Publications
Peer Reviewed Publications (selected):
Journal Articles and Conference Proceedings (*Indicates equal contribution)
2025
[32] Jia, C., Gondimalla, A., Zhang, A., Mullings, D. J., Boltz, A., & Lee, M. K. (2026). Beyond Accuracy: Experts See AI Fact-Checks as Accurate but Less Useful. In Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (CHI 2026).
[PDF] | [BibTeX] | [Google Scholar]
[31] Alsebayel, G., Lainfiesta, X., Fatima, A., Troiano, G., Jia, C., Harteveld, C. (2026). My Body, Their Business: User Perspectives on Commercial Practices in FemTech mHealth Apps. In Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (CHI 2026).
[PDF] | [BibTeX] | [Google Scholar]
[30] *Piccardi, T., *Saveski, M., *Jia, C., Hancock, J. T., Tsai, J., & Bernstein, M. S. (2026). Reranking Social Media Feeds: A Practical Guide for Field Experiments. ACM Transactions on Social Computing (TSC).
[PDF] | [BibTeX] | [Google Scholar]
2025
[29] *Piccardi, T., *Saveski, M., *Jia, C., Hancock, J. T., Tsai, J., & Bernstein, M. S. (2025). Reranking partisan animosity in algorithmic social media feeds alters affective polarization. Science.
[PDF] | [BibTeX] | [Google Scholar]
2024
[28] *Jia, C., *Lee, A. Y., Moore, R. C., Decatur, C. H., Liu, S. X., Hancock, J. T. (2024). Collaboration, Crowdsourcing, and Misinformation. PNAS (The Proceedings of the National Academy of Sciences) Nexus.
[PDF] | [BibTeX] | [Google Scholar]
[27] *Jia, C., *Lam, M. S., Mai, M. C., Hancock, J. T. Bernstein, M. S. (2024). Embedding Democratic Values into Social Media AIs via Societal Objective Functions. Proceedings of the ACM: Human-Computer Interaction. Issue CSCW (CSCW 2024). 8, CSCW1, Article 163.
[PDF] | [BibTeX] | [Google Scholar]
[26] *Jia, C., & *Lee, T. (2024). Journalistic professionalism matters: Understanding how Americans perceive fact-checking labels. Harvard Kennedy School (HKS) Misinformation Review.
[PDF] | [BibTeX] | [Google Scholar]
[25] Liu, R., Yang, R., Jia, C., Zhang, G., Yang, D., & Vosoughi, S. (2024). Training Socially Aligned Language Models in Simulated Human Society. Proceedings of the International Conference on Learning Representations (ICLR 2024).
[PDF] | [BibTeX] | [Google Scholar]
[24] Christin, A., Bernstein, M., Hancock, J., Jia, C., Mado, M., Tsai, J., & Xu, C. (2024). Social media platforms as evaluation machines. Social Media and Society.
[PDF] | [BibTeX] | [Google Scholar]
[23] Jia, C., Riedl, J. M., Woolley, S. (2024). Promises and perils of automated journalism: algorithms, experimentation, and ‘teachers of machines’ in China and the United States. Journalism Studies.
[PDF] | [BibTeX] | [Google Scholar]
2023
[22] Bernstein, M. S., Christin, A., Hancock, J. T., Hashimoto, T., Jia, C., Lam, M. S., Meister, N., Persily, N., Piccardi, T., Saveski, M., Tsai, J. L., Ugander, J., Xu, C. (2023). Embedding Societal Values into Social Media Algorithms. Journal of Online Trust and Safety.
[PDF] | [BibTeX] | [Google Scholar]
[21] Lee, T., Johnson, T., Jia, C., & Lacasa, I. (2023). How social media users become misinformed: The roles of news-finds-me perception and misinformation exposure in COVID-19 misperception. New Media & Society.
[PDF] | [BibTeX] | [Google Scholar]
[20] Jia, C. (2023). Effects of Issue Involvement and Algorithmic Literacy on Individuals’ Perceptions of News Recommended by Algorithms: A Machine Heuristic and Systematic Processing Model. SSRN.
[Preprint] | [BibTeX] | [Google Scholar]
[19] Zimmerman, T., Shiroma, K., Fleischmann, K.R., Xie, B., Verma, N., Jia, C., and Lee, M.K. (2023). Misinformation and COVID-19 Vaccine Hesitancy. Vaccine.
[PDF] | [BibTeX] | [Google Scholar]
[18] Lee, T., & Jia, C. (2023). Curse or Cure? The Role of Algorithm in Promoting or Countering Information Disorder. Information Disorder, 29-45. Routledge.
[PDF] | [BibTeX] | [Google Scholar]
[17] Shiroma, K., Zimmerman, T., Xie, B., Fleischmann, K.R., Rich, K., Lee, M.K., Verma, N., & Jia, C. (2023). Older adults' trust and distrust in COVID-19 public health information: A qualitative critical incident study. JMIR Aging. http://dx.doi.org/10.2196/42517
[PDF] | [BibTeX] | [Google Scholar]
2022
[16] Jia, C., *Boltz, A., *Zhang, A., Chen, A., & Lee, M. K. (2022). Understanding effects of algorithmic vs. community label on perceived accuracy of hyper-partisan misinformation. Proceedings of the ACM: Human-Computer Interaction. Issue CSCW (CSCW 2022).
[PDF] | [BibTeX] | [Google Scholar]
[15] Koo, H. G., Johnson, T., Lee, T., & Jia, C. (2022). Politically contested beliefs: Support for Trump better predicts having inaccurate beliefs about COVID-19 than being Conservative. Mass Communication and Society.
[PDF] | [BibTeX] | [Google Scholar]
[14] Liu, R., Jia, C., Wei, J., Xu, G., & Vosoughi, S. (2022). Quantifying and alleviating political bias in language models. Artificial Intelligence (AIJ).
[PDF] | [BibTeX] | [Google Scholar]
[13] Verma, N., Fleischmann, K. R., Zhou, L., Xie, B., Lee, M. K., Rich, K., Shiroma, K., Jia, C., & Zimmerman, T. (2022). Trust in COVID-19 public health information. Journal of the Association for Information Science and Technology, 1–17.
[PDF] | [BibTeX] | [Google Scholar]
[12] Liu, R., Gao, C., Jia, C., Xu, G., & Vosoughi, S. (2022). Non-parallel text style transfer with self-parallel supervision. Proceedings of the Tenth International Conference on Learning Representations (ICLR 2022).
[PDF] | [BibTeX] | [Google Scholar]
[11] Liu, R., Jia, C., Zhang, G., Zhuang, Z., Liu, T., Vosoughi, S. (2022). Second thoughts are best: Learning to re-align with human values from text edits. Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS 2022).
[PDF] | [BibTeX] | [Google Scholar]
2021
[10] Liu, R., Jia, C., Wei, J., Xu, G., Wang, Li., & Vosoughi, S. (2021). Mitigating political bias in language models through reinforced calibration. Proceedings of the 35th AAAI Conference on Artificial Intelligence (AAAI 2021).
[PDF] | [BibTeX] | [Google Scholar]
[9] Jia, C., & Liu, R. (2021). Algorithmic or human source? Examining relative hostile media effect with a transformer-based framework. Media and Communication. 9(4), 170 – 181.
[PDF] | [BibTeX] | [Google Scholar]
[8] Jia, C., & Johnson, T. (2021). Source credibility matters: Does automated journalism inspire selective exposure? International Journal of Communication. 15(2021), 3760–3781.
[PDF] | [BibTeX] | [Google Scholar]
[7] Liu, R., Wei, J., Jia, C., & Vosoughi, S. (2021). Modulating language models with emotions.
Proceedings of the Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021).
[PDF] | [BibTeX] | [Google Scholar]
[6] Liu, R., Jia, C., & Vosoughi, S. (2021). A transformer-based framework for flipping political polarity of news articles. Proceedings of the ACM: Human-Computer Interaction Journal. Issue CSCW 2021, Vol. 5.
[PDF] | [BibTeX] | [Google Scholar]
2020
[5] Jia, C. (2020). Chinese automated news: A comparison between expectations and perceived quality. International Journal of Communication. 14(2020), 2611–2632.
[PDF] | [BibTeX] | [Google Scholar]
[4] Jia, C., & Gwizdka, J. (2020). An eye-tracking study of differences in reading between automated news and human-written news. Davis, F., Riedl, R., Brocke, J., Léger, P., Randolph, A., Fischer, T. (Eds.), Information Systems and Neuroscience. vol 43, 100–110. Springer International Publishing.
[PDF] | [BibTeX] | [Google Scholar]
[3] Liu, R., Xu, G., Jia, C., Ma, W., Wang, L., & Vosoughi, S. (2020). Data Boost: Text data augmentation through reinforcement learning guided conditional generation. Proceedings of 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP 2020). 9031–9041. Association for Computational Linguistics.
[PDF] | [BibTeX] | [Google Scholar]
Workshop Papers
[2] Jia, C., Zhang, A., Boltz, A., Chen, A., & Lee, M. K. (2022). Algorithmic vs. Community Label Interventions on Perceived Accuracy of Hyper-partisan Misinformation. Workshop Proceedings of the International AAAI Conference on Web and Social Media (ICWSM 2022): Mediate 2022 ICWSM workshop.
White Papers
[1] Piccardi, T*., Saveski, M*., Jia, C*., Hancock, J. T., Tsai, J., & Bernstein, M. S. (2024). Reranking social media feeds: A practical guide for field experiments. ArXiv.
🏆
🏆