More Like this

1. On the Use of Proxies in Political Ad Targeting

   https://doi.org/10.1145/3686917  

   Sapiezynski, Piotr; Kaplan, Levi; Mislove, Alan; Korolova, Aleksandra (November 2024, Proceedings of the ACM on Human-Computer Interaction)

   Detailed targeting of advertisements has long been one of the core offerings of online platforms. Unfortunately, malicious advertisers have frequently abused such targeting features, with results that range from violating civil rights laws to driving division, polarization, and even social unrest. Platforms have often attempted to mitigate this behavior by removing targeting attributes deemed problematic, such as inferred political leaning, religion, or ethnicity. In this work, we examine the effectiveness of these mitigations by collecting data from political ads placed on Facebook in the lead up to the 2022 U.S. midterm elections. We show that major political advertisers circumvented these mitigations by targeting proxy attributes: seemingly innocuous targeting criteria that closely correspond to political and racial divides in American society. We introduce novel methods for directly measuring the skew of various targeting criteria to quantify their effectiveness as proxies, and then examine the scale at which those attributes are used. Our findings have crucial implications for the ongoing discussion on the regulation of political advertising and emphasize the urgency for increased transparency. 

   more » « less
2. Political Discussion is Abundant in Non-political Subreddits (and Less Toxic)

   Rajadesingan, Ashwin; Budak, Ceren; Resnick, Paul (May 2021, Proceedings of the Fifteenth International AAAI Conference on Web and Social Media)

   Budak, Ceren; Cha, Meeyoung; Quercia, Daniele; Xie, Lexing (Ed.)

   Research on online political communication has primarily focused on content in explicitly political spaces. In this work, we set out to determine the amount of political talk missed using this approach. Focusing on Reddit, we estimate that nearly half of all political talk takes place in subreddits that host political content less than 25% of the time. In other words, cumulatively, political talk in non-political spaces is abundant. We further examine the nature of political talk and show that political conversations are less toxic in non-political subreddits. Indeed, the average toxicity of political comments replying to a out-partisan in non-political subreddits is less than even the toxicity of co-partisan replies in explicitly political subreddits. 

   more » « less
3. Detecting political biases of named entities and hashtags on Twitter

   https://doi.org/10.1140/epjds/s13688-023-00386-6  

   Xiao, Zhiping; Zhu, Jeffrey; Wang, Yining; Zhou, Pei; Lam, Wen Hong; Porter, Mason A.; Sun, Yizhou (June 2023, EPJ Data Science)

   Abstract Ideological divisions in the United States have become increasingly prominent in daily communication. Accordingly, there has been much research on political polarization, including many recent efforts that take a computational perspective. By detecting political biases in a text document, one can attempt to discern and describe its polarity. Intuitively, the named entities (i.e., the nouns and the phrases that act as nouns) and hashtags in text often carry information about political views. For example, people who use the term “pro-choice” are likely to be liberal and people who use the term “pro-life” are likely to be conservative. In this paper, we seek to reveal political polarities in social-media text data and to quantify these polarities by explicitly assigning a polarity score to entities and hashtags. Although this idea is straightforward, it is difficult to perform such inference in a trustworthy quantitative way. Key challenges include the small number of known labels, the continuous spectrum of political views, and the preservation of both a polarity score and a polarity-neutral semantic meaning in an embedding vector of words. To attempt to overcome these challenges, we propose thePolarity-awareEmbeddingMulti-task learning (PEM) model. This model consists of (1) a self-supervised context-preservation task, (2) an attention-based tweet-level polarity-inference task, and (3) an adversarial learning task that promotes independence between an embedding’s polarity component and its semantic component. Our experimental results demonstrate that ourPEMmodel can successfully learn polarity-aware embeddings that perform well at tweet-level and account-level classification tasks. We examine a variety of applications—including a study of spatial and temporal distributions of polarities and a comparison between tweets from Twitter and posts from Parler—and we thereby demonstrate the effectiveness of ourPEMmodel. We also discuss important limitations of our work and encourage caution when applying thePEMmodel to real-world scenarios. 

   more » « less
4. Towards Inclusive Political Representation

   Kaur, Komal (May 2024, Proquest Dissertations)

   My research asks the following questions: What are the ramifications of male dominance in positions of power? Do they adequately address the concerns of women constituents? How do electoral quotas influence the trajectory of political careers for underrepresented groups? Which subgroups derive the greatest benefits from quota implementation? How do voters respond to the introduction of quotas, and what factors shape their reactions? I theorize and offer causal evidence on the consequences of inequitable political representation and the role of quotas in remedying disparities in political inequality. Through a combination of observational and experimental data spanning various levels ranging from legislatures to voters, my research examines quotas (or lack thereof) from multiple perspectives using a range of methodological approaches. My research demonstrates that while there is a risk of neglecting policy issues faced by underrepresented groups in legislative spaces, indicating the need for institutionalizing quotas, quotas can have asymmetric effects on citizens’ political behavior. Quotas can bridge gaps in political participation by demobilizing dominant groups while simultaneously mobilizing underrepresented groups. However, their repercussions extend beyond the realm of politics and have implications for intergroup relations. Thus, my research highlights the nuances of political representation and examines the effects of quotas on governance structures and political behavior. My dissertation comprises three distinct yet interconnected empirical chapters, all situated within the context of India. Overall, this dissertation offers lessons not only for those interested in Indian politics but also for everyone seeking to understand the role of quotas in addressing political inequality. 

   more » « less
5. Truth of Varying Shades: On Political Fact-Checking and Fake News

   Rashkin, Hannah; Choi, Eunsol; Jang, Jin Yea; Volkova, Svitlana; Choi, Yejin (November 2017, Conference on Empirical Methods in Natural Language Processing)

   We present an analytic study on the language of news media in the context of political fact-checking and fake news detection. We compare the language of real news with that of satire, hoaxes, and propaganda to find linguistic characteristics of untrustworthy text. To probe the feasibility of automatic political fact-checking, we also present a case study based on PolitiFact.com using their factuality judgments on a 6-point scale. Experiments show that while media fact-checking remains to be an open research question, stylistic cues can help determine the truthfulness of text. 

   more » « less