Yuan Yuan

Assistant Professor, Purdue University

Hi! My name is Yuan Yuan (). I am a computational social scientist and an assistant professor at the Krannert School of Management (MIS area) at Purdue University. I am also a research fellow of the MIT Connection Science and the MIT Initiative on the Digital Economy.

I am interested in

  • leveraging big data and advanced computational techniques (e.g., machine learning and causal inference) to study online social interactions and social networks.
  • developing computational techniques that combine machine learning and causal inference, with applications to online field experiments (a.k.a A/B testing).

Before Purdue, I did my PhD in Institute for Data, Systems, and Society (IDSS) at Massachusetts Institute of Technology. I received my Bachelor's degrees with honors in Computer Science and Economics from Tsinghua University.

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News


Selected work

[6] Yuan Yuan, Eaman Jahani, Shengjia Zhao, Yong-Yeol Ahn, and Alex Pentland "Mobility network reveals the impact of geographic vaccination heterogeneity on COVID-19", working paper, [preprint]

[5] Yuan Yuan, Christos Nicolaides, Alex Pentland, and Dean Eckles "Promoting physical activity through prosocial incentives on mobile platforms", working paper [preprint]

[4] Yuan Yuan, Tracy Xiao Liu, Chenhao Tan, Qian Chen, Alex Pentland, and Jie Tang, "Gift contagion in online groups: Evidence from virtual red packets" [Minor revision at Management Science] [preprint]

[3] Ding Lyu, Yuan Yuan (corr author), Lin Wang, Xiaofan Wang, Alex Pentland, "Investigating and Modeling the Dynamics of Long Ties", Communications Physics (Nature Portfolio), [paper]

[2] Yuan Yuan, Kristen Altenburger, and Farshad Kooti, "Causal Network Motifs: Identifying Heterogeneous Spillover Effects in A/B Tests", WWW'2021 [paper].

[1] Yuan Yuan, Ahmad Alabdulkareem, Alex Pentland, "An Interpretable Approach for Social Network Formation Among Heterogeneous Agents", Nature Communications, 2018 [paper].

Talks

Invited talks
  • [5] “Causal Network Motifs: Identifying Heterogenous Spillover Effects in A/B Tests”, invited talk, Networks Seminar, Oxford Mathematical Institute, Nov 2020.
  • [4] “Causal identifications in observational studies” invited talk, Big Data and Social Computing, Aug 2020.
  • [3] “Identifying gift contagion in online groups, ” guest lecturer for Behavioral Economics, Tsinghua University (remotely), Mar 2020.
  • [2] “Predicting economic growth by social diversity, ” invited talk, International Conference on Social Computing, Aug 2019.
  • [1] “Trading off between homophily and social exchange for social network formation, ” invited talk, Beijing Normal University, Jan 2019.
Conference presentations
  • [15] “Network Motifs with Treatment Assignment Conditions: Identifying Heterogeneous Network Interference Eects in A/B Tests,” Conference on Digital Experimentation (CODE), Nov 2020.
  • [14] “Prosocial Incentives and Workouts: Evidence from a Massive Online Experiment,” Conference on Digital Experimentation (CODE), Nov 2020.
  • [13] “Who motivates more workouts: Friends or strangers?” International Conference on Network Science (NetSci), Rome, Sept 2020.
  • [12] “Who motivates more workouts: Friends or strangers?”, International Conference on Computational Social Science (IC2S2), Boston, July 2020.
  • [11] “The contagion of online gift giving,” INFORMS Annual Meeting, Seattle, Oct 2019.
  • [10] “Does prosocial contagion increase inequality? A large-scale online field experiment,” International
  • Conference on Computational Social Science (IC2S2), Amsterdam, July 2019.
  • [9] “A large-scale natural experiment of indirect reciprocity,” Conference on Digital Experimentation (CODE), Boston, Oct 2018.
  • [8] “A large-scale natural experiment of indirect reciprocity,” Advances in Field Experiments (AFE), Boston, Oct 2018.
  • [7] “Online red packets: A large-scale empirical study of gift giving on WeChat,” International Conference on Computational Social Science (IC2S2), Evanston, July 2018.
  • [6] “An interpretable approach for social network formation among heterogeneous agents,” International Conference on Computational Social Science (IC2S2), Evanston, July 2018.
  • [5] “Trade-off between social exchange and homophily in social network formation,” International Conference on Network Science (NetSci), Paris, June 2018.
  • [4] “A large-scale empirical study of gift giving on WeChat,” Annual Conference on Network Science and Economics (NetSci Econ), Nashville, Apr 2018.
  • [3] “Trade-off between social exchange and homophily in social network formation,” Annual Conference on Network Science and Economics (NetSci Econ), Nashville, Apr 2018.
  • [2] “Social network formation based on endowment exchange. and Social Representation,” Conference on Complex Systems (CCS), Cancún, Oct 2017.
  • [1] “Interpretable and effective opinion spam detection via temporal pattern mining across websites,” IEEE International Conference on Big Data (BigData), Washington DC, Dec 2016.

Services

Technical program committee: Conference ON Digital Experimentation (CODE), 2019 & 2020.

Organizer: Summer Institute in Computational Social Science (SICSS), Beijing .

Reviewer: Management Science, MIS Quarterly, IC2S2, CODE, TKDD, IEEE Transactions on Big Data, HKS Misinformation Review.

Services

I am teaching PhD level Social Network Analysis in Fall 2021.

I will be teaching undergraduate level Introduction to MIS in Spring 2022.


Contact

If you have any questions or just want to have a chat, please contact me via:

Email: yuanyuan [at] purdue [dot] edu

Purdue office: 403 W State St, Room 709, West Lafayette, IN 47907

Twitter: