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--- |
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license: mit |
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task_categories: |
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- text-classification |
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language: |
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- en |
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pretty_name: s |
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size_categories: |
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- 10M<n<100M |
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--- |
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# Dataset Card for "Large twitter tweets sentiment analysis" |
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## Table of Contents |
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- [Dataset Description](#dataset-description) |
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- [Dataset Summary](#dataset-summary) |
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- [Languages](#languages) |
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- [Dataset Structure](#dataset-structure) |
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- [Data Instances](#data-instances) |
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- [Data Splits and Size](#data-splits-and-size) |
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## Dataset Description |
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### Dataset Summary |
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This dataset is a collection of tweets formatted in a tabular data structure, annotated for sentiment analysis. |
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Each tweet is associated with a sentiment label, with `1` indicating a Positive sentiment and `0` for a Negative sentiment. |
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### Languages |
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The tweets in English. |
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## Dataset Structure |
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### Data Instances |
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An instance of the dataset includes the following fields: |
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- `text`: a string containing the tweet's content. |
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- `sentiment`: an integer where `1` indicates Positive sentiment and `0` indicates Negative sentiment. |
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### Data Splits and Size |
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The dataset is divided into training and test sets. The sizes are as follows: |
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- Training set: 179995 instances |
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- Test set: 44999 instances |
