This is the sentiment analysis dataset based on IMDB reviews initially released by Stanford University. This is a dataset for binary sentiment classification containing substantially more data than previous benchmark datasets. We provide a set of 25,000 highly polar movie reviews for training, and 25,000 for testing. There is additional unlabeled data for use as well. Raw text and already processed bag of words formats are provided. See the README file contained in the release for more… See the full description on the dataset page: https://huggingface.co/datasets/scikit-learn/imdb.

Dataset

This dataset was created by Utathya Ghosh

Released under Database: Open Database, Contents: Database Contents

Contents

This dataset contains nearly 1 Million unique movie reviews from 1150 different IMDb movies spread across 17 IMDb genres - Action, Adventure, Animation, Biography, Comedy, Crime, Drama, Fantasy, History, Horror, Music, Mystery, Romance, Sci-Fi, Sport, Thriller and War. The dataset also contains movie metadata such as date of release of the movie, run length, IMDb rating, movie rating (PG-13, R, etc), number of IMDb raters, and number of reviews per movie.

The IMDb dataset is a collection of 50,000 reviews from the Internet Movie Database (IMDb). The reviews are labeled as either positive or negative and are split into two sets of 25,000 reviews for training and testing. Each set contains an equal number of positive and negative reviews.

The IMDb dataset is a binary sentiment analysis dataset for natural language processing or text analytics. It contains more data than previous benchmark datasets.

IMDb is a rich source of film data that includes cast and crew lists, movie release dates, box office information, plot summaries, trailers, actor and director biographies, and other trivia. Information on IMDb comes from a variety of sources, such as filmmakers, film studios, on-screen credits, and other official sources.

title.akas.csv

titleId (string) - a tconst, an alphanumeric unique identifier of the title ordering (integer) – a number to uniquely identify rows for a given titleId title (string) – the localized title region (string) - the region for this version of the title language (string) - the language of the title types (array) - Enumerated set of attributes for this alternative title. One or more of the following: "alternative", "dvd", "festival", "tv", "video", "working", "original"… See the full description on the dataset page: https://huggingface.co/datasets/labofsahil/IMDb-Dataset.

Context

This is the IMDB dataset exactly same as ImDb Movie Reviews Dataset, contains the movie reviews.

Content

The real dataset contains text files for training and testing purpose, but I created two csv files from those text files to ease the task ✌️ . Now you only need to download and apply your model. Each file contains 25000 reviews with label 0 for negative and 1 for positive. Each file has two columns 0 and 1, 0 represents reviews and 1 represents labels.

mteb/imdb dataset hosted on Hugging Face and contributed by the HF Datasets community

IMDB-MULTI is a relational dataset that consists of a network of 1000 actors or actresses who played roles in movies in IMDB. A node represents an actor or actress, and an edge connects two nodes when they appear in the same movie. In IMDB-MULTI, the edges are collected from three different genres: Comedy, Romance and Sci-Fi.

Dataset Card for IMDB-BINARY (IMDb-B)

  Dataset Summary

The IMDb-B dataset is "a movie collaboration dataset that consists of the ego-networks of 1,000 actors/actresses who played roles in movies in IMDB. In each graph, nodes represent actors/actress, and there is an edge between them if they appear in the same movie. These graphs are derived from the Action and Romance genres".

  Supported Tasks and Leaderboards

IMDb-B should be used for graph… See the full description on the dataset page: https://huggingface.co/datasets/graphs-datasets/IMDB-BINARY.

The IMDB Movie Details Dataset is a comprehensive collection of data about movies, TV shows, and streaming content listed on IMDB. It includes detailed information such as titles, release years, genres, cast, crew, ratings, and more. This dataset is ideal for data analysis, machine learning projects, and insights into the film and entertainment industry. Perfect for developers, researchers, and movie enthusiasts looking to explore trends and patterns in the world of cinema.

Dataset Card for IMDb Movie Dataset: All Movies by Genre

  Dataset Summary

This dataset is an adapted version of "IMDb Movie Dataset: All Movies by Genre" found at: https://www.kaggle.com/datasets/rajugc/imdb-movies-dataset-based-on-genre?select=history.csv. Within the dataset, the movie title and year columns were combined, the genre was extracted from the seperate csv files, the pre-existing genre column was renamed to expanded-genres, any movies missing a… See the full description on the dataset page: https://huggingface.co/datasets/jquigl/imdb-genres.

IMDB movie review sentiment classification dataset (Andrew L. Maas, Raymond E. Daly, Peter T. Pham, Dan Huang, Andrew Y. Ng, and Christopher Potts. (2011). Learning Word Vectors for Sentiment Analysis. The 49th Annual Meeting of the Association for Computational Linguistics (ACL 2011)). For more information please refer to: https://ai.stanford.edu/~amaas/data/sentiment/

The IMDB dataset was modified as follows to prepare it for use in a Galaxy Training Tutorial (https://training.galaxyproject.org/):

The top 50 words are excluded (mostly stop words). Included the next 10,000 top words. Reviews are limited to 500 words max (Longer reviews trimmed and shorter reviews are padded). 25,000 reviews are used for training and testing each. Files are in tsv (tab separated value) format to be consumed by Galaxy (www.usegalaxy.org).

AlignmentResearch/IMDB-test dataset hosted on Hugging Face and contributed by the HF Datasets community

IMDB-BINARY is a movie collaboration dataset that consists of the ego-networks of 1,000 actors/actresses who played roles in movies in IMDB. In each graph, nodes represent actors/actress, and there is an edge between them if they appear in the same movie. These graphs are derived from the Action and Romance genres.

IMDB movie/actor network - IMDB movie/actor network, www.imdb.com

We have cleaned the noisy IMDB-WIKI dataset using a constrained clustering method, resulting this new benchmark for in-the-wild age estimation. The annotations also allow this dataset to use for some other tasks, like gender classification and face recognition/verification. For more details, please refer to our FPAge paper.

Dataset

This dataset was created by Sharad Goel

Contents

Dataset

This dataset was created by simhyunsu

Contents

NoNONONONOO/imdb dataset hosted on Hugging Face and contributed by the HF Datasets community