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libimseti — Libimseti.cz dating ratings (2006)

Description

Ratings of user profiles by the users of LibimSeTi.cz, a Czech online dating website, as dumped on April 4, 2006. The data were provided by O. Neuberger (LibimSeTi.cz) and prepared by L. Brozovsky and V. Petricek (Charles University in Prague) for their study of recommender systems for online dating. Nodes are users, and a directed edge $i \to j$ is a rating of the profile of user $j$ by user $i$, on a scale from 1 to 10 (10 is best; integer ratings only).

The data contain 17,359,346 ratings of 168,791 profiles by 135,359 users; all 220,970 users rate or are rated. Only users who gave at least 20 ratings are included as raters, and users who gave constant ratings were excluded (by the source).

The network has the following properties:

  • (Node) gender: the gender of the user, F (female), M (male) or U (unknown).
  • (Edge) weight: the rating, from 1 to 10.
Tags
Social Online Weighted Metadata
Added
2020-08-11
Citation
Upstream URL OK
https://web.archive.org/web/20200901085122/http://www.occamslab.com/petricek/data/
Upstream license
Research use only; no redistribution without separate permission; no commercial use without permission from LibimSeTi.cz, https://web.archive.org/web/20200901085122/http://www.occamslab.com/petricek/data/
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
libimseti 220,970 17,359,346 78.56 483.96 943.38 6.29 -0.14 0.01 6 1.00 Directed Unipartite weight 35.5 MiB 84.7 MiB 80.9 MiB 72.5 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.