens more satisfied with local democracy?

Previous article Next article
by Professor Tobias Escher

We find that giving citizens an opportunity to have a say in political decisions influences their opinions about local politics—but not all of them are satisfied.

by Professor Tobias Escher

In political discussions, the legitimacy crisis of democracy is a common theme. Even though citizens value the concept of democracy, they are often unhappy with how it is implemented. This issue also extends to the local level, where political decisions directly affect citizens. It is worth noting that whenever a local conflict arises, citizens (and policymakers themselves) often call for more participation as a means to increase the legitimacy of such decisions. As a result, municipalities frequently conduct public consultations and increasingly use the Internet to enable online participation. But what role can these online consultations play in improving legitimacy?  In a recent study published by Policy & Internet, Bastian Rottinghaus and I investigated how participation in local consultation processes affects attitudes toward local politics. To achieve this, we examined participation procedures in which three German municipalities consulted their citizens on local cycling infrastructure. In each case, citizens submitted, commented on, and evaluated proposals through an online platform. After the end of these consultations, we surveyed nearly 600 citizens who had participated in these procedures. Here are some of our key findings: • The participation processes influenced the attitudes of those who participated in these consultations. • For many participants, the positive effect that was hoped for did indeed occur: they were more positive about local institutions (mayor, administration) and local politics as a whole. The decisive factor for the assessment was whether one expected local politics to take the citizens’ proposals seriously and act upon them. In other words, the result of the process was more important to attitudes than the process itself.  • It is worth noting that this also applies to those with negative views of local politics. However, previous experience with local politics also played a role: those who already had a higher level of satisfaction and trust in the municipality became more positive by participating.  • At the same time, participation may reduce satisfaction, especially…

Governance & Security, Interviews, Methods

How policy makers can extract meaningful public opinion data from social media to inform their actions

Previous article Next article
by David Sutcliffe

Examining how the information available on social media can support the actions of politicians and bureaucrats along the policy cycle.

by David Sutcliffe

Social media analysis can provide insight into the mobilisation processes of stakeholders in response to government actions. Image of No-TAV protestors by Darren Johnson (Flickr: CC BY-NC-ND 2.0).

The role of social media in fostering the transparency of governments and strengthening the interaction between citizens and public administrations has been widely studied. Scholars have highlighted how online citizen-government and citizen-citizen interactions favour debates on social and political matters, and positively affect citizens’ interest in political processes, like elections, policy agenda setting, and policy implementation. However, while top-down social media communication between public administrations and citizens has been widely examined, the bottom-up side of this interaction has been largely overlooked. In their Policy & Internet article “The ‘Social Side’ of Public Policy: Monitoring Online Public Opinion and Its Mobilisation During the Policy Cycle,” Andrea Ceron and Fedra Negri aim to bridge the gap between knowledge and practice, by examining how the information available on social media can support the actions of politicians and bureaucrats along the policy cycle. Policymakers, particularly politicians, have always been interested in knowing citizens’ preferences, in measuring their satisfaction and in receiving feedback on their activities. Using the technique of Supervised Aggregated Sentiment Analysis, the authors show that meaningful information on public services, programmes, and policies can be extracted from the unsolicited comments posted by social media users, particularly those posted on Twitter. They use this technique to extract and analyse citizen opinion on two major public policies (on labour market reform and school reform) that drove the agenda of the Matteo Renzi cabinet in Italy between 2014 and 2015. They show how online public opinion reacted to the different policy alternatives formulated and discussed during the adoption of the policies. They also demonstrate how social media analysis allows monitoring of the mobilisation and de-mobilisation processes of rival stakeholders in response to the various amendments adopted by the government, with results comparable to those of a survey and a public consultation that were undertaken by the government. We caught up with the authors to discuss their findings: Ed.: You say that this form of opinion…

Social media analysis can provide insight into the mobilisation processes of stakeholders in response to government actions. Image of No-TAV protestors by Darren Johnson (Flickr: CC BY-NC-ND 2.0).

Health, Methods, Social Data Science, Wellbeing

Facts and figures or prayers and hugs: how people with different health conditions support each other online

Previous article Next article
by admin

Online support groups are one of the major ways in which the Internet has fundamentally changed how people experience health and health care.

by admin

Online forums are important means of people living with health conditions to obtain both emotional and informational support from this in a similar situation. Pictured: The Alzheimer Society of B.C. unveiled three life-size ice sculptures depicting important moments in life. The ice sculptures will melt, representing the fading of life memories on the dementia journey. Image: bcgovphotos (Flickr)

Online support groups are being used increasingly by individuals who suffer from a wide range of medical conditions. OII DPhil Student Ulrike Deetjen’s recent article with John Powell, Informational and emotional elements in online support groups: a Bayesian approach to large-scale content analysis uses machine learning to examine the role of online support groups in the healthcare process. They categorise 40,000 online posts from one of the most well-used forums to show how users with different conditions receive different types of support. Online support groups are one of the major ways in which the Internet has fundamentally changed how people experience health and health care. They provide a platform for health discussions formerly restricted by time and place, enable individuals to connect with others in similar situations, and facilitate open, anonymous communication. Previous studies have identified that individuals primarily obtain two kinds of support from online support groups: informational (for example, advice on treatments, medication, symptom relief, and diet) and emotional (for example, receiving encouragement, being told they are in others’ prayers, receiving “hugs”, or being told that they are not alone). However, existing research has been limited as it has often used hand-coded qualitative approaches to contrast both forms of support, thereby only examining relatively few posts (<1,000) for one or two conditions. In contrast, our research employed a machine-learning approach suitable for uncovering patterns in “big data”. Using this method a computer (which initially has no knowledge of online support groups) is given examples of informational and emotional posts (2,000 examples in our study). It then “learns” what words are associated with each category (emotional: prayers, sorry, hugs, glad, thoughts, deal, welcome, thank, god, loved, strength, alone, support, wonderful, sending; informational: effects, started, weight, blood, eating, drink, dose, night, recently, taking, side, using, twice, meal). The computer then uses this knowledge to assess new posts, and decide whether they contain more emotional or informational support. With this approach we were able to determine the emotional or informational content of 40,000…

Online forums are important means of people living with health conditions to obtain both emotional and informational support from this in a similar situation. Pictured: The Alzheimer Society of B.C. unveiled three life-size ice sculptures depicting important moments in life. The ice sculptures will melt, representing the fading of life memories on the dementia journey. Image: bcgovphotos (Flickr)

Methods, Politics & Government

How easy is it to research the Chinese web?

Previous article Next article
by Han-Teng Liao

The research expectations seem to be that control and intervention by Beijing will be most likely on political and cultural topics, not likely on economic or entertainment ones.

by Han-Teng Liao

Access to data from the Chinese Web, like other Web data, depends on platform policies, the level of data openness, and the availability of data intermediary and tools. Image of a Chinese Internet cafe by Hal Dick.

Ed: How easy is it to request or scrape data from the “Chinese Web”? And how much of it is under some form of government control? Han-Teng: Access to data from the Chinese Web, like other Web data, depends on the policies of platforms, the level of data openness, and the availability of data intermediary and tools. All these factors have direct impacts on the quality and usability of data. Since there are many forms of government control and intentions, increasingly not just the websites inside mainland China under Chinese jurisdiction, but also the Chinese “soft power” institutions and individuals telling the “Chinese story” or “Chinese dream” (as opposed to “American dreams”), it requires case-by-case research to determine the extent and level of government control and interventions. Based on my own research on Chinese user-generated encyclopaedias and Chinese-language twitter and Weibo, the research expectations seem to be that control and intervention by Beijing will be most likely on political and cultural topics, not likely on economic or entertainment ones. This observation is linked to how various forms of government control and interventions are executed, which often requires massive data and human operations to filter, categorise and produce content that are often based on keywords. It is particularly true for Chinese websites in mainland China (behind the Great Firewall, excluding Hong Kong and Macao), where private website companies execute these day-to-day operations under the directives and memos of various Chinese party and government agencies. Of course there is some extra layer of challenges if researchers try to request content and traffic data from the major Chinese websites for research, especially regarding censorship. Nonetheless, since most Web content data is open, researchers such as Professor Fu in Hong Kong University manage to scrape data sample from Weibo, helping researchers like me to access the data more easily. These openly collected data can then be used to measure potential government control, as has…

Access to data from the Chinese Web, like other Web data, depends on platform policies, the level of data openness, and the availability of data intermediary and tools. Image of a Chinese Internet cafe by Hal Dick.

Mapping, Methods, Politics & Government, Social Data Science

Mapping collective public opinion in the Russian blogosphere

Previous article Next article
by Olessia Koltsova

The Russian language blogosphere counts about 85 million blogs—an amount far beyond the capacities of any government to control—and is thereby able to function as a mass medium of “public opinion” and also to exercise influence.

by Olessia Koltsova

Widely reported as fraudulent, the 2011 Russian Parliamentary elections provoked mass street protest action by tens of thousands of people in Moscow and cities and towns across Russia. Image by Nikolai Vassiliev.

Blogs are becoming increasingly important for agenda setting and formation of collective public opinion on a wide range of issues. In countries like Russia where the Internet is not technically filtered, but where the traditional media is tightly controlled by the state, they may be particularly important. The Russian language blogosphere counts about 85 million blogs—an amount far beyond the capacities of any government to control—and the Russian search engine Yandex, with its blog rating service, serves as an important reference point for Russia’s educated public in its search of authoritative and independent sources of information. The blogosphere is thereby able to function as a mass medium of “public opinion” and also to exercise influence. One topic that was particularly salient over the period we studied concerned the Russian Parliamentary elections of December 2011. Widely reported as fraudulent, they provoked immediate and mass street protest action by tens of thousands of people in Moscow and cities and towns across Russia, as well as corresponding activity in the blogosphere. Protesters made effective use of the Internet to organise a movement that demanded cancellation of the parliamentary election results, and the holding of new and fair elections. These protests continued until the following summer, gaining widespread national and international attention. Most of the political and social discussion blogged in Russia is hosted on the blog platform LiveJournal. Some of these bloggers can claim a certain amount of influence; the top thirty bloggers have over 20,000 “friends” each, representing a good circulation for the average Russian newspaper. Part of the blogosphere may thereby resemble the traditional media; the deeper into the long tail of average bloggers, however, the more it functions as more as pure public opinion. This “top list” effect may be particularly important in societies (like Russia’s) where popularity lists exert a visible influence on bloggers’ competitive behaviour and on public perceptions of their significance. Given the influence of these top…

Widely reported as fraudulent, the 2011 Russian Parliamentary elections provoked mass street protest action by tens of thousands of people in Moscow and cities and towns across Russia. Image by Nikolai Vassiliev.

Mapping, Methods, Social Data Science

Edit wars! Measuring and mapping society’s most controversial topics

Previous article Next article
by taha yasseri

Although some topics are globally debated, like religion and politics, there are many topics which are controversial only in a single language edition. This reflects the local preferences and importances assigned to topics by different editorial communities.

by taha yasseri

Ed: How did you construct your quantitative measure of ‘conflict’? Did you go beyond just looking at content flagged by editors as controversial? Taha: Yes we did. Actually, we have shown that controversy measures based on “controversial” flags are not inclusive at all and although they might have high precision, they have very low recall. Instead, we constructed an automated algorithm to locate and quantify the editorial wars taking place on the Wikipedia platform. Our algorithm is based on reversions, i.e. when editors undo each other’s contributions. We focused specifically on mutual reverts between pairs of editors and we assigned a maturity score to each editor, based on the total volume of their previous contributions. While counting the mutual reverts, we used more weight for those ones committed by/on editors with higher maturity scores; as a revert between two experienced editors indicates a more serious problem. We always validated our method and compared it with other methods, using human judgement on a random selection of articles. Ed: Was there any discrepancy between the content deemed controversial by your own quantitative measure, and what the editors themselves had flagged? Taha: We were able to capture all the flagged content, but not all the articles found to be controversial by our method are flagged. And when you check the editorial history of those articles, you soon realise that they are indeed controversial but for some reason have not been flagged. It’s worth mentioning that the flagging process is not very well implemented in smaller language editions of Wikipedia. Even if the controversy is detected and flagged in English Wikipedia, it might not be in the smaller language editions. Our model is of course independent of the size and editorial conventions of different language editions. Ed: Were there any differences in the way conflicts arose/were resolved in the different language versions? Taha: We found the main differences to be the topics of controversial…

Methods, Social Data Science

The physics of social science: using big data for real-time predictive modelling

Previous article Next article
by taha yasseri

There are very interesting examples of using big data to make predictions about disease outbreaks, financial moves in the markets, social interactions based on human mobility patterns, election results, etc.

by taha yasseri

Ed: You are interested in analysis of big data to understand human dynamics; how much work is being done in terms of real-time predictive modelling using these data? Taha: The socially generated transactional data that we call “big data” have been available only very recently; the amount of data we now produce about human activities in a year is comparable to the amount that used to be produced in decades (or centuries). And this is all due to recent advancements in ICTs. Despite the short period of availability of big data, the use of them in different sectors including academia and business has been significant. However, in many cases, the use of big data is limited to monitoring and post hoc analysis of different patterns. Predictive models have been rarely used in combination with big data. Nevertheless, there are very interesting examples of using big data to make predictions about disease outbreaks, financial moves in the markets, social interactions based on human mobility patterns, election results, etc. Ed: What were the advantages of using Wikipedia as a data source for your study—as opposed to Twitter, blogs, Facebook or traditional media, etc.? Taha: Our results have shown that the predictive power of Wikipedia page view and edit data outperforms similar box office-prediction models based on Twitter data. This can partially be explained by considering the different nature of Wikipedia compared to social media sites. Wikipedia is now the number one source of online information, and Wikipedia article page view statistics show how much Internet users have been interested in knowing about a specific movie. And the edit counts—even more importantly—indicate the level of interest of the editors in sharing their knowledge about the movies with others. Both indicators are much stronger than what you could measure on Twitter, which is mainly the reaction of the users after watching or reading about the movie. The cost of participation in Wikipedia’s editorial process…

Methods, Politics & Government

Can text mining help handle the data deluge in public policy analysis?

Previous article Next article
by Aude Bicquelet

There has been a major shift in the policies of governments concerning participatory governance—that is, engaged, collaborative, and community-focused public policy.

by Aude Bicquelet

Policy makers today must contend with two inescapable phenomena. On the one hand, there has been a major shift in the policies of governments concerning participatory governance—that is, engaged, collaborative, and community-focused public policy. At the same time, a significant proportion of government activities have now moved online, bringing about “a change to the whole information environment within which government operates” (Margetts 2009, 6). Indeed, the Internet has become the main medium of interaction between government and citizens, and numerous websites offer opportunities for online democratic participation. The Hansard Society, for instance, regularly runs e-consultations on behalf of UK parliamentary select committees. For examples, e-consultations have been run on the Climate Change Bill (2007), the Human Tissue and Embryo Bill (2007), and on domestic violence and forced marriage (2008). Councils and boroughs also regularly invite citizens to take part in online consultations on issues affecting their area. The London Borough of Hammersmith and Fulham, for example, recently asked its residents for thier views on Sex Entertainment Venues and Sex Establishment Licensing policy. However, citizen participation poses certain challenges for the design and analysis of public policy. In particular, governments and organisations must demonstrate that all opinions expressed through participatory exercises have been duly considered and carefully weighted before decisions are reached. One method for partly automating the interpretation of large quantities of online content typically produced by public consultations is text mining. Software products currently available range from those primarily used in qualitative research (integrating functions like tagging, indexing, and classification), to those integrating more quantitative and statistical tools, such as word frequency and cluster analysis (more information on text mining tools can be found at the National Centre for Text Mining). While these methods have certainly attracted criticism and skepticism in terms of the interpretability of the output, they offer four important advantages for the analyst: namely categorisation, data reduction, visualisation, and speed. 1. Categorisation. When analysing the results…

Health, Methods, Social Data Science

Can Twitter provide an early warning function for the next pandemic?

Previous article Next article
by Patty Kostkova

While traditional surveillance systems will remain the pillars of public health, online media monitoring has added an important early-warning function, with social media bringing additional benefits to epidemic intelligence.

by Patty Kostkova

Communication of risk in any public health emergency is a complex task for healthcare agencies; a task made more challenging when citizens are bombarded with online information. Mexico City, 2009. Image by Eneas.

Ed: Could you briefly outline your study? Patty: We investigated the role of Twitter during the 2009 swine flu pandemics from two perspectives. Firstly, we demonstrated the role of the social network to detect an upcoming spike in an epidemic before the official surveillance systems—up to week in the UK and up to 2-3 weeks in the US—by investigating users who “self-diagnosed” themselves posting tweets such as “I have flu/swine flu.” Secondly, we illustrated how online resources reporting the WHO declaration of “pandemics” on 11 June 2009 were propagated through Twitter during the 24 hours after the official announcement [1,2,3]. Ed: Disease control agencies already routinely follow media sources; are public health agencies  aware of social media as another valuable source of information? Patty:  Social media are providing an invaluable real-time data signal complementing well-established epidemic intelligence (EI) systems monitoring online media, such as MedISys and GPHIN. While traditional surveillance systems will remain the pillars of public health, online media monitoring has added an important early-warning function, with social media bringing additional benefits to epidemic intelligence: virtually real-time information available in the public domain that is contributed by users themselves, thus not relying on the editorial policies of media agencies. Public health agencies (such as the European Centre for Disease Prevention and Control) are interested in social media early warning systems, but more research is required to develop robust social media monitoring solutions that are ready to be integrated with agencies’ EI services. Ed: How difficult is this data to process? E.g.: is this a full sample, processed in real-time? Patty:  No, obtaining all Twitter search query results is not possible. In our 2009 pilot study we were accessing data from Twitter using a search API interface querying the database every minute (the number of results was limited to 100 tweets). Currently, only 1% of the ‘Firehose’ (massive real-time stream of all public tweets) is made available using the streaming API. The searches have…

Communication of risk in any public health emergency is a complex task for healthcare agencies; a task made more challenging when citizens are bombarded with online information. Mexico City, 2009. Image by Eneas.

Close Menu