Chenyan Jia

schoolNortheastern Universitybar_chart#2562 Global Rank

Total Papers

HCI Rank

#2562

Research Areas

Years Active

Recent Publications

My Body, Their Business: User Perspectives on Commercial Data Practices in FemTech Apps

FemTech, including apps for fertility, menstruation, and menopause, increasingly shapes how users manage intimate aspects of their health. Yet these apps are often built on opaque commercial models, raising ethical concerns about consent, privacy, and misuse of sensitive health data. While prior work has documented th…

CHI '261st AuthorExplainable AI (XAI) +2

Beyond Accuracy: Experts See AI Fact-Checks as Accurate but Less Useful

As misinformation proliferates online, large language models (LLMs) have been proposed as a promising tool to accelerate fact-checking workflows. While LLMs demonstrate strong performance in tasks such as text annotation, their capabilities in generating fact-checking reports remain uncertain. To investigate how media…

CSCW '241st AuthorBest PaperSession 1d: Understanding and Shaping Online Behavior

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…

CSCW '221st AuthorPolitics, Polarization and Partisanship; Politics, Polarization and Partisanship

Understanding Effects of Algorithmic vs. Community Label on Perceived Accuracy of Hyper-partisan Misinformation

Hyper-partisan misinformation has become a major public concern. To examine what type of misinformation label can mitigate hyper-partisan misinformation sharing on social media, we conducted a 4 (label type: algorithm, community, third-party fact-checker, and no label) X 2 (post ideology: liberal and conservative) bet…

CSCW '212nd AuthorCivic Engagement, Politics, and Polarization

A Transformer-based Framework for Neutralizing and Reversing the Political Polarity of News Articles

People often prefer to consume news with similar political predispositions and access like-minded news articles, which aggravates polarized clusters known as "echo chamber". To mitigate this phenomenon, we propose a computer-aided solution to help combat extreme political polarization. Specifically, we present a frame…

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