yelp_reviews — Yelp reviewers of establishment categories (2005-2017)

Description

Bipartite networks of Yelp users and groups of users who reviewed establishments of the same category in the same month, compiled by Amburg, Veldt and Benson from the Yelp dataset distributed on Kaggle. The reviews of establishments of a given type in one city were split into month-long periods, and for each period and each establishment category (a Yelp sub-category, such as "Thai" or "Cocktail Bars") a group was formed with all users who reviewed an establishment of that category in that period; an edge connects each group to each of its users. Only groups with at least two users are included. The reviews span the years 2005 to 2017; the date of each group is not given in the data, and users are identified only by anonymous numbers.

madison: restaurants in Madison, Wisconsin, with ten cuisine categories (one of which, "Mongolian", has no group).
vegas: bars and nightlife establishments in Las Vegas, Nevada, with 18 categories (of which "Airport Lounges", "Tiki Bars" and "Wine Bars" have no group).

The networks have the following properties:

is_group: whether the node is a group of reviewers (otherwise it is a user).
User nodes: id, the number of the user in the source data (users that appear in no group are not included).
Group nodes: category, the establishment category reviewed by the group. The same set of users can appear in more than one group (in different months or categories).

Tags

Online Commerce Unweighted Metadata

Citation

I. Amburg, N. Veldt, A. R. Benson, "Diverse and Experienced Group Discovery via Hypergraph Clustering." Proceedings of the 2022 SIAM International Conference on Data Mining (SDM), 145-153 (2022) 10.1137/1.9781611977172.17 Sci-Hub
Yelp, "Yelp Dataset." Kaggle www.kaggle.com

Upstream URL OK

https://www.cs.cornell.edu/~arb/data/cat-edge-madison-restaurant-reviews/
https://www.cs.cornell.edu/~arb/data/cat-edge-vegas-bars-reviews/

Networks

Tip: click on a column header to sort the list, or hover over it 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
madison	1,166	4,601	7.89	7.25	13.99	12.67	-0.08	0.00	11	1.00	Undirected	Bipartite	is_group id category		9 KiB	18 KiB	17 KiB	18 KiB
vegas	2,428	11,865	9.77	11.02	24.18	57.77	-0.07	0.00	13	1.00	Undirected	Bipartite	is_group id category		19 KiB	42 KiB	42 KiB	46 KiB