I am an assistant professor at the Department of Computer Science and the Department of Information Science (by courtsey) at University of Colorado Boulder.
You can learn more about my life trajectory here.
My main research interests include
- Language and social dynamics.
- The effect of wording, how language influences social interaction such as persuasion and information sharing.
- The ecosystem of ideas, how ideas relate to each other and evolve over time.
- Multi-community engagement, how a person interacts with multiple communities and how communities relate to each other.
- Human-centered machine learning, how we can use machine learning to empower humans and augment human intelligence such as enhancing creativity and avoiding behavioral biases.
I am also broadly interested in computational social science, natural language processing, and artificial intelligence.
Here is my CV.
I am looking for motivated students who are interested in NLP, data science, computational social science or machine learning! Please read this FAQ before contacting me.
I am teaching a new course, Human-centered Machine Learning.
Here are three representative papers in the past three years:
- Chenhao Tan, Dallas Card, Noah A. Smith.
Friendships, Rivalries, and Trysts: Characterizing Relations between Ideas in Texts.[blog]
In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (ACL'2017)
- Chenhao Tan, Vlad Niculae, Cristian Danescu-Niculescu-Mizil, Lillian Lee.
Winning Arguments: Interaction Dynamics and Persuasion Strategies in Good-faith Online Discussions.
In Proceedings of the 25th International World Wide Web Conference (WWW'2016) (featured on The Washington Post and other media outlets, interview with You Are Not So Smart, on NPR).
- Chenhao Tan, Lillian Lee.
All Who Wander: On the Prevalence and Characteristics of Multi-community Engagement.
In Proceedings of the 24th International World Wide Web Conference (WWW'2015).
- TReMoLoop, text revision with a machine in the loop. Try to write a slogan!
- retweetedmore, predict which tweet is going to be retweeted more.
If you want to learn more about my research, check my papers. And kudos to all my collaborators!