movie_review


The labeled dataset consists of 5000 IMDB movie reviews, specially selected
for sentiment analysis. The sentiment of the reviews is binary, meaning an
IMDB rating < 5 results in a sentiment score of 0, and a rating >=7 has a
sentiment score of 1. No individual movie has more than 30 reviews. Important
note: we removed non ASCII symbols from the original dataset to satisfy CRAN
policy.


datasets

Very fast and memory-friendly tools for text vectorization and
state-of-the-art word embeddings (GloVe). This package provides a
source-agnostic streaming API, which allows researchers to perform analysis
of collections of documents which are much larger than available RAM. All
core functions are parallelized to benefit from multicore machines.

Dmitriy Selivanov

text2vec

Fast Text Mining Framework for Vectorization and Word Embeddings

movie_review function

A data frame with 5000 rows and 3 variables: <dl>
  <dt>id</dt><dd>Unique ID of each review</dd>
 <dt>sentiment</dt><dd>Sentiment of the
  review; 1 for positive reviews and 0 for negative reviews</dd> <dt>review</dt><dd>Text of the review (UTF-8) </dd>
</dl>

Format

<a href="http://ai.stanford.edu/~amaas/data/sentiment/">http://ai.stanford.edu/~amaas/data/sentiment/</a>

movie_review: IMDB movie reviews

Description

Usage

Arguments

Format

Source