Twitch Social Networks

Dataset information

These datasets used for node classification and transfer learning are Twitch user-user networks of gamers who stream in a certain language. Nodes are the users themselves and the links are mutual friendships between them. Vertex features are extracted based on the games played and liked, location and streaming habits. Datasets share the same set of node features, this makes transfer learning across networks possible. These social networks were collected in May 2018. The supervised task related to these networks is binary node classification - one has to predict whether a streamer uses explicit language.

MUSAE paper: arxiv.org
MUSAE Project: Github

Dataset statistics
	DE	EN	ES	FR	PT	RU
Nodes	9,498	7,126	4,648	6,549	1,912	4,385
Edges	153,138	35,324	59,382	112,666	31,299	37,304
Density	0.003	0.002	0.006	0.005	0.017	0.004
Transitvity	0.047	0.042	0.084	0.054	0.131	0.049

Possible tasks
Transfer learning
Binary node classification
Link prediction
Community detection
Network visualization

Source (citation)

B. Rozemberczki, C. Allen and R. Sarkar. Multi-scale Attributed Node Embedding. 2019.

          @misc{rozemberczki2019multiscale,
            title={Multi-scale Attributed Node Embedding},
            author={Benedek Rozemberczki and Carl Allen and Rik Sarkar},
            year={2019},
            eprint={1909.13021},
            archivePrefix={arXiv},
            primaryClass={cs.LG}
        }
        

Files

File	Description
twitch.zip	Twitch Social Networks