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Social Network Lab
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The lab studies how information spreads on social media by analyzing networks.
AboutAbout the lab
Understanding a complex society through networks.
The Social Network Lab studies the mechanisms of a complex society by focusing on the connections between people.
The lab analyzes large-scale data from the Web and social media to investigate how information flows and spreads.
Its research topics also include identifying influencers and methods for curbing the spread of misinformation such as fake news.
For fourth-year undergraduate graduation research, the lab accepts students from the College of Media Arts, Science and Technology and the College of Information Science.
Key terms
- Social network
- A representation of connections between people as a network of nodes and links, used to study the structure of human society
- Influencer
- A person who triggers the explosive spread of information between people
- Graph neural network
- A type of neural network designed to handle network data made up of nodes and links
NewsLab news
Held a lab information session for third-year students of the College of Media Arts, Science and Technology (10/20)
A paper by a master's student received the Best Student Paper Runner-up at ASONAM2026
A paper by a master's student was published in the international journal Social Network Analysis and Mining
Associate Professor Tsugawa was selected for the Best Reviewer Award at ICWSM2026
A student received the FY2025 Dean's Award of the College of Media Arts, Science and Technology
ResearchResearch themes
With "networks" as its keyword, the Social Network Lab pursues empirical and theoretical research that contributes to a deep understanding of a complex society, and develops fundamental technologies that contribute to solving social problems. Its main research topics are the analysis of large-scale data on the Web and social media, network analysis methods and theory, and graph algorithms for making information circulation healthier.
*Illustrative imageIdentifying Influencers
The lab studies methods for identifying, from social networks, the people who trigger the explosive spread of information. These include methods for finding them with only limited information and methods for identifying them with high accuracy using graph neural networks.
*Illustrative imageAnalyzing the Characteristics of Information Diffusion
The lab analyzes large-scale social media data to investigate universal characteristics of information diffusion. So far, it has examined how community structure and the sentiment polarity of posts affect the spread of information.
*Illustrative imageMethods for Curbing the Spread of Misinformation
This research aims to curb the spread of fake news and online abuse and defamation, and to make the flow of information healthier. The lab explores strategies for sending out corrective information and intervention methods that suppress spread, from the perspectives of both theory and data analysis.
MembersFaculty
The members of the Social Network Lab consist of faculty and doctoral, master's, and undergraduate students.As of 2026
- Associate ProfessorSho Tsugawa
VoicesStudent voices
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Report an errorAbout the images
The top and research theme images are illustrative and were not taken at the lab. They are cropped from Wikimedia Commons images. Cropped CC BY-SA images are provided under the same CC BY-SA license as the original (version shown on each line).
- Top image: “Social Media App Icons On The Screen of A Smartphone” mikemacmarketing / CC BY 2.0 (cropped)
- Identifying Influencers: “A starling murmuration at Galashiels - geograph.org.uk - 5991163” Walter Baxter / CC BY-SA 2.0 (cropped)
- Analyzing the Characteristics of Information Diffusion: “Network Visualization” Martin Grandjean / CC BY-SA 4.0 (cropped)
- Methods for Curbing the Spread of Misinformation: “CBC journalists in Montreal” Conrad Poirier / Public domain (cropped)
- Related lab (Machine Learning and Language Understanding Lab): “Chess game Staunton No. 6” Wilfredor / CC0 (cropped)
- Related lab (Computer Network Lab): “tower in fields in Punjab” Sahil Dhiman / CC BY-SA 4.0 (cropped)
- Related lab (Natural Language Processing Lab): “Numerical Keys on a Vintage Typewriter” Mathieu Landretti / CC BY-SA 4.0 (cropped)
- Related lab (Data Systems Engineering Lab): “3PAR SAN in the server room” Alexis Lê-Quôc from New York, United States / CC BY-SA 2.0 (cropped)
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