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Beginner NLP Sentiment Dataset
Data Science and Analytics
Tags and Keywords
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"No reviews yet"
Free
About
This dataset contains 1,000 text reviews gathered from various restaurants, with each review clearly marked as either positive or negative. It has been created with beginners in mind, particularly for those delving into the fields of sentiment analysis and natural language processing (NLP). The dataset serves as an excellent starting point for understanding how to process and classify textual data.
Columns
- Unnamed: 0: An index or identifier for each individual review. This column can generally be disregarded for analytical purposes.
- sentence: This column holds the actual text content of the restaurant review itself.
- label: This indicates the sentiment associated with the review. A value of 1 signifies a positive review, while 0 denotes a negative review. There are 500 positive and 500 negative reviews within the dataset.
Distribution
The dataset is provided as a CSV (Comma-Separated Values) file, named
Beginner_Reviews_dataset.csv. It has a file size of approximately 66.84 kB. The dataset consists of 1,000 records or rows, with each row representing a single restaurant review and its corresponding sentiment label.Usage
This dataset is designed to be user-friendly for those new to data science. It can be utilised to train and evaluate sentiment analysis models, making it ideal for binary classification tasks. It is well-suited for educational purposes, assisting learners in developing skills in text preprocessing, feature extraction, and various classification algorithms within the NLP domain.
Coverage
The reviews included in this dataset originate from various restaurants, implying a global scope rather than a specific geographic region. There is no specific time range for the reviews themselves detailed in the provided information, nor any particular demographic focus beyond being restaurant reviews.
License
CC0
Who Can Use It
This dataset is primarily intended for beginners in sentiment analysis and natural language processing. It is suitable for:
- Students learning text analytics and machine learning.
- New practitioners looking for simple datasets to practise building classification models.
- Anyone interested in educational projects involving text data and sentiment classification.
Dataset Name Suggestions
- Restaurant Review Sentiment Analysis
- Beginner NLP Sentiment Dataset
- Food Review Opinion Data
- Simple Restaurant Sentiment Reviews
- Binary Restaurant Review Sentiment
Attributes
Original Data Source: ❤️ vs 😡: Sentiment Analysis 📝
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