Through portraying and predicting human behaviour & psychology by computational thinking, I step towards my goal to be a computational social scientist.


Google Scholar



Netease Music



State Key Lab of Software Development Environment (软件开发环境国家重点实验室)
Beihang University (北航), Beijing, China


Hernan Makse's Lab

Jichang Zhao's Group (赵吉昌教授)

Zhenkun Zhou 👨🏻‍💻

Zhenkun Zhou (周振坤) is a Ph.D. candidate of Computer Science in Beihang University under supervision of Professor Ke Xu (许可). His research focuses on computational social science, social networks and machine learning (计算社会科学,社交网络,机器学习).

From 2018, he has been visiting Levich Institute, City College of New York, under supervision of Professor Hernan Makse.

He also works as an intern researcher and big-data engineer in Company of Warming Technology, in charge of analyzing online social networks and stock markets.

Selected Publications

Homophily of Music Listening in Online Social Networks of China
Social Networks, Volume 55, October 2018, Pages 160-169
Extroverts Tweet Differently from Introverts in Weibo
EPJ Data Science, 2018. 7:18
Tales of Emotion and Stock in China: Volatility, Causality and Prediction
World Wide Web, 2017.
Can Online Emotions Predict the Stock Market in China?
Web Information Systems Engineering (WISE), 2016.
*Best Paper Award Honorable Mention (最佳论文奖提名)

Dance music joints musicians of different genres
Through systematically studying the collaboration network of musicians, we conclude that dance music plays an essential role in promoting the collaboration of musicians in music creation.

Working Projects

How Brainwashing Songs Wash the Brain
The study explores the method to recognize those "brainwashing" songs and try to find an effective and accurate way to predict the popularity of songs. In addition, through the EEG experiment, the research verifies that brainwiashing songs could have some impact on human brain.
Losses Loom Larger than Gains in Social Media
This research investigates the association between stock market and corresponding online behaviors in social media. It is revealed that people are not only sensitive to losses than to gains, but also attach great importance to losses, which demonstrate the robustness of the sensitive and attentional effect of losses.

Online Applications

Live Daily Prediction Using Artificial Intelligence
Through collecting a massively large number of tweets and building machine learning models, Zhenkun Zhou and Hernan Makse investigate the dynamics of the Twitter social network formed by the interactions among millions of Twitter supporters. We then infer the opinion of each user with Artificial Intelligence on the candidates of the 2019 Argentina presidential election.
This project is collecting kinds of real-time data in Netease Music platform, including the massive user listening behaivor. Through online analyzing the indivdual and collective listening records, we uncover ''WHO ARE U'' in music.
Stock Prediction System with SVM-ES
The system applies the SVM based on online emotions to predict the price and volume of stock market in China. It provides the prediction results to Company of Warming Technology for paid service.


Journal Reviewer
Cyberpsychology, Behavior, and Social Networking; PLoS One; IEEE Transactions on Big Data; Journal of Computational Social Science