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Elon Musk Tweets Sentiment
Data Science and Analytics
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Free
About
A collection of historical tweets from the @elonmusk account, compiled to enable detailed analysis of the user's tweeting history, patterns, and impact. Key features include the raw tweet text alongside computationally derived sentiment classifications and extracted user mentions, providing ready-to-use inputs for analytical models concerning technology, finance, and popular culture.
Columns
- Tweet Id: Unique identifier for each tweet.
- Datetime/Date: Timestamp of when the tweet was posted, covering the full history of posts.
- Text: The raw content of the tweet or reply.
- Username: The account from which the tweets were scraped (@elonmusk).
- location: The reported location of the user (consistently noted as Twitter HQ).
- reply count: The total number of replies the tweet received.
- retweet count: The total number of retweets the tweet received.
- like count: The total number of likes the tweet received.
- language: The dominant language of the tweet (mostly English).
- Twitter Access Point: The platform or device used to post the tweet (primarily Twitter for iPhone).
- Follower Count/Friends Count: User metrics at the time of compilation.
- verified: Boolean field confirming the account's verification status (True for all records).
- mentions: Any user accounts mentioned within the body of the tweet.
- sentiment: The dominant sentiment classification (e.g., neutral, positive, negative) as determined by the RoBERTa model.
Distribution
The dataset is typically provided in a tabular format, often CSV, and consists of 19 columns. It contains approximately 17.4 thousand validated records. The data is structured chronologically.
Usage
This dataset is highly useful for:
- Time series analysis, tracking tweet volume and sentiment changes over time.
- Advanced Natural Language Processing (NLP) model training and evaluation.
- Sentiment analysis related to specific business sectors like Automobiles, Vehicles, and Electronics.
- Academic research into the influence of high-profile figures on public discourse and market movements.
- Text mining and analysis of tweet content and recurring themes.
Coverage
The time range covered extends from June 2010 through to October 2022. The data focuses exclusively on a single user account, @elonmusk. The geographical scope is restricted to the location associated with this user, which is noted as Twitter HQ. The majority of the content is in English.
License
CC0: Public Domain
Who Can Use It
- Financial Analysts: Tracking sentiment signals that may correlate with changes in stock values related to the user’s enterprises.
- Academics and Data Scientists: Building and testing machine learning models for sentiment and topic modelling on high-impact social media data.
- Journalists and Media Researchers: Investigating communication strategies and engagement patterns of highly influential public figures.
Dataset Name Suggestions
- Elon Musk Tweets Sentiment
- @elonmusk Historical Data
- Musk Twitter NLP Corpus
- Classified Musk Tweets
Attributes
Original Data Source: Elon Musk Tweets Sentiment
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