gxb912/large-twitter-tweets-sentiment
收藏资源简介：
--- 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
数据集卡片 for "Large twitter tweets sentiment analysis"
数据集描述
数据集概述
该数据集是格式化为表格结构的推文集合，用于情感分析。每个推文都与一个情感标签相关联，其中 1 表示正面情感，0 表示负面情感。
语言
推文为英语。
数据集结构
数据实例
数据集的一个实例包括以下字段：
text: 包含推文内容的字符串。sentiment: 一个整数，其中1表示正面情感，0表示负面情感。
数据分割和大小
数据集分为训练集和测试集。大小如下：
- 训练集：179995 个实例
- 测试集：44999 个实例
