Using Social Media Data to Analyse Issue Engagement During the 2017 German Federal Election

A fundamental tenet of democracy is that political parties present policy alternatives, such that the public can participate in the decision-making process. Parties, however, strategically control public discussion by emphasising topics that they believe will highlight their strengths in voters’ minds. Political strategy has been studied for decades, mostly by manually annotating and analysing party statements, press coverage, or TV ads. Here we build on recent work in the areas of computational social science and eDemocracy, which studied these concepts computationally with social media. We operationalize issue engagement and related political science theories to measure and quantify politicians’ communication behavior using more than 366k Tweets posted by over 1,000 prominent German politicians in the 2017 election year. To this end, we first identify issues in posted Tweets by utilising a hashtag-based approach well known in the literature. This method allows several prominent issues featuring in the political debate on Twitter that year to be identified. We show that different political parties engage to a larger or lesser extent with these issues. The findings reveal differing social media strategies by parties located at different sides of the political left-right scale, in terms of which issues they engage with, how confrontational they are and how their strategies evolve in the lead-up to the election. Whereas previous work has analysed the general public’s use of Twitter or politicians’ communication in terms of cross-party polarisation, this is the first study of political science theories, relating to issue engagement, using politicians’ social media data.

Politics is making us sick: The negative impact of political engagement on public health during the Trump administration

Objectives To quantify the effect of politics on the physical, psychological, and social health of American adults during the four-year span of the Trump administration. Methods A previously validated politics and health scale was used to compare health markers in nationally representative surveys administered to separate samples in March 2017 (N = 800) and October 2020 (N = 700). Participants in the 2020 survey were re-sampled approximately two weeks after the 2020 election and health markers were compared to their pre-election baselines. Results Large numbers of Americans reported politics takes a significant toll on a range of health markers—everything from stress, loss of sleep, or suicidal thoughts to an inability to stop thinking about politics and making intemperate social media posts. The proportion of Americans reporting these effects stayed stable or slightly increased between the spring of 2017 and the fall of 2020 prior to the presidential election. Deterioration in measures of physical health became detectably worse in the wake of the 2020 election. Those who were young, politically interested, politically engaged, or on the political left were more likely to report negative effects. Conclusions Politics is a pervasive and largely unavoidable source of chronic stress that exacted significant health costs for large numbers of American adults between 2017 and 2020. The 2020 election did little to alleviate those effects and quite likely exacerbated them.

Algorithmic amplification of politics on Twitter

Content on Twitter’s home timeline is selected and ordered by personalization algorithms. By consistently ranking certain content higher, these algorithms may amplify some messages while reducing the visibility of others. There’s been intense public and scholarly debate about the possibility that some political groups benefit more from algorithmic amplification than others. We provide quantitative evidence from a long-running, massive-scale randomized experiment on the Twitter platform that committed a randomized control group including nearly 2 million daily active accounts to a reverse-chronological content feed free of algorithmic personalization. We present two sets of findings. First, we studied tweets by elected legislators from major political parties in seven countries. Our results reveal a remarkably consistent trend: In six out of seven countries studied, the mainstream political right enjoys higher algorithmic amplification than the mainstream political left. Consistent with this overall trend, our second set of findings studying the US media landscape revealed that algorithmic amplification favors right-leaning news sources. We further looked at whether algorithms amplify far-left and far-right political groups more than moderate ones; contrary to prevailing public belief, we did not find evidence to support this hypothesis. We hope our findings will contribute to an evidence-based debate on the role personalization algorithms play in shaping political content consumption.

Prejudice, Bigotry, and Support for Compensatory Interventions to Address Black-White Inequalities: Evidence from the General Social Survey, 2006-2020

The General Social Survey (GSS) shows that many self-identified white adults continue to hold racial attitudes that can be regarded, collectively, as a persistent social problem. Similar to findings from the analysis of electoral surveys, the GSS also shows that these racial attitudes have more strongly predicted political behavior since 2012. However, and in contrast to group-identity interpretations of these patterns, the increase in predictive power since 2012 is attributable to a positive development: above and beyond the effects of cohort replacement, support for compensatory interventions to address black-white inequalities has increased substantially, while prejudice and bigotry have decreased slightly. Because these changes have been larger on the political left than on the political right, the attitudes have gained in overall predictive power.

Group Size and Protest Mobilization across Movements and Countermovements

Many social movements face fierce resistance in the form of a countermovement. Therefore, when deciding to become politically active, a movement supporter has to consider both her own movement’s activity and that of the opponent. This paper studies the decision of a movement supporter to attend a protest when faced with a counterprotest. We implement two field experiments among supporters of a right- and left-leaning movement ahead of two protest–counterprotest interactions in Germany. Supporters were exposed to low or high official estimates about their own and the opposing group’s turnout. We find that the size of the opposing group has no effect on supporters’ protest intentions. However, as the own protest gets larger, supporters of the right-leaning movement become less while supporters of the left-leaning movement become more willing to protest. We argue that the difference is best explained by stronger social motives on the political left.

Losses, hopes, and expectations for sustainable futures after COVID

The COVID-19 pandemic has caused immense distress but also created opportunity for radical change. Two main avenues for recovery from the pandemic have been discussed: A “back to normal” that foregrounds economic recovery, and a sustainable and progressive “build back better” approach that seeks to address global problems such as inequality and climate change. The article reports two experiments conducted on representative British and American samples (N = 600 and N = 800, respectively, for the two experiments) that show that people in both countries overall prefer a progressive future to a return to normal, although that preference is stronger on the political left and center-left with ambivalence prevailing on the right. However, irrespective of political leanings, people consider a return to normal more likely than a progressive future. People also mistakenly believe that others want the progressive scenarios less, and the return to normal more, than they actually do. The divergence between what people want and what they think others want represents an instance of pluralistic ignorance, which arises when public discourse is not reflecting people’s actual opinions. Publicizing public opinion is thus crucial to facilitate a future with broad support. In additional open-ended items, participants cited working from home, reduced commuting, and a collective sense of civility as worth retaining post pandemic.

Authenticity, Respectability, and the Desire for Marriage

With marriage equality victorious, chapter 15 delves into the question of why so many on the political Left, in the gay rights movement and in academia, failed to appreciate how practical and radical marriage equality would be. Many social movement scholars and gay rights activists had claimed that same-sex couples did not really want to marry. Yet once same-sex couples had the option to marry, they voted with their feet and their hearts to get married by the hundreds of thousands. California same-sex couples chose marriage over domestic partnership by a 20-to-1 margin once they had the choice. Some critics from the Left had argued that marriage equality was not radical enough. The success of marriage equality suggests that there may be nothing as radical as a social change that is also practical and rooted in tradition.

Hidden Continuities?: The Avatars of “Judicial Lustration” in Post-Communist Romania

This Article grapples with the instrumentalization of the past in Romania, in the specific context of “judicial lustration” measures. It argues that decommunization and lustration policies, which could not be pursued in the immediate aftermath of the collapse of state socialism in 1989, were weaponized much later and used in order to advance other purposes. In 2006, an expedited judicial vetting procedure, in the context of the EU-driven fight against corruption, was repurposed by the center-right as a lustration instrument. In the same year, the dismantling of an intelligence service created after 1991 in the Justice Ministry (SIPA) to monitor ‘vulnerabilities’ in the justice system has set in motion a long series of failed attempts to bring closure to the question regarding the service’s archives, fomenting continuities of suspicion until today. More recently, in 2018, a form of ‘mock-judicial lustration’ has been used by the political left to deflect or at least delegitimize repressive anti-corruption policies. The new “lustration procedure” implicitly equated the recent cooperation between prosecutors and intelligence officers, in the context of the fight against corruption, with past practices of collusion between the members of the judiciary and the communist Securitate. These three episodes of ‘dealing with the past’ are reviewed in order to showcase path-dependencies. Such path-dependencies are not linked only with carryovers from or throwbacks to the communist past. Rather, pre- and post-communist deficiencies of modernization, combined more recently with gaps in post-accession monitoring by the EU Commission, create continuities of peripheral instrumentalism. Various narratives, such as decommunization, the fight against graft, judicial reform and the rule of law are used to legitimize short-term consequentialism, evincing a resilient, structural resistance to legislative and legal normativity.

Data-driven group comparisons of eye fixations to dynamic stimuli

Recent advances in software and hardware have allowed eye tracking to move away from static images to more ecologically relevant video streams. The analysis of eye tracking data for such dynamic stimuli, however, is not without challenges. The frame-by-frame coding of regions of interest (ROIs) is labour-intensive and computer vision techniques to automatically code such ROIs are not yet mainstream, restricting the use of such stimuli. Combined with the more general problem of defining relevant ROIs for video frames, methods are needed that facilitate data analysis. Here, we present a first evaluation of an easy-to-implement data-driven method with the potential to address these issues. To test the new method, we examined the differences in eye movements of self-reported politically left- or right-wing leaning participants to video clips of left- and right-wing politicians. The results show that our method can accurately predict group membership on the basis of eye movement patterns, isolate video clips that best distinguish people on the political left–right spectrum, and reveal the section of each video clip with the largest group differences. Our methodology thereby aids the understanding of group differences in gaze behaviour, and the identification of critical stimuli for follow-up studies or for use in saccade diagnosis.

DISCOURSES OF VICTIMHOOD AND IDENTITY POLITICS ON SOCIAL MEDIA: UNDERSTANDING AFFECTIVE POLARIZATION DURING THE US ELECTION

This cross-platform digital ethnography examines the nuances of how emotions are expressed and who they are directed towards within social media in order to better understand the phenomenon of affective polarization and the increased emotionality online. As part of a larger three-year SSHRC-funded comparative study between the US and Canadian elections, the focused dataset for this project draws on grounded theory (Charmaz, 2006) and our exploration of 1800 social media posts from the political left and right across social media platforms: Twitter, Facebook, and Gab. By examining how social media users discursively construct representations of self and other through expressions of us/them dichotomies, this project seeks to better understand polarized political identities and how social media users emphasize that their morals and values are similar or distinct from others. How do people on the left and the right feel victimized by the other? What are the moral and emotional injuries as well as the identity politics upon which they base their claims to victimhood and simultaneously place blame on the other? How do social media users rhetorically express their indignation through us/them dichotomizing, to justify their negative affect as well as enactments of revenge as moral duty? In addition to presenting key findings, this talk highlights our innovative approach to affective discourse analysis developed over the past two years of iterative, grounded theoretical qualitative study.