Publications
Peer Reviewed Publications (selected):
Journal Articles and Conference Proceedings
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.
[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.
Peer Reviewed Conference Papers (selected):
Jia, C., Lee, A. Y., Moore, R. C., Decatur, C. H., Qiu, T., Liu, S. X., Hancock, J. T. (2024). Group Discussion Improves Detection of Misinformation on Social Media. Communication & Technology Division. 74th Annual International Communication Association Conference, Reclaiming Authenticity in Communication (ICA 2024), June 20-24, 2023, Gold Coast, Australia.
Jia, C., Li, J., Liu, S. X., Tang, L., Bagdasarian, T., Baird, C., Vaughan, C., Hancock, J. T. (2024). Averse Towards AI or Human? A Meta-Analysis of Impacts of Task Objectivity and Agent Characteristics on Algorithm Appreciation and Aversion. Human-Machine Communication Division. 74th Annual International Communication Association Conference, Reclaiming Authenticity in Communication (ICA 2024), June 20-24, 2023, Gold Coast, Australia.
Jia, C., Lu, Y., Kim, S. (2024). Nudging Emotions via AI: Examining the Effect of Emotion-Interventions on Reducing Susceptibility to Text and Image Misinformation. Communication & Technology Division. 74th Annual International Communication Association Conference, Reclaiming Authenticity in Communication (ICA 2024), June 20-24, 2023, Gold Coast, Australia. (Panel: Algorithmically Yours: Communicating in the Age of Generative AI)
Jia, C. (2023) Effects of Issue Involvement and Algorithmic Literacy on Individuals’ Perceptions of News Recommended by Algorithms. Communication & Technology Division. 73rd Annual International Communication Association Conference, Reclaiming Authenticity in Communication (ICA 2023), May 25-29, 2023, Toronto, Ontario, Canada.
Jia, C. (2023). Understanding Effects of Machine vs. Human Heuristics on People’s Perceptions of Political News. Human-Machine Communication Division. 73rd Annual International Communication Association Conference, Reclaiming Authenticity in Communication (ICA 2023), May 25-29, 2023, Toronto, Ontario, Canada.
Lu, S., & Jia, C. (2022). Mitigating psychological reactance in online content moderation: A communication visibility perspective. The 72nd Annual International Communication Association Conference (ICA 2022), May 26-30, 2022, Paris, France.
Koo, H. G., Johnson, T., Lee, T., & Jia, C. (2021). Politically contested beliefs: Why do conservatives tend to have more inaccurate beliefs about COVID-19? Mass Communication & Society Division. The Association for Education in Journalism and Mass Communication (AEJMC 2021) Summer’s Annual Conference, August 4-7, 2021, Virtual Conference.
Jia, C., Johnson, T., Wallace, R., & Lee, T. (2021). News algorithm appreciation or aversion? Examining media trust and algorithm attitudes. The 71st Annual International Communication Association Conference (ICA 2021), Human-Machine Communication Interest Group, May 27–31, 2021, Virtual Conference.
Jia, C., & Liu, R. (2021). Examine relative hostile media effect with a transformer-based framework: A computational method to flip the polarity of news headline and body text. The 71st Annual International Communication Association Conference (ICA 2021), Communication & Technology Division, May 27–31, 2021, Virtual Conference.
Jia, C., and Johnson, T. (2020). Source credibility matters: Does automated journalism inspire selective exposure? The 70th Annual International Communication Association Conference(ICA 2020), Communication & Technology Division, May 21-25, 2020, Virtual Conference.
Jia, C., and Woolley, S. (2020). Social scaffolding or computational propaganda?: A comparative analysis of automated journalism in China and the United States. The 70th Annual International Communication Association Conference, Political Communication Division (ICA 2020). May 21-25, 2020, Virtual Conference.
Jia, C. (2019). Chinese automated news: A comparison between prior expectations and actual perceptions. The Association for Education in Journalism and Mass Communication Summer’s Annual Conference (AEJMC 2019), The Communication Technology Division, August 7-10, Toronto, Canada.
Jia, C. (2019). Chinese automated news: Readability, expertise and credibility. The Association for Education in Journalism and Mass Communication (AEJMC) Mid-winter Conference, The Communication Technology Division, March 1-2, the University of Oklahoma, Norman, Oklahoma, the United States.
Jia, C., Yao, Y., & Zhong, W. (2017). The readability analysis of Chinese and English automated news. International Communication Association (ICA) International New Media Forum, Panel 2: News Production in the Digital Age, November 11, Shanghai, China.
Jia, C. (2017). The development mode of printed media' s WeChat accounts in Zhejiang province: Based on empirical research on Urban Express, Qianjiang Evening News, and Hangzhou Daily. International Symposium on Chinese Newspapers, Panel 2A, June 1 -2, Hong Kong, China.