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

被引：3

作者：

Garg, Amish ^{[1
]}

Shah, Tanav ^{[1
]}

Jain, Vinay Kumar ^{[1
]}

Sharma, Raksha ^{[1
]}

机构：

[1] Indian Inst Technol Roorkee, Dept Comp Sci & Engn, Roorkee, Uttar Pradesh, India

来源：

20TH IEEE INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND APPLICATIONS (ICMLA 2021) | 2021年

关键词：

Cryptocurrency; Bitcoin; NLP; Tweets; Dataset;

D O I：

10.1109/ICMLA52953.2021.00065

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Cryptocurrencies are gaining popularity day by day, and their analysis is a fascinating and demanding research topic. The average daily trading volume of Bitcoin was $67 billion in May 2021. A peculiar feature of cryptocurrencies is that they are not generally issued by a central authority, making them insusceptible to any governmental impedance. Cryptocurrency rates are closely related to news and influenced by tweets. However, no available dataset can analyze the crypto market adequately. We present CrypTopl2, a benchmark dataset for Cryptocurrency Price Movement Prediction based on tweets and historical prices. We collect over 576K tweets related to the top 12 cryptocurrencies, spanning over 1255 days and refine them to filter the tweets that are most relevant to price fluctuations. We also demonstrate use-cases by providing adapted baseline methods and a quantitative results analysis on our dataset.

引用

页码：379 / 384

页数：6

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