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