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digg_reply — Digg reply network (2008)

Description

A network of replies among users of the social news site Digg, collected by M. De Choudhury and collaborators with crawlers based on the Digg API. The data comprise stories on 56 topics, their comments, and the replies to these comments, written between late October and mid-November 2008. Each node is a Digg user, and a directed edge from $i$ to $j$ means that user $i$ replied to a comment by user $j$, with one edge per reply. Only replies to top-level comments included in the data are present (1,313 replies whose parent comment is not included are left out), and users replying to their own comments give self-loops.

The network has the following properties:

  • (Node) name: the Digg user name.
  • (Edge) time: the time of the reply (Unix time, from the date given in the data, whose time zone is not documented and is assumed to be UTC).
  • (Edge) story: the Digg id of the story on which the comment was made.
  • (Edge) comment: the Digg id of the comment that was replied to.
Tags
Social Online Unweighted Multigraph Timestamps
Added
2020-08-11
Citation
  • M. De Choudhury et al., "Social synchrony: Predicting mimicry of user actions in online social media." In Proc. Int. Conf. on Computational Science and Engineering (CSE '09), 151-158, (2009) 10.1109/cse.2009.439 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
Name Nodes Edges $\left<k\right>$ $\sigma_k$ $\lambda_h$ $\tau$ $r$ $c$ $\oslash$ $S$ Kind Mode NPs EPs gt GraphML GML csv
digg_reply 30,398 87,627 2.88 11.73 28.31 26.22 0.04 0.01 12 0.98 Directed Unipartite weight time 905 KiB 1.3 MiB 1.2 MiB 1.1 MiB
Ridiculograms*
* These are automatically generated force-directed visualizations, and can be quite meaningless for networks both big and small. They should not be taken seriously as sources of scientific insight. See here for a discussion.