Truman is a complete social media simulation platform for experimental research. It creates a custom social media site where every user, post, like, reply, notification, and interaction can be created, curated and controlled by the research team. This social media simulation platform (named Truman after the 1998 film, The Truman Show) can create a controlled social media experience for participants. In this way, each participant is completely "alone" in this social media site, as every user they interact with is an actor being played by a "bot". This allows for complete control of the social situations and actions that take place on the platform, as every participant experiences the exact same social media experience. The Truman platform also allows for complete replication of any study as all the code, data, and media necessary to run this social media simulation is freely available on a public GitHub repository. Truman is an open source platform that is freely available for other researchers to use and build upon for their own studies.

Social Media TestDrive is a educational platform that lets kids practice being online while ensuring their mistakes won’t come back to haunt them, online or off. The training simulation (built off the Truman Platform) includes a number of lesson plans to teach social media skills to kids. It has been used by over 800,000 middle school students acorss the US.

DART is a cross-disciplinary, multi-institutional, user-centered effort to develop games and a learing platform to help older adults recognize and navigate scams. The Deception Awareness and Resilience Training (DART) platform aims to fill the gap in the lack of appropriate resources and training for older populations. A collaboration between researchers, game designers, and community organizations, our platform is unique in tailoring its curriculum and using gamification to make training accessible and engaging for seniors. The overarching goal of our DART project is the development of a research/educational platform with integrated digital tools, advanced pedagogical techniques, and timely materials to increase disinformation awareness and improve resilience, to inoculate users against the impact of harmful disinformation, and prevent its spread.

Although bystander intervention can mitigate the negative effects of cyberbullying, few bystanders ever attempt to intervene. In this study, we explored the effects of interface design on bystander intervention using a simulated custom-made social media platform. Participants took part in a three-day, in-situ experiment, in which they were exposed to several cyberbullying incidents. Depending on the experimental condition, they received different information about the audience size and viewing notifications intended to increase a sense of personal responsibility in bystanders. Results indicated that bystanders were more likely to intervene indirectly than directly, and information about the audience size and viewership increased the likelihood of flagging cyberbullying posts through serial mediation of public surveillance, accountability, and personal responsibility. The study has implications for understanding bystander effect in cyberbullying, and how to develop design solutions to encourage bystander intervention in social media.

This research aims to explore AI system's impact on inidviduals, groups and communities. We have run studies that have explored how personification of AI agents affects people’s sense of privacy violation, how smart reply systems affect group communication in chatting apps, and how AI-based social media moderation systems are perceived differ-ently than human-based ones.

Moshi is a web-based research platform that allows researchers to engage online participants in text-based, real-time interpersonal communication. Moshi provides a modular scaffold for experiments on text based AI-MC, allowing other researchers to modify it and explore their own research questions. The interface is reactive to device type and resizes itself to work well on desktops, tablets, and mobile devices (e.g., Android and iOS). In addition to the standard text box to send messages, participants can also receive smart replies that they can click or tap to send automatically. Similar to existing chat apps, users can also scroll to see the history of the conversation at any point.