twitter — Twitter followers (2009)
- Description
A directed network of following relationships on Twitter, collected by M. De Choudhury and collaborators with crawlers based on the Twitter API, as part of a data set of about 10.5 million tweets (from 2006 to 2009) of about 200,000 users. The social graph lists, for 2,502 crawled users, up to about 500 of the users they follow, so that almost all nodes have only incoming edges. A directed edge from $i$ to $j$ means that user $i$ follows user $j$ (the direction is not documented in the source, but is consistent with the users' profile counts). Repeated lines and 117 lines with an empty user name in the source file are left out.
The network has the following properties:
- (Node)
name: the Twitter user name. - (Node)
time_zone: the time zone set in the user's profile (empty if none). - (Node)
statuses,followers,friends,favourites: counts from the user's profile (-1 for the 9,205 users without profile data). The columns of the profile file are not documented; this assignment is inferred from the attributes listed in the source page and from the values (thefriendscount, i.e. the number of users followed, usually matches the number of out-edges of the crawled users).
- (Node)
- Tags
- Social Online Unweighted Metadata
- Added
- 2020-08-11
- Citation
-
- M. De Choudhury, Y.-R. Lin, H. Sundaram, K. S. Candan, L. Xie, A. Kelliher, "How does the data sampling strategy impact the discovery of information diffusion in social media?" Proceedings of the International AAAI Conference on Web and Social Media 4(1), 34-41 (2010) 10.1609/icwsm.v4i1.14024 Sci-Hub
- Upstream URL OK
- https://web.archive.org/web/20101201040745/http://www.public.asu.edu/~mdechoud/datasets.html
- Upstream license
- Creative Commons Attribution-NonCommercial 3.0 United States (CC BY-NC 3.0 US), https://creativecommons.org/licenses/by-nc/3.0/us/
- Networks
-
Tip: hover over a column header for a description.
Column legend
- $\left<k\right>$
- Mean degree
- $\sigma_k$
- Standard deviation of the degrees
- $\lambda_h$
- Largest eigenvalue of the Hashimoto (non-backtracking) matrix
- $\tau$
- Random walk mixing time
- $r$
- Degree assortativity
- $c$
- Global clustering coefficient
- $\oslash$
- (Pseudo-) diameter
- $S$
- Relative size of the largest component
- NPs
- Node properties
- EPs
- Edge properties
- Ridiculograms*
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