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股市推文 NLP

发布时间：2026-03-17 14:30:39资源ID：2032010427700252674资源类型：免费

该数据集《Stock Market TWEETS NLP》主要用于多分类任务，数据形态以文本为主，应用场景偏向文本内容分析。 题目说明：Stock Market TWEETS Labelled With GCP NLP 任务类型：文本多分类。 建议流程：先做文本清洗与分词，再比较 TF - IDF+线性模型 与 预训练语言模型。 评估建议：使用分层切分或交叉验证，优先关注 F1、Recall、AUC 等分类指标。 可用文件：Labelled Tweets.csv。 Context: Stock Market TWEETS Sentiment Analysis Data Set Overview: This is a data set of tweets related to the stock market. Dataset is derived from an existing dataset Stock Market TWEETS Data - NLP - 2021. In the original data set 943,9672 tweets are collected between April 9 and July 16, 2020, using the S&P 500 tag (#SPX500), the references to the top 25 companies in the S&P 500 index, and the Bloomberg tag (#stocks), However, In the original dataset, a total of 943,672 tweets are provided out of which only 1300 are labeled with the sentiment score which is a very small percentage.

股市推文 NLP

摘要概览

该数据集《Stock Market TWEETS NLP》主要用于多分类任务，数据形态以文本为主，应用场景偏向文本内容分析。 题目说明：Stock Market TWEETS Labelled With GCP NLP

任务类型：文本多分类。

建议流程：先做文本清洗与分词，再比较 TF - IDF+线性模型 与 预训练语言模型。

评估建议：使用分层切分或交叉验证，优先关注 F1、Recall、AUC 等分类指标。

可用文件：Labelled Tweets.csv。

Context:

Stock Market TWEETS Sentiment Analysis

Data Set Overview:

This is a data set of tweets related to the stock market. Dataset is derived from an existing dataset Stock Market TWEETS Data - NLP - 2021.

In the original data set 943,9672 tweets are collected between April 9 and July 16, 2020, using the S&P 500 tag (#SPX500), the references to the top 25 companies in the S&P 500 index, and the Bloomberg tag (#stocks), However, In the original dataset, a total of 943,672 tweets are provided out of which only 1300 are labeled with the sentiment score which is a very small percentage.