CrypTop12: A Dataset For Cryptocurrency Price Movement Prediction From Tweets And Historical Prices

This is the official repository for the release of the CrypTop12 dataset. If you would like to use our research, please cite the following:

A. Garg, T. Shah, V. K. Jain and R. Sharma, "CrypTop12: A Dataset For Cryptocurrency Price Movement Prediction From Tweets And Historical Prices," 2021 20th IEEE International Conference on Machine Learning and Applications (ICMLA), 2021, pp. 379-384, doi: 10.1109/ICMLA52953.2021.00065.

Feel free to reach us out at tanavshah@gmail.com if you have any queries and suggestions for us!

Overview

The dataset consists of two components: the historical prices and the tweets.

Number of Coins	Duration	Number of Days	Average Tweets
12	21/09/2017 to 27/03/2021	1255	38.28

Components

There are two main components:

Price

The price data is taken from CoinMarketCap.

The raw and preprocessed data for prices is organized as follows:

• ./price/raw
• ./price/preprocessed

Tweet

The tweet data is taken from Twitter.

The raw and preprocessed data for tweets is organized as follows:

• ./tweet/raw
• ./tweet/preprocessed

Data fields and format

Prices

• Date: Date of observation (YYYY-MM-DD)
• High: Highest price on the given date
• Low: Lowest price on the given date
• Open: Opening price on the given date
• Close: Closing price on the given date
• Volume: Volume of transactions on the given date
• Marketcap: Market capitalization in USD on the given date

For pre-processed version:

• We normalize Open, Close, High, Low as:

  • Normalized Price(t) = (Price(t) / Close Price(t - 1)) - 1

• We add an additional feature for movement percentage in the price dataset.

  • Movement%(t) = (Close Price(t) - Close Price(t - 1)) / Close Price(t - 1)

• We also remove the Marketcap attribute.

Tweets

• id: Tweet Id
• username: Username of account posting the given tweet
• created_at: Date-Time of posting of the given tweet
• tweet: Content of tweet in raw format
• replies_count: Count of replies to the given tweet
• retweets_count: Count of retweets to the given tweet
• likes_count: Count of likes to the given tweet
• Follower_count: Count of followers of the username

For pre-processed version:

• We use TweetTokenizer by NLTK for primary tokenization of each tweet.
• "AT_USER" prefix for the usernames mentioned in the tweet.
• "URL" for all the hyperlinks.
• "#" prefix for the hashtags.

Authors

• Amish Garg
• Tanav Shah
• Vinay Kumar Jain
• Prof. Raksha Sharma