Introducing our 2024-25 Fellows
The Stanford Social Media Lab is thrilled to welcome our incoming postdoctoral and predoctoral fellows, along with visiting scholar Yi-Chia Wang. These new members, reflecting our lab’s expanding impact and diverse research interests, will immerse themselves in research and mentoring while actively contributing to our three core research areas: technology and well-being, AI-mediated communication, and misinformation and trust.
This year’s cohort includes six exceptional researchers, visiting scholar Yi-Chia Wang, postdoctoral fellows Fangjing Tu, William Schulz, Anja Stevic, and Harry Yan, and predoctoral fellow Sarah Wu.
Yi-Chia Wang received her Ph.D. from the Language Technologies Institute in School of Computer Science at Carnegie Mellon University in 2016. After graduation, she has been a Research Scientist in theindustry (Uber AI and Facebook/Meta AI). She will join the Social Media Lab as a Visiting Scholar in partnership with the Human-Computer Interaction Group at the Computer Science Department. Her research is interdisciplinary and lies in the intersection of Natural Language Processing (NLP), Computational Social Science (CSS), and Artificial Intelligence (AI). The goals are to study and model human-human and human-computer interaction in social contexts, understand its outcomes (e.g., engagement, well-being, integrity/fairness), and apply empirical findings to develop language technologies and interventions to better support these interactions. She has published more than 40 peer-reviewed papers in top-tier conferences/journals (e.g., ACL, EMNLP, CHI, CSCW, and theWebConf) and received awards, including the CHI Honorable Mention Paper Award, the CSCW Best Paper Award, and the AIED Best Student Paper Nomination. She has served as Area Chair of Dialogue and Interactive Systems track at AACL 2022, Associate Chair at CHI 2019, and program committees of numerous HCI and NLP conferences (e.g., ACL, SIGDIAL, COLING, CHI) for years. She was an invited keynote speaker in the SocialNLP workshop at ACL 2018 and gave invited speeches in the CS Colloquiums at Johns Hopkins University, UC Davis, and UC Santa Barbara in 2019.
Fangjing Tu received her Ph.D. in Communication from the University of Wisconsin-Madison. She earned an M.A. in Media Studies from the University of Texas at Austin and a B.A. in Journalism from Tsinghua University. Her research examines the challenges and solutions for citizens to stay informed in today’s media landscape, marked by the rampant spread of misinformation, widespread distrust in media and science, and the advancement of AI technology. Her research spans misinformation, media psychology, political communication, journalism, and science communication. Fangjing's dissertation explores the public’s susceptibility to and involvement in the spread of misinformation on social media and investigates scalable interventions to mitigate this issue. Currently, she is working on projects to develop digital literacy interventions to combat misinformation among marginalized populations and to investigate how political identity interacts with generative AI to influence individuals’ news judgment and engagement on social media.
Anja Stevic completed her Ph.D. in Communication Science at the University of Vienna, where her doctoral research focused on how different ways of using smartphones across generations influence interpersonal relationships and psychological well-being. Anja’s research interests include digital pressure related to social media use among adolescents, mobile communication, and AI-mediated communication in the context of online dating. Anja will join Social Media Lab as a postdoc.
Will Schulz received his PhD in 2024 from the Department of Politics at Princeton University, where his doctoral research sought to resolve two seemingly contradictory facts of American politics: (1) most people hold moderate or mixed political views, and yet (2) online political discourse is (apparently) polarized. Will's work includes both research and also the development of tools for data collection and analysis to facilitate that research. In his dissertation, Will developed an original method for characterizing individuals' political speech, and for estimating preference falsification and self-censorship, using a survey experiment exploiting contemporary political catchphrases. Most recently, he has focused on developing and implementing research projects with Argyle, which is a social media research tool adapted from the open-source Mastodon platform. Currently, Will is most interested in studying why certain individuals abstain from expressing their political views online, and the role of recommendation algorithms in contributing to differences in rates of online political expression.
Harry Yaojun Yan earned his Ph.D. from Indiana University Bloomington through the National Science Foundation's Interdisciplinary Trainee (NSF-NRT) program, with a dual major in Media Arts & Sciences at the Media School and Complex Networks & Systems (CNS) at the Luddy School of Informatics, Computing, and Engineering. Before joining the Cybersecurity Policy Center at Stanford, he was a Knight Foundation Research Fellow at the Observatory on Social Media (OSoMe) and served as a visiting assistant professor at Texas A&M University. His research explores the impact of AI-user interactions on user perceptions of social and political realities, as well as the process of public opinion formation. Currently, his work focuses on the effects of large language models (LLMs) on knowledge acquisition and language styles. He is also developing a public-facing open-source online platform for designing scalable and flexible human-AI interaction experiments.
Sarah Wu is a predoctoral research fellow in the Social Media Lab and a member of the inaugural predoc cohort at Stanford’s Institute for Research in the Social Sciences. Prior to joining the Social Media Lab, Sarah was the Operations Manager at a nonprofit youth orchestra in the Bay Area. She earned her BA in Psychology and Music minor from Reed College, where she wrote her senior thesis on the perceived narrative capabilities of AI music composers. In the Social Media Lab, Sarah aims to (1) understand the factors determining algorithm aversion across contexts and (2) develop and test interventions to improve adolescents’ social media use. In her free time, Sarah enjoys playing classical and tango violin in local ensembles, bouldering, and reading up-lit fiction.
