Kyuyoung Kim
Ph.D. student, KAIST AI
kykim [AT] cs.stanford.edu
Bio
My research develops tools for analyzing large-scale social data, aiming to provide a better understanding of social structure and behaviors online while also impacting the design of digital social systems. My recent work has focused on reducing political polarization online [ICWSM'22a, ICWSM'22b, WSDM'21, WWW'18], improving the health of online conversations [WWW'21, CSCW'21], and causal inference in social systems [KDD'17 Biometrika'19]. My research often falls at the intersections of Social Networks, Machine Learning, and Causal Inference.
I'm an Assistant Professor in the Information School at the University of Washington. Before joining UW, I was a Postdoc at Stanford University, mentored by Johan Ugander. I received my Ph.D. from MIT in 2020 under the supervision of Deb Roy. Prior to coming to MIT, I spent one year in Paris and one year in Barcelona doing a M.Sc. in Data mining and Knowledge Management. I got my B.Sc. from Staffordshire University with First Class honors in Computer Science. Throughout my graduate studies, I spent several summers doing internships in industry, including Yahoo! Labs, Amazon, LinkedIn, and Facebook.
Prospective Students
I'm recruiting PhD students to start Fall 2024 at the University of Washington!
I'm looking for students passionate about using computational methods to study how social platforms can be reimagined to enable better conversations, bridge political divides, and reduce the spread of misinfo.
I'm particularly interested in the role of algorithms in social platforms.
I'm especially looking for students with a background and/or interest in social network analysis, machine learning, causal inference, or natural language processing.
If you are interested, please apply to the UW iSchool PhD program and mention me in your application.
If you have any questions, feel free to reach out.
Publications
Most recent publications on Google Scholar.
‡ indicates equal contribution.
Embedding Societal Values into Social Media Algorithms
Michael Bernstein, Angèle Christin, Jeffrey Hancock, Tatsunori Hashimoto, Chenyan Jia, Michelle S. Lam, Nicole Meister, Nathaniel Persily, Tiziano Piccardi, Martin Saveski, Jeanne Tsai, Johan Ugander, Chunchen Xu
JOTS'23: Journal of Online Trust and Safety. 2023.
Counterfactual Evaluation of Peer-Review Assignment Policies
Martin Saveski, Steven Jecmen, Nihar B. Shah, Johan Ugander
NeurIPS'23: Advances in Neural Information Processing Systems (Spotlight). 2023.
Engaging Politically Diverse Audiences on Social Media
Martin Saveski, Doug Beeferman, David McClure, Deb Roy
ICWSM'22: International AAAI Conference on Web and Social Media. 2022.
Perspective-taking to Reduce Affective Polarization on Social Media
Martin Saveski‡, Nabeel Gillani‡, Ann Yuan, Prashanth Vijayaraghavan, Deb Roy
ICWSM'22: International AAAI Conference on Web and Social Media. 2022.
The Structure of Toxic Conversations on Twitter
Martin Saveski, Brandon Roy, Deb Roy
WWW'21: The Web Conference 2021
Social Catalysts: Characterizing People Who Spark Conversations Among Others
Martin Saveski, Farshad Kooti, Sylvia Morelli Vitousek, Carlos Diuk, Bryce Bartlett, Lada Adamic
CSCW'21: Conference on Computer-Supported Cooperative Work and Social Computing
Me, My Echo Chamber, and I: Introspection on Social Media Polarization
Nabeel Gillani, Ann Yuan, Martin Saveski, Soroush Vosoughi, Deb Roy
WWW'18: International Conference on the World Wide Web. 2018. (Honarable mention)
Detecting Network Effects: Randomizing Over Randomized Experiments
Martin Saveski‡, Jean Pouget-Abadie‡, Guillaume Saint-Jacques, Weitao Duan, Souvik Ghosh, Ya Xu, Edo Airoldi
KDD'17: International Conference on Knowledge Discovery and Data Mining. 2017. (Research Track)
One-Pass Ranking Models for Low-Latency Product Recommendations
Antonino Freno, Martin Saveski, Rodolphe Jenatton, Cédric Archambeau
KDD'15: International Conference on Knowledge Discovery and Data Mining. 2015. (Industry Track)
Item Cold-Start Recommendations: Learning Local Collective Embeddings
Martin Saveski, Amin Mantrach.
RecSys'14, ACM Conference Series on Recommender Systems. 2014.
Embedding Societal Values into Social Media Algorithms
Michael Bernstein, Angèle Christin, Jeffrey Hancock, Tatsunori Hashimoto, Chenyan Jia, Michelle S. Lam, Nicole Meister, Nathaniel Persily, Tiziano Piccardi, Martin Saveski, Jeanne Tsai, Johan Ugander, Chunchen Xu
JOTS'23: Journal of Online Trust and Safety. 2023.
Counterfactual Evaluation of Peer-Review Assignment Policies
Martin Saveski, Steven Jecmen, Nihar B. Shah, Johan Ugander
NeurIPS'23: Advances in Neural Information Processing Systems (Spotlight). 2023.
Engaging Politically Diverse Audiences on Social Media
Martin Saveski, Doug Beeferman, David McClure, Deb Roy
ICWSM'22: International AAAI Conference on Web and Social Media. 2022.
Perspective-taking to Reduce Affective Polarization on Social Media
Martin Saveski‡, Nabeel Gillani‡, Ann Yuan, Prashanth Vijayaraghavan, Deb Roy
ICWSM'22: International AAAI Conference on Web and Social Media. 2022.
The Structure of Toxic Conversations on Twitter
Martin Saveski, Brandon Roy, Deb Roy
WWW'21: The Web Conference 2021
Social Catalysts: Characterizing People Who Spark Conversations Among Others
Martin Saveski, Farshad Kooti, Sylvia Morelli Vitousek, Carlos Diuk, Bryce Bartlett, Lada Adamic
CSCW'21: Conference on Computer-Supported Cooperative Work and Social Computing
Balanced Influence Maximization in the Presence of Homophily
Md Sanzeed Anwar, Martin Saveski, Deb Roy
WSDM'21: International Conference on Web Search and Data Mining
Algorithmic and Human Prediction of Success in Human Collaboration From Visual Features
Martin Saveski‡, Edmond Awad‡, Iyad Rahwan, Manuel Cebrian
Nature Scientific Reports. 2021
Testing for Arbitrary Interference on Experimentation Platforms
Jean Pouget-Abadie, Guillaume Saint-Jacques‡, Martin Saveski‡, Weitao Duan, Souvik Ghosh, Ya Xu, Edo Airoldi
Biometrika. 2019.
Observational Causal Inference Using Network Information
Yan Leng, Martin Saveski, Alex ‘Sandy’ Pentland, Dean Eckles
NeurIPS'19, Workshop on Graph Representation Learning. 2019.
Me, My Echo Chamber, and I: Introspection on Social Media Polarization
Nabeel Gillani, Ann Yuan, Martin Saveski, Soroush Vosoughi, Deb Roy
WWW'18: International Conference on the World Wide Web. 2018. (Honarable mention)
Detecting Network Effects: Randomizing Over Randomized Experiments
Martin Saveski‡, Jean Pouget-Abadie‡, Guillaume Saint-Jacques, Weitao Duan, Souvik Ghosh, Ya Xu, Edo Airoldi
KDD'17: International Conference on Knowledge Discovery and Data Mining. 2017. (Research Track)
Human Atlas: A Tool for Mapping Social Networks
Martin Saveski, Eric Chu, Soroush Vosoughi, Deb Roy
WWW'16: International Conference on the World Wide Web. 2016. (Demo)
Topic Modeling in Twitter: Aggregating Tweets by Conversations
David Alvarez-Melis‡, Martin Saveski‡
ICWSM'16: International AAAI Conference on Web and Social Media. 2016. (Short Paper)
Tracking the Yak: An Empirical Study of Yik Yak
Martin Saveski, Sophie Chou, Deb Roy.
ICWSM'16: International AAAI Conference on Web and Social Media. 2016. (Short Paper)
One-Pass Ranking Models for Low-Latency Product Recommendations
Antonino Freno, Martin Saveski, Rodolphe Jenatton, Cédric Archambeau
KDD'15: International Conference on Knowledge Discovery and Data Mining. 2015. (Industry Track)
Item Cold-Start Recommendations: Learning Local Collective Embeddings
Martin Saveski, Amin Mantrach.
RecSys'14, ACM Conference Series on Recommender Systems. 2014.
The Geography of Online News Engagement
Martin Saveski, Daniele Quercia, Amin Mantrach
Socinfo'14: International Conference on Social Informatics. 2014.
Joint semi-supervised Learning of Hidden Conditional Random Fields and Hidden Markov Models
Yann Soullard, Martin Saveski, Thierry Artières
Pattern Recognition Letters. 2013.
Web Services for Stream Mining: A Stream-Based Active Learning Use Case
Martin Saveski, Miha Grčar
ECML'11, Workshop on Planning to Learn and Service-Oriented Knowledge Discovery. 2011.
Automatic Construction of Wordnets by Using Machine Translation and Language Modeling
Martin Saveski, Igor Trajkovski
In Proceedings of Seventh Language Technologies Conference. 2010.
Development of an English-Macedonian Machine Readable Dictionary by Using Parallel Corpora
Martin Saveski, Igor Trajkovski
Proceedings of ICT Innovations Conference. 2010.
Vitæ
Full Resume in PDF.
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KAIST AI 2023 - nowPh.D. Student
Graduate School of AI -
Stanford University 2021 - 2023M.S. Student
Computer Science
Distinction in Research -
Google 2013 - 2021Senior Software Engineer
Google Assistant
Google Research
Display Ads -
Facebook Aug 2012 - Nov 2012Software Engineer, Intern
Messages Backend -
Cornell UniversityB.S. Student
Computing Science
Magna cum laude
Website Design
Since I made this website, many people have found this Jekyll template useful [ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38 ]. You can find all the code needed to build your website in this GitHub repo. Feel free to use it.If you end up using it, please link to here and drop me an email. I'm always happy to see people using it.