Publications

Lu, Y., & Pan J. (2021). The Pervasive Presence of Chinese Government Content on Douyin Trending Videos. Computational Communication Research. Forthcoming. (Preprint)

  • Abstract: As audiences have moved to digital media, so too have authoritarian regimes. While previous research has focused on how authoritarian regimes employ strategies such as the use of fabricated accounts and content to boost their reach, this paper reveals two different tactics the Chinese regime uses on Douyin, the Chinese version of the video-sharing platform TikTok, to compete for audience attention. We use a multi-modal approach that combines analysis of video, text, and meta-data to examine a novel dataset of Douyin videos. We find that a large share of trending videos are produced by accounts affiliated with the Chinese regime. These videos contain visual characteristics designed to maximize attention such as high levels of brightness and entropy and very short duration, and are more visually similar to content produced by celebrities and ordinary users than to content from non-official media accounts. We also find that the majority of videos produced by regime-affiliated accounts do not fit traditional definitions of propaganda but rather contain stories and topics unrelated to any aspect of the government, the Chinese Communist Party, policies, or politics.

Lu, Y., Pan J., & Xu Y. (2021). Public Sentiment on Chinese Social Media during the Emergence of COVID-19. Journal of Quantitative Description: Digital Media. 1, 2021, 1-47. (DOI, Replication)

  • Abstract: When COVID-19 first emerged in China, there was speculation that the outbreak would trigger public anger and weaken the Chinese regime. By analyzing millions of social media posts from Sina Weibo made between December 2019 and February 2020, we describe the contours of public, online discussions pertaining to COVID-19 in China. We find that discussions of COVID-19 became widespread on January 20, 2020, consisting primarily of personal reflections, opinions, updates, and appeals. We find that the largest bursts of discussion, which contain simultaneous spikes of criticism and support targeting the Chinese government, coincide with the January 23 lockdown of Wuhan and the February 7 death of Dr. Li Wenliang. Criticisms are directed at the government for perceived lack of action, incompetence, and wrongdoing—in particular, censoring information relevant to public welfare. Support is directed at the government for aggressive action and positive outcomes. As the crisis unfolds, the same events are interpreted differently by different people, with those who criticize focusing on the government’s shortcomings and those who praise focusing on the government’s actions.

Lu, Y., & Pan J. (2021). Capturing Clicks: How the Chinese Government Uses Clickbait to Compete for Visiblity. Political Communication. 38(1-2), 23-54. (DOI, Appendix, Replication)

  • Abstract: The proliferation of social media and digital technologies has made it necessary for governments to expand their focus beyond propaganda content in order to disseminate propaganda effectively. We identify a strategy of using clickbait to increase the visibility of political propaganda. We show that such a strategy is used across China by combining ethnography with a computational analysis of a novel dataset of the titles of 197,303 propaganda posts made by 213 Chinese city-level governments on WeChat. We find that Chinese propagandists face intense pressures to demonstrate their effectiveness on social media because their work is heavily quantified–measured, analyzed, and ranked–with metrics such as views and likes. Propagandists use both clickbait and non-propaganda content (e.g., lifestyle tips) to capture clicks, but rely more heavily on clickbait because it does not decrease space available for political propaganda. Government propagandists use clickbait at a rate commensurate with commercial and celebrity social media accounts. The use of clickbait is associated with more views and likes, as well as greater reach of government propaganda outlets and messages. These results reveal how the advertising-based business model and affordances of social media influence political propaganda and how government strategies to control information are moving beyond censorship, propaganda, and disinformation.

Reeves, B., Ram N., Robinson T. N., Cummings J. J., Giles L., Pan J., Chiatti A., Cho M., Roehrick K., Yang X., Gagneja A., Brinberg M., Muise D., Lu Y., Luo M., Fitzgerald A., Yeykelis L. (2021). Screenomics: A Framework to Capture and Analyze Personal Life Experiences and the Ways that Technology Shapes Them. Human-Computer Interaction. 36(2), 150-201. (DOI. New York Times report)

  • Abstract: Digital experiences capture an increasingly large part of life, making them a preferred, if not required, method to describe and theorize about human behavior. Digital media also shape behavior by enabling people to switch between different content easily, and create unique threads of experiences that pass quickly through numerous information categories. Current methods of recording digital experiences provide only partial reconstructions of digital lives that weave – often within seconds – among multiple applications, locations, functions, and media. We describe an end-to-end system for capturing and analyzing the “screenome” of life in media, i.e., the record of individual experiences represented as a sequence of screens that people view and interact with over time. The system includes software that collects screenshots, extracts text and images, and allows searching of a screenshot database. We discuss how the system can be used to elaborate current theories about psychological processing of technology, and suggest new theoretical questions that are enabled by multiple timescale analyses. Capabilities of the system are highlighted with eight research examples that analyze screens from adults who have generated data within the system. We end with a discussion of future uses, limitations, theory, and privacy.

Lu, Y. (2015). Social Media Technology and Female Emancipation in China: Case Study in Sina-Weibo, Synergy: The Journal of Contemporary Asian Studies, University of Toronto, 12(1). (online access)

Working Papers / Selected Works in Progress

Selectively Localized: Comparing Temporal and Visual Structure of Screen Interactions across Media Environments,” with Dan Muise, Jennifer Pan, and Byron Reeves, Revise and Resubmit, Mobile Media & Communication

Pandemic Nationalism: Use of Government Social Media for Political Information and Belief in COVID-19 Conspiracy Theories in China,” with Anfan Chen, Kaiping Chen, and Aaron Ng, Under review

Information Flows Between Global and Chinese Social Media,” with Jack Schaefer, Kunwoo park, Jungseock Joo, and Jennifer Pan, Under review

The Influencer Pay Gap: Platform Labor Meets Racial Capitalism,” with Angèle Christin, Extended abstract under review

Unpacking multimodal fact-checking: Features and engagement of fact-checking videos on Chinese TikTok (Douyin),” with Cuihua Cindy Shen

Selected Conference Presentations

Lu, Y., Pan, J. & Xu, Y. (2021, September). Public Sentiment on Chinese Social Media during the Emergence of COVID-19. Presented in “Chinese Politics Mini-Conference” at American Political Science Association Annual Meeting

Lu, Y. & Shen, C. (2021, September). Unpacking multimodal fact-checking: features and engagement of fact-checking videos on Chinese TikTok. Presented at The 3rd Multidisciplinary International Symposium on Disinformation in Open Online Media

Lu, Y., Schaefer, J., Joo, J., Park, K. & Pan, J. (2021, September). Tale of Two Internets: How Information Flows from the US to Chinese Social Media. Presented at Virtual Conference of the International Journal of Press/Politics

Chen, A., Lu, Y., Chen, K., & Ng, A. (2021, September). Pandemic Nationalism: How Exposure to Government Social Media Affects People’s Belief in COVID-19 Conspiracy Theories in China. Presented at Virtual Conference of the International Journal of Press/Politics

Lu, Y. & Pan, J. (2021, August). The Pervasive Presence of Chinese Government Content on Douyin Trending Videos. Presented at Association for Education in Journalism and Mass Communication (AEJMC) 2021 Annual Conference

Lu, Y. & Pan, J. (2021, July). The Pervasive Presence of Chinese Government Content on Douyin Trending Videos. Presented at International Conference on Computational Social Science (IC2S2) 2021

Lu, Y. & Pan, J. (2020, September). Capturing Clicks: How the Chinese Government Uses Clickbait to Compete for Visiblity. Presented in “Chinese Politics Mini-Conference” at American Political Science Association Annual Meeting.

Lu, Y. & Pan, J. (2020, May). Capturing Clicks: How the Chinese Government Uses Clickbait to Compete for Visiblity. Presented in panel “Propaganda in the computational age: disinformation and beyond” at International Communication Association’s 70th Annual Conference. (Panel video)

Lu, Y., Muise D., Pan, J., & Reeves, B. (2018, May). Micro-Level Natural Interaction with Information Systems: An International Screenshot Comparison. Presented at International Communication Association’s 68th Annual Conference, Prague, Czech Republic. (Presentation file)

Lu, Y. (2017, November). National Identity Shift in Taiwan Through Media: Case Study of News Reports on Cross-Strait Tourism. Presented at National Communication Association 2017 Annual Convention, Dallas, TX.

Lu, Y., & Yu, X. (2016, November). Public Intellectuals Deliberation on Chinese Weibo: Case study of School-bus Safety Incident. Presented at National Communication Association 2016 Annual Convention, Philadelphia, PA.

Lu, Y. (2016, June). Reimagining Civility from Public and Media: Agendas in Chinese Haze Governance. Presented at Asian Studies on the Pacific Coast 2016 Conference, California State University, Northridge, CA.

Invited Talks / Guest Lectures

Stanford University, Center for Work Technology and Organization (Dec 2021)

ICA Regional Hub Symposium, China (May 2021)

Stanford University, Data Science Lab (Feb 2020)(Feb 2021)

Tsinghua University, China Computational Social Science Forum (Jan 2021)

University of Wisconsin-Madison, Social Media Analytics (Nov 2020)

University of San Francisco, Natural Language Processing (Nov 2020)

Tsinghua University, Comparative Journalism Studies (Nov 2020)

United Nations University on Computing and Society, Conversation Series (July 2019)(event news)

Tsinghua University, Political Methodology Workshop (Jan 2018)