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Author: 8072

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Through the Looking-Glass: AI-Mediated Video Communication Reduces Trust and Confidence in Judgement

AI-based tools that mediate, enhance or generate parts of video communication may interfere with how people evaluate trustworthiness and credibility. In two preregistered online experiments (N = 2,000), we examined whether AI-mediated video retouching, background replacement and avatars affect interpersonal trust, peo…

Nelson Navajas Fernandez et al.Bauhaus University Weimar

Not just 'for you': How the Algorithmic Crystal Mediates Communication and Identity Work on TikTok’s FYP

Personalized algorithms are central to how people discover information and engage with media online. Drawing on interviews and screen-sharing sessions with TikTok users (N=27), we extend the algorithmic crystal framework, which conceptualizes personalized algorithms as reflective surfaces through which users may inter…

Zoë Natalia Cullen et al.University of Michigan

What Social Media Feeds Tell Us

Contextualizing Misinformation: A User-Centric Approach to Linguistic and Topical Patterns in News Consumption

Exposure to misinformation poses significant challenges to democratic processes and public health, particularly during critical events like elections. This study adopts a user-centric approach to analyze the linguistic features of misinformation actually consumed by individuals during web browsing. Using data from a n…

Ross Dahlke et al.Stanford University

Misinformation, News, and Fact-Checking

Embedding Democratic Values into Social Media AIs via Societal Objective Functions

Mounting evidence indicates that the artificial intelligence (AI) systems that rank our social media feeds bear nontrivial responsibility for amplifying partisan animosity: negative thoughts, feelings, and behaviors toward political out-groups. Can we design these AIs to consider democratic values such as mitigating p…

Chenyan Jia et al.Northeastern University

Session 1d: Understanding and Shaping Online Behavior

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Hate Raids on Twitch: Echoes of the Past, New Modalities, and Implications for Platform Governance

In the summer of 2021, users on the livestreaming platform Twitch experienced a wave of "hate raids," a form of attack that overwhelms a target's chatroom with hateful messages, often with the aid of bots and automation. Utilizing a mixed-methods approach, we combine interviews with streamers and third-party bot devel…

Catherine Han et al.Stanford University

Moderation II

Working with AI to persuade: Examining a large language model’s ability to generate pro-vaccination messages

Artificial Intelligence (AI) is a transformative force in communication and messaging strategy, with potential to disrupt traditional approaches. Large language models (LLMs), a form of AI, are capable of generating high-quality, humanlike text. We investigate the persuasive quality of AI-generated messages to underst…

Elise Karinshak et al.University of Georgia

Health and AI

End-User Audits: A System Empowering Communities to Lead Large-Scale Investigations of Harmful Algorithmic Behavior

Because algorithm audits are conducted by technical experts, audits are necessarily limited to the hypotheses that experts think to test. End users hold the promise to expand this purview, as they inhabit spaces and witness algorithmic impacts that auditors do not. In pursuit of this goal, we propose end-user audits—s…

Michelle S. Lam et al.Stanford University

Algorithmic Decision-making

The Algorithmic Crystal: Conceptualizing the Self through Algorithmic Personalization on TikTok

This research examines how TikTok users conceptualize and engage with personalized algorithms on the TikTok platform. Using qualitative methods, we analyzed 24 interviews with TikTok users to explore how algorithmic personalization processes inform people’s understanding of their identities as well as shape their orie…

Angela Y Lee et al.Stanford University

Users' Understanding of Algorithms; Users' Understanding of Algorithms

Jury Learning: Integrating Dissenting Voices into Machine Learning Models

Whose labels should a machine learning (ML) algorithm learn to emulate? For ML tasks ranging from online comment toxicity to misinformation detection to medical diagnosis, different groups in society may have irreconcilable disagreements about ground truth labels. Supervised ML today resolves these label disagreements…

Mitchell L. Gordon et al.Stanford University

Emotional Amplification During Live-Streaming: Evidence from Comments During and After News Events

Live streaming services allow people to concurrently consume and comment on media events with other people in real time. Durkheim’s theory of “collective effervescence” suggests that face-to-face encounters in ritual events conjure emotional arousal, so people often feel happier and more excited while watching events…

Mufan Luo et al.Stanford University

Videos, Live Streaming, and VR

Search Media and Elections: A Longitudinal Investigation of Political Search Results

Concern about algorithmically-curated content and its impact on democracy is reaching a fever pitch worldwide. But relative to the role of social media in electoral processes, the role of search results has received less public attention. We develop a theoretical conceptualization of search results as a form of media—…

Danaë Metaxa et al.Stanford University

Political Participation and Polarization

Paper Title	Authors	Research Topics
Through the Looking-Glass: AI-Mediated Video Communication Reduces Trust and Confidence in Judgement AI-based tools that mediate, enhance or generate parts of video communication may interfere with how people evaluate trustworthiness and credibility. In two preregistered online experiments (N = 2,000), we examined whether AI-mediated video retouching, background replacement and avatars affect interpersonal trust, peo…	NF Nelson Navajas Fernandez et al.Bauhaus University Weimar
emoji_events Not just 'for you': How the Algorithmic Crystal Mediates Communication and Identity Work on TikTok’s FYP Personalized algorithms are central to how people discover information and engage with media online. Drawing on interviews and screen-sharing sessions with TikTok users (N=27), we extend the algorithmic crystal framework, which conceptualizes personalized algorithms as reflective surfaces through which users may inter…	ZC Zoë Natalia Cullen et al.University of Michigan	What Social Media Feeds Tell Us
Contextualizing Misinformation: A User-Centric Approach to Linguistic and Topical Patterns in News Consumption Exposure to misinformation poses significant challenges to democratic processes and public health, particularly during critical events like elections. This study adopts a user-centric approach to analyze the linguistic features of misinformation actually consumed by individuals during web browsing. Using data from a n…	RD Ross Dahlke et al.Stanford University	Misinformation, News, and Fact-Checking
emoji_events Embedding Democratic Values into Social Media AIs via Societal Objective Functions Mounting evidence indicates that the artificial intelligence (AI) systems that rank our social media feeds bear nontrivial responsibility for amplifying partisan animosity: negative thoughts, feelings, and behaviors toward political out-groups. Can we design these AIs to consider democratic values such as mitigating p…	CJ Chenyan Jia et al.Northeastern University	Session 1d: Understanding and Shaping Online Behavior
AdRecommended Learn AI Coding at CodeNow Structured lessons, hands-on projects, and continuous updates for people bringing AI into real development work. Explore Now
emoji_events Hate Raids on Twitch: Echoes of the Past, New Modalities, and Implications for Platform Governance In the summer of 2021, users on the livestreaming platform Twitch experienced a wave of "hate raids," a form of attack that overwhelms a target's chatroom with hateful messages, often with the aid of bots and automation. Utilizing a mixed-methods approach, we combine interviews with streamers and third-party bot devel…	CH Catherine Han et al.Stanford University	Moderation II
Working with AI to persuade: Examining a large language model’s ability to generate pro-vaccination messages Artificial Intelligence (AI) is a transformative force in communication and messaging strategy, with potential to disrupt traditional approaches. Large language models (LLMs), a form of AI, are capable of generating high-quality, humanlike text. We investigate the persuasive quality of AI-generated messages to underst…	EK Elise Karinshak et al.University of Georgia	Health and AI
End-User Audits: A System Empowering Communities to Lead Large-Scale Investigations of Harmful Algorithmic Behavior Because algorithm audits are conducted by technical experts, audits are necessarily limited to the hypotheses that experts think to test. End users hold the promise to expand this purview, as they inhabit spaces and witness algorithmic impacts that auditors do not. In pursuit of this goal, we propose end-user audits—s…	ML Michelle S. Lam et al.Stanford University	Algorithmic Decision-making
The Algorithmic Crystal: Conceptualizing the Self through Algorithmic Personalization on TikTok This research examines how TikTok users conceptualize and engage with personalized algorithms on the TikTok platform. Using qualitative methods, we analyzed 24 interviews with TikTok users to explore how algorithmic personalization processes inform people’s understanding of their identities as well as shape their orie…	AL Angela Y Lee et al.Stanford University	Users' Understanding of Algorithms; Users' Understanding of Algorithms
emoji_events Jury Learning: Integrating Dissenting Voices into Machine Learning Models Whose labels should a machine learning (ML) algorithm learn to emulate? For ML tasks ranging from online comment toxicity to misinformation detection to medical diagnosis, different groups in society may have irreconcilable disagreements about ground truth labels. Supervised ML today resolves these label disagreements…	MG Mitchell L. Gordon et al.Stanford University
Emotional Amplification During Live-Streaming: Evidence from Comments During and After News Events Live streaming services allow people to concurrently consume and comment on media events with other people in real time. Durkheim’s theory of “collective effervescence” suggests that face-to-face encounters in ritual events conjure emotional arousal, so people often feel happier and more excited while watching events…	ML Mufan Luo et al.Stanford University	Videos, Live Streaming, and VR
Search Media and Elections: A Longitudinal Investigation of Political Search Results Concern about algorithmically-curated content and its impact on democracy is reaching a fever pitch worldwide. But relative to the role of social media in electoral processes, the role of search results has received less public attention. We develop a theoretical conceptualization of search results as a form of media—…	DM Danaë Metaxa et al.Stanford University	Political Participation and Polarization