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Investor Reaction Crypto Dataset
Data Science and Analytics
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Free
About
This dataset provides insights into the social media reaction following a significant hack of a popular cryptocurrency exchange platform in September 2020. It allows for the analysis of how major events in the crypto world propagate through social media, offering a valuable resource for understanding investor behaviour and the broader market's response to critical situations. The dataset can be used to identify key developments within the crypto landscape by analysing public discourse.
Columns
- username: This column contains the username of the individual who authored the tweet.
- tweet_content: This column holds the actual content or body of the tweet.
- time: This column records the timestamp, formatted according to ISO standards, indicating when the tweet was published.
Distribution
The dataset is typically provided as a data file, commonly in CSV format. It comprises 3553 total records, with each record detailing the username, tweet content, and publishing timestamp. While the exact file size is not specified, the number of individual tweets is available.
Usage
This dataset is particularly well-suited for several applications:
- Text classification: Organising and categorising tweets based on their content.
- Analysis of investor's behaviour: Studying how investors react and communicate during high-stakes situations.
- Predicting exchange rates: When combined with cryptocurrency rates, the dataset can help forecast future exchange rates by observing the collective reaction of investors.
Coverage
The data covers tweets specifically related to the crypto hack that occurred in September 2020. Its regional scope is global. Specific details regarding demographic coverage or data availability for particular groups or years beyond the specified time frame are not provided.
License
CCO
Who Can Use It
This dataset is intended for a range of users, including those in data science and analytics. Ideal users and their potential applications include:
- Data scientists: For developing and refining text classification models and algorithms.
- Financial analysts: To gain an understanding of investor sentiment and its impact on the cryptocurrency market.
- Researchers: For studying social media propagation of news, crisis communication, and market psychology.
- Developers: For building applications that leverage Natural Language Processing (NLP) and text mining techniques related to financial topics.
Dataset Name Suggestions
- Tweets About Crypto Hack 2020
- Social Media Crypto Event Data
- Cryptocurrency Breach Tweets
- Investor Reaction Crypto Dataset
Attributes
Original Data Source: Tweets About Big Crypto Hack
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