331 citations · 896 across the 27 of their papers we have counts for
29 papers
Introducing AI to an Online Petition Platform Changed Outputs but not Outcomes
Isabel Corpus, Eric Gilbert, Allison Koenecke +1
The rapid integration of AI writing tools into online platforms raises critical questions about their impact on content production and outcomes. We leverage a unique natural experi…
Penalizing Transparency? How AI Disclosure and Author Demographics Shape Human and AI Judgments About Writing
Inyoung Cheong, Alicia Guo, Mina Lee +7
As AI integrates in various types of human writing, calls for transparency around AI assistance are growing. However, if transparency operates on uneven ground and certain identity…
Examining Human-AI Collaboration for Co-Writing Constructive Comments Online
Farhana Shahid, Maximilian Dittgen, Mor Naaman +1
This paper examines if large language models (LLMs) can help people write constructive comments on divisive social issues due to the difficulty of expressing constructive disagreem…
Examining the Prevalence and Dynamics of AI-Generated Media in Art Subreddits
Hana Matatov, Marianne Aubin Le Quéré, Ofra Amir +1
Broadly accessible generative AI models like Dall-E have made it possible for anyone to create compelling visual art. In online communities, the introduction of AI-generated conten…
Generative AI and Perceptual Harms: Who's Suspected of using LLMs?
Kowe Kadoma, Danaé Metaxa, Mor Naaman
Large language models (LLMs) are increasingly integrated into a variety of writing tasks. While these tools can help people by generating ideas or producing higher quality work, li…
AI Suggestions Homogenize Writing Toward Western Styles and Diminish Cultural Nuances
Dhruv Agarwal, Mor Naaman, Aditya Vashistha
Large language models (LLMs) are being increasingly integrated into everyday products and services, such as coding tools and writing assistants. As these embedded AI applications a…
"There Has To Be a Lot That We're Missing": Moderating AI-Generated Content on Reddit
Travis Lloyd, Joseph Reagle, Mor Naaman
Generative AI is altering how we work, learn, communicate, and participate in online communities. How might online communities be changed by generative AI? To start addressing this…
Trustworthiness Evaluations of Search Results: The Impact of Rank and Misinformation
Sterling Williams-Ceci, Michael Macy, Mor Naaman
Users rely on search engines for information in critical contexts, such as public health emergencies. Understanding how users evaluate the trustworthiness of search results is ther…
The Role of Inclusion, Control, and Ownership in Workplace AI-Mediated Communication
Kowe Kadoma, Marianne Aubin Le Quere, Jenny Fu +3
Given large language models' (LLMs) increasing integration into workplace software, it is important to examine how biases in the models may impact workers. For example, stylistic b…
Co-Writing with Opinionated Language Models Affects Users' Views
Maurice Jakesch, Advait Bhat, Daniel Buschek +2
If large language models like GPT-3 preferably produce a particular point of view, they may influence people's opinions on an unknown scale. This study investigates whether a langu…
Stop the [Image] Steal: The Role and Dynamics of Visual Content in the 2020 U.S. Election Misinformation Campaign
Hana Matatov, Mor Naaman, Ofra Amir
Images are powerful. Visual information can attract attention, improve persuasion, trigger stronger emotions, and is easy to share and spread. We examine the characteristics of the…
Estimating Exposure to Information on Social Networks
Buddhika Nettasinghe, Kowe Kadoma, Mor Naaman +1
This paper considers the problem of estimating exposure to information in a social network. Given a piece of information (e.g., a URL of a news article on Facebook, a hashtag on Tw…
Human heuristics for AI-generated language are flawed
Maurice Jakesch, Jeffrey Hancock, Mor Naaman
Human communication is increasingly intermixed with language generated by AI. Across chat, email, and social media, AI systems suggest words, complete sentences, or produce entire…
Dataset and Case Studies for Visual Near-Duplicates Detection in the Context of Social Media
Hana Matatov, Mor Naaman, Ofra Amir
The massive spread of visual content through the web and social media poses both challenges and opportunities. Tracking visually-similar content is an important task for studying a…
Characterizing Alternative Monetization Strategies on YouTube
Yiqing Hua, Manoel Horta Ribeiro, Robert West +2
One of the key emerging roles of the YouTube platform is providing creators the ability to generate revenue from their content and interactions. Alongside tools provided directly b…
Characterizing Reddit Participation of Users Who Engage in the QAnon Conspiracy Theories
Kristen Engel, Yiqing Hua, Taixiang Zeng +1
Widespread conspiracy theories may significantly impact our society. This paper focuses on the QAnon conspiracy theory, a consequential conspiracy theory that started on and dissem…
Increasing Adversarial Uncertainty to Scale Private Similarity Testing
Yiqing Hua, Armin Namavari, Kaishuo Cheng +2
Social media and other platforms rely on automated detection of abusive content to help combat disinformation, harassment, and abuse. One common approach is to check user content f…
Trend Alert: How a Cross-Platform Organization Manipulated Twitter Trends in the Indian General Election
Maurice Jakesch, Kiran Garimella, Dean Eckles +1
Political organizations worldwide keep innovating their use of social media technologies. In the 2019 Indian general election, organizers used a network of WhatsApp groups to manip…
Artificial intelligence in communication impacts language and social relationships
Jess Hohenstein, Dominic DiFranzo, Rene F. Kizilcec +6
Artificial intelligence (AI) is now widely used to facilitate social interaction, but its impact on social relationships and communication is not well understood. We study the soci…
VoterFraud2020: a Multi-modal Dataset of Election Fraud Claims on Twitter
Anton Abilov, Yiqing Hua, Hana Matatov +2
The wide spread of unfounded election fraud claims surrounding the U.S. 2020 election had resulted in undermining of trust in the election, culminating in violence inside the U.S.…
Characterizing Twitter Users Who Engage in Adversarial Interactions against Political Candidates
Yiqing Hua, Mor Naaman, Thomas Ristenpart
Social media provides a critical communication platform for political figures, but also makes them easy targets for harassment. In this paper, we characterize users who adversarial…
Towards Measuring Adversarial Twitter Interactions against Candidates in the US Midterm Elections
Yiqing Hua, Thomas Ristenpart, Mor Naaman
Adversarial interactions against politicians on social media such as Twitter have significant impact on society. In particular they disrupt substantive political discussions online…
When Do People Trust Their Social Groups?
Xiao Ma, Justin Cheng, Shankar Iyer +1
Trust facilitates cooperation and supports positive outcomes in social groups, including member satisfaction, information sharing, and task performance. Extensive prior research ha…
Understanding Image Quality and Trust in Peer-to-Peer Marketplaces
Xiao Ma, Lina Mezghani, Kimberly Wilber +4
As any savvy online shopper knows, second-hand peer-to-peer marketplaces are filled with images of mixed quality. How does image quality impact marketplace outcomes, and can qualit…