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Kai-Cheng Yang


Hi! I'm Kai-Cheng Yang (杨凯程), the pronunciation is KY-cheng YAHNG. I also go by Kevin.

I'm a second year Ph.D student in Informatics at School of Informatics, Computing and Egineering in Indiana University Bloomington. I mainly work with Filippo Menczer, Yong-Yeol Ahn and Brea L. Perry. Check out the Projects and Publications sections for what I have been working on.

Before joining the Ph.D program at IU, I received my bachelor and master degree in theoretical physics from Lanzhou University in China.


  • Nov 20, 2018: Our paper The spread of low-credibility content by social bots has been published in Nature Communications.


  1. Shao, C., Ciampaglia, G. L., Varol, O., Yang, K. C., Flammini, A., & Menczer, F. (2018) The spread of low-credibility content by social bots. Nature Communications, 9(1), 4787.
  2. Yang, K. C. , Wu, Z. X., Holme, P., & Nonaka, E. (2017). Expansion of cooperatively growing populations: Optimal migration rates and habitat network structures. Physical Review E, 95(1), 012306.


Bot Electioneering Volume

BEV is a tool that visualizes the activity of likely bots on Twitter around the 2018 US midterm elections. It allows to explore how active bots are on a daily basis in efforts to influence online discourse about the elections. It also shows what topics are being targeted by likely bots.


Geographical characterization of doctor shoppers

Doctor shoppers are people that visit multiple physicians to obtain multiple prescriptions of controlled substances. The opioid doctor shoppers have been found to be more likely to overdose leading to the ever severer opioid crisis in US. The project intends to apply computational methods to over 9 years of longitudinal medical records from a large group of patients to characterize the geographics related behaviors of doctor shoppers.

Medical diagnosis embedding

Word2vec is applied to large scale of medical records to find a distributed representation of the diagnoses. The embedding can effectively reduce the dimensions needed to encode all the diagnoses therefore serves as a preprocessing step for other machine learning tasks. Besides, the embedding itself can reveal interesing relationship between diagnoses.


Botometer is a machine learning tool that can extract over 1000 different features from a Twitter account and evaluate its likelihood of being social bot. Botometer supports many other services like BEV and Hoaxy.

Contribution: maintenance, training data annotation and model retraining



Hoaxy is a tool that visualizes the spread of articles online. Articles can be found on Twitter, or in a corpus of claims and related fact checking. With the incorporation of Botometer, Hoaxy can also visualize the composition of accounts invovled in certain articles in terms of bot-like behaviors.

Contribution: developing API for Hoaxy to fetch Botometer scores

Hoaxy Paper


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