Originating from a unique partnership between data scientists (datavaluepeople) and peacebuilders (Build Up), this commentary explores an innovative methodology to overcome key challenges in social media analysis by developing customized text classifiers through a participatory design approach, engaging both peace practitioners and data scientists. It advocates for researchers to focus on developing frameworks that prioritize being usable and participatory in field settings, rather than perfect in simulation. Focusing on a case study investigating the polarization within online Christian communities in the United States, we outline a testing process with a dataset consisting of 8954 tweets and 10,034 Facebook posts to experiment with active learning methodologies aimed at enhancing the efficiency and accuracy of text classification. This commentary demonstrates that the inclusion of domain expertise from peace practitioners significantly refines the design and performance of text classifiers, enabling a deeper comprehension of digital conflicts. This collaborative framework seeks to transition from a data-rich, analysis-poor scenario to one where data-driven insights robustly inform peacebuilding interventions.

This article examines the information sharing behavior of U.S. politicians and the mass public by mapping the ideological sharing space of political news on social media. As data, we use the near-universal currency of online information exchange: web links. We introduce a methodological approach and software to unify the measurement of ideology across social media platforms by using sharing data to jointly estimate the ideology of news media organizations, politicians, and the mass public. Empirically, we show that (1) politicians who share ideologically polarized content share, by far, the most political news and commentary and (2) that the less competitive elections are, the more likely politicians are to share polarized information. These results demonstrate that news and commentary shared by politicians come from a highly unrepresentative set of ideologically extreme legislators and that decreases in election pressures (e.g., by gerrymandering) may encourage polarized sharing behavior.

We introduce a dynamic dataset of all communications by state election officials (EOs) on social media during the 2022 election cycle and develop metrics to assess the effectiveness of trust-building strategies on voter confidence. We employ quantitative manual content analysis of 10,000 organic posts from 118 state EOs’ accounts on Facebook, Instagram, and Twitter between September 10 and November 30, 2022, and code for the presence of variables that measure EOs’ efforts to combat misinformation and build trusted networks of communications. The measures we present here address two questions: (1) How much coordination was there among states in terms of incorporating the #TrustedInfo2022 campaign, promoted by the National Association of Secretaries of State, in their social media communications, and (2) How much of states’ social media communications explicitly signaled that EOs are trusted sources of information? We demonstrate the applicability of our data on research that evaluates the impact of trust-building campaigns on voter confidence in elections, which is grounded on theories of deliberative democracy and democratic listening.

We analyze a cache of tweets from partisan users concerning the confirmation hearings of Justices Brett Kavanaugh, Amy Coney Barrett, and Ketanji Brown Jackson. Using these original data, we investigate how Twitter users with partisan leanings interact with judicial nominations and confirmations. We find that these users tend to exhibit behavior consistent with offline partisan dynamics. Our analysis reveals that Democrats and Republicans express distinct emotional responses based on the alignment of nominees with their respective parties. Additionally, our study highlights the active participation of partisans in promoting politically charged topics throughout the confirmation process, starting from the vacancy stage.

Ideal points of MPs in the UK House of Commons (HoC) are characteristically difficult to ascertain due to tight party discipline and strategic voting by opposition members. This research note generates left/right ideal point estimates for 591 British MPs sitting in the HoC as of 22/08/2022, ascertained through their social media followership. Specifically, estimates are derived by conducting correspondence analysis (CA) on MP Twitter (X) follower networks, which are subsequently validated against an expert survey, confirming that these estimates have a high degree of between-party (R2 = 0.93) and within-party (Con: r = 0.84; Lab: r = 0.81) accuracy. The informative value of these estimates is then demonstrated by predicting candidate endorsement in the September 2022 Conservative leadership contest, confirming that an MP's ideal point was a statistically significant predictor of candidate endorsement, with Liz Truss drawing support primarily from the further right of the party.

Judges are not the first political officials that come to mind when one considers the role of social media in modern politics. Following in the wake of some prominent judicial personalities adopting Twitter, however, a growing number of state high court judges have adopted and established more public personas on the platform. Judges use Twitter in substantively different ways than traditional elected officials (Curry and Fix 2019); however, little is understood about how the use of such social media platforms affects broader judicial networks. Recognizing that judges, like typical social media users, may aspire to expand their networks to build and appeal to broader audiences, we contend that active participation in judicial Twitterverse could yield personal and professional advantages. Here, we address a currently unexplored question: To what extent have judges formed a distinctive “judicial network,” on Twitter, and what discernible patterns present in these networks? Leveraging the unique structure of social media, we collect comprehensive network data on judging using Twitter and analyze what institutional and social factors impact greater power within the judicial network. We find that early adoption, electoral concerns, and connective links between judges all impact the strength of the judicial network, highlighting the complex motivations driving judicial Twitter engagement, and the significance of network building in judges’ social media strategies and its potential impact on career advancement.

Within Holocaust studies, there has been an increasingly uncritical acceptance that by engaging with social media, Holocaust memory has shifted from the ‘era of the witness’ to the ‘era of the user’ (Hogervorst 2020). This paper starts by problematising this proposition. This claim to a paradigmatic shift implies that (1) the user somehow replaces the witness as an authority of memory, which neglects the wealth of digital recordings of witnesses now circulating in digital spaces and (2) agency online is solely human-centric, a position that ignores the complex negotiations between corporations, individuals, and computational logics that shape our digital experiences. This article proposes instead that we take a posthumanist approach to understanding Holocaust memory on, and with, social media. Adapting Barad's (2007) work on entanglement to memory studies, we analyse two case studies on TikTok: the #WeRemember campaign and the docuseries How To: Never Forget to demonstrate: (1) the usefulness of reading Holocaust memory on social media through the lens of entanglement which offers a methodology that accounts for the complex network of human and non-human actants involved in the production of this phenomenon which are simultaneously being shaped by it. (2) That professional memory institutions and organisations are increasingly acknowledging the use of social media for the sake of Holocaust memory. Nevertheless, we observe that in practice the significance of technical actancy is still undervalued in this context.

Control over the legislative messaging agenda has important political, electoral and policy consequences. Existing models of congressional agenda-setting suggest that national polarization drives the agenda. At the same time, models of home style and formal models of leadership hypothesize that legislators shift their messaging as they balance coordination and information problems. We say the coordination problem dominates when conditions incentivize legislators to agree on the same message rather than fail to reach consensus. Conversely, the information problem is said to dominate in circumstances where legislators prefer to say nothing at all rather than reach consensus on the wrong political message. Formal theories predict that when coordination problems are pressing, legislative members follow the policy positions of party leaders. When their party’s information problem is acute, party members instead rely on the wisdom of the caucus to set the party’s agenda. To test these theories, we analyze the Twitter accounts of U.S. House members with a Joint Sentiment Topic model, generating a new understanding of House leadership power. Our analyses reveal complex leader-follower relationships. Party leaders possess the power to substantially affect the propensity of rank-and-file members to discuss topics, especially when the coordination problem dominates; these effects are pronounced even when coordination problems are pressing. That said, when the underlying politics are unclear, rank-and-file members exert influence on the discussion of a topic because the information problem is more acute. At the same time and for these uncertain topics, leadership influence decreases, consistent with theory. We show these results are robust to the underlying dynamics of contemporary political discussion and context, including leading explanations for party leadership power, such as national polarization.

By examining social media interactions, the analysis that is presented in this article reveals how hashtags are adeptly used to reframe the lithium mining issue, embedding it within wider narratives. The article investigates narratives surrounding lithium mining protests in Serbia, using digital ethnography and narrative analysis to study the discourse of ecology activists on the social platform X (formerly known as Twitter). It illuminates the fluid, rhizomatic, and puzzle-like nature of hashtags that helps to achieve online visibility, mobilize audiences for street protests, and appear as narrative building blocks. Hashtags operate as algorithmic signifiers that create additional layers of meaning and fine-tune narratives toward either the left or right side of the political spectrum. This article focuses on how activists use hashtags not just as tools for categorizing content but also as essential components in shaping their narratives. This approach reveals the dynamic engagement of a broad political spectrum in the lithium mining debate, forging connections between different actors. The analysis demonstrates how interconnected hashtags modulate the narratives so that they can transgress from the right to the left side of the political spectrum, indicating that lithium mining is a global rather than a local problem.

Election violence is increasingly taking place online. However, we still do not know much about how such attacks affect the representation of politically marginalized groups such as women. This article develops and applies strategies for analyzing (gendered) exposure to and impacts of online attacks against political candidates. It focuses on the 2019 parliamentary election campaign in Tunisia and combines manual analysis of Tunisian candidates’ public Facebook pages with candidate interviews. We find no gendered patterns in exposure to online election violence in the Facebook data and a low general exposure to attacks. The interview data nevertheless suggests gendered perceptions and impacts of attacks, as well as a perception among the candidates that online election violence is widespread and problematic. These discrepancies highlight that we need a combination of methods and materials to capture the multifaceted nature of online election violence, and in particular those that directly link candidate exposure to impact.