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Movie Review Sentiment and POS Tagging
Entertainment & Media Consumption
Tags and Keywords
Trusted By
"No reviews yet"
Free
About
This dataset provides detailed linguistic analysis of film and television series reviews, capturing part-of-speech tags and the overall impact of each review on the audience. It offers a rich context for understanding how story descriptions relate to sentiment and provides granular data for natural language processing applications.
Columns
- MOVIES: The name of the movie or TV series.
- SENTENCE: Represents which sentence each word belongs to.
- tag: The part of speech for each individual word.
- word: Each individual word in a row.
- REVIEW: The impact of the review on the audience, indicating sentiment (e.g., POSITIVE or NEGATIVE).
Distribution
The dataset is typically provided in a CSV file format. Specific numbers for rows or records are not available in the provided information, but the structure includes columns for movie titles, sentences, words, part-of-speech tags, and review impact.
Usage
This dataset is ideal for various applications, including:
- Natural Language Processing (NLP) tasks such as sentiment analysis and part-of-speech tagging.
- Training machine learning models using frameworks like TensorFlow, LSTM, scikit-learn (Sklearn), and NLTK.
- Analysing audience perception and review impact for entertainment content.
- Developing tools for content analysis and understanding consumer feedback on movies and TV shows.
Coverage
The dataset's region coverage is global. Specific time ranges or demographic scopes are not detailed in the available information.
License
CC0
Who Can Use It
This dataset is suitable for:
- Data scientists and NLP researchers working on linguistic analysis and sentiment understanding.
- Machine learning engineers developing models for text classification and processing.
- Content analysts seeking insights into audience reception of entertainment media.
- Developers building applications that leverage AI and Large Language Model (LLM) data for consumer and product intelligence.
Dataset Name Suggestions
- movie_review_nltk
- Film Review Linguistic Analysis
- Movie Review Sentiment and POS Tagging
- Entertainment Review NLP Dataset
Attributes
Original Data Source: movie_review_nltk
QUALITY