yelp_restaurants — Yelp users and restaurants (AllSet, 2021)

Description

A bipartite network of Yelp users and the restaurants they reviewed, compiled by Chien et al. from the Yelp Open Dataset (a subset of Yelp's businesses, reviews and users released by Yelp for academic use) as a benchmark for node classification. All businesses in Yelp's "Restaurants" category were selected, and each user is connected to the restaurants they reviewed (the compilers describe them as restaurants "visited by the same user"). Every user is connected to at least two restaurants. The restaurants are located in 459 cities and 16 states or provinces of North America; the identities of the users and businesses in the original data are not included, and the version of the Yelp Open Dataset that was used is not stated.

The network has the following properties:

is_user: whether the node is a user (otherwise it is a restaurant). Users are numbered in the order of their identifiers in the source data.
Restaurant nodes: name, the name of the restaurant; stars, the average star rating of the restaurant's reviews on Yelp, rounded to half stars (1.0 to 5.0); latitude and longitude, the location of the restaurant, in degrees (as given in the source; one restaurant has a positive longitude, probably a sign error); city, zipcode and state, integer codes for the city, postal code and state or province of the restaurant (the code tables are not available in the source data, so codes can only be compared for equality).
User nodes have empty or zero values for the restaurant properties.

Tags

Online Commerce Unweighted Metadata Spatial

Citation

E. Chien, C. Pan, J. Peng, O. Milenkovic, "You are AllSet: A Multiset Function Framework for Hypergraph Neural Networks." International Conference on Learning Representations (ICLR) (2022) openreview.net
Yelp, "Yelp Open Dataset." www.yelp.com

Upstream URL OK

https://github.com/jianhao2016/AllSet

Upstream license

Yelp Dataset Terms of Use, https://www.yelp.com/dataset

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
yelp_restaurants	730,060	4,523,594	12.39	52.54	127.97	37.35	-0.14	0.00	10	1.00	Undirected	Bipartite	is_user name stars latitude longitude city zipcode state		11.7 MiB	17.7 MiB	17.2 MiB	19.9 MiB