movielens_ratings — MovieLens ratings (1995-2019)

Description

Bipartite networks of the users and movies of the online movie recommender service MovieLens, from the MovieLens data sets released by GroupLens Research (University of Minnesota) between 1998 and 2019. In each data set, the users were selected at random among those who had rated at least 20 movies, and their ids were anonymized. Each edge is the rating that a user gave to a movie (a user rates a movie at most once).

100k: MovieLens 100K (released in April 1998), 100,000 ratings of 1,682 movies by 943 users, on a scale from 1 to 5 stars, made between September 1997 and April 1998 (users who had less than 20 ratings or did not give complete demographic information were removed by GroupLens).
1m: MovieLens 1M (released in February 2003), 1,000,209 ratings of 3,706 movies by 6,040 users who joined MovieLens in 2000, on a scale from 1 to 5 stars, made between April 2000 and February 2003.
10m: MovieLens 10M (released in January 2009), 10,000,054 ratings of 10,677 movies by 69,878 users, made between January 1995 and January 2009, on a scale from 0.5 to 5 stars in half-star steps (whole stars only before February 2003).
20m: MovieLens 20M (released in October 2016), 20,000,263 ratings of 26,744 movies by 138,493 users, made between January 1995 and March 2015.
25m: MovieLens 25M (released in November 2019), 25,000,095 ratings of 59,047 movies by 162,541 users, made between January 1995 and November 2019.
20m_tags and 25m_tags: the tag applications of the 20M and 25M data sets (465,564 and 1,093,360), as bipartite networks of tags and movies, where each edge is one application of a tag (a free-text word or short phrase, case-sensitive) to a movie by a user, so that the same tag applied to the same movie by several users (or several times) gives multiple edges. Only the movies with at least one tag are included.

Each rating network contains all the movies listed in its data set, including those that only received tags (which have no edges). Left out are the "tag genome" relevance scores of the 20M and 25M data sets, the cross-validation splits of the 100K and 10M data sets, and the release dates and IMDb links of the 100K data set. The tags of the 10M data set are in the entry movielens_10m_tags, and the most recent data set (32M) is in the entry movielens_32m.

The networks have the following properties:

(Node) movie_id: the MovieLens id of the movie (-1 for the other nodes).
(Node) title: the title of the movie, including its year of release.
(Node) genres: the list of its genres (empty if none is listed).
(Node) imdb_id, tmdb_id (20m, 25m, 20m_tags and 25m_tags): the ids of the movie in IMDb and in The Movie Database (-1 if not given).
(Node) is_user (rating networks): whether the node is a user (otherwise a movie).
(Node) user_id (rating networks): the anonymized id of the user (-1 for movies).
(Node) gender, age, occupation, zip (100k and 1m): the demographic information given by the user (empty for movies); gender is "M" or "F". In 100k, age is the age in years; in 1m, it is the lower bound of the user's age group (1 for "under 18", 18, 25, 35, 45, 50 and 56 for "56+"). In both, -1 for movies.
(Node) is_tag (20m_tags and 25m_tags): whether the node is a tag (otherwise a movie).
(Node) name (20m_tags and 25m_tags): the tag string (empty for movies).
(Edge) rating (rating networks): the rating in stars.
(Edge) time: the time of the rating (rating networks), or when the tag was applied (20m_tags and 25m_tags), as Unix time.
(Edge) user (20m_tags and 25m_tags): the anonymized id of the user who applied the tag (the same as user_id in the rating network of the same data set).

Tags

Social Online Preferences Weighted Timestamps Metadata

Added

2026-10-28

Citation

F. M. Harper, J. A. Konstan, "The MovieLens Datasets: History and Context." ACM Transactions on Interactive Intelligent Systems 5(4), 19 (2015) 10.1145/2827872 Sci-Hub

Upstream URL OK

https://grouplens.org/datasets/movielens/

Upstream license

Restricted access. Upstream does not permit data redistribution, hence the network files cannot be downloaded without authorization. See here how to gain access.

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	$\left<k\right>$	$\sigma_k$	$\lambda_h$	$\tau$	$r$	$\oslash$	$S$	Kind	Mode	NPs	EPs	gt	GraphML	GML	csv
100k	2,625	100,000	76.19	91.07	170.13	2.29	-0.23	5	1.00	Undirected	Bipartite	is_user user_id gender age occupation zip movie_id title genres	rating time	447 KiB	775 KiB	738 KiB	646 KiB
1m	9,923	1,000,209	201.59	284.49	503.15	1.41	-0.28	6	0.98	Undirected	Bipartite	is_user user_id gender age occupation zip movie_id title genres	rating time	3.4 MiB	7.1 MiB	6.7 MiB	5.9 MiB
10m	80,559	10,000,054	248.27	965.93	1455.22	2.23	-0.33	6	1.00	Undirected	Bipartite	is_user user_id movie_id title genres	rating time	34.0 MiB	70.1 MiB	66.7 MiB	61.8 MiB
20m	165,771	20,000,263	241.30	1276.68	2007.38	2.23	-0.31	6	1.00	Undirected	Bipartite	is_user user_id movie_id title genres imdb_id tmdb_id	rating time	70.7 MiB	145.3 MiB	137.0 MiB	128.6 MiB
25m	224,964	25,000,095	222.26	1295.45	2177.72	4.24	-0.29	6	0.98	Undirected	Bipartite	is_user user_id movie_id title genres imdb_id tmdb_id	rating time	89.3 MiB	185.8 MiB	175.2 MiB	164.0 MiB
20m_tags	58,189	465,564	16.00	73.74	62.64	49.01	0.10	15	0.97	Undirected	Bipartite	is_tag name movie_id title genres imdb_id tmdb_id	user time	4.2 MiB	5.9 MiB	5.8 MiB	5.9 MiB
25m_tags	118,302	1,093,360	18.48	114.49	78.52	23.00	0.14	12	0.99	Undirected	Bipartite	is_tag name movie_id title genres imdb_id tmdb_id	user time	9.2 MiB	13.4 MiB	13.0 MiB	13.2 MiB