A Tweet-based Dataset for Company-Level Stock Return Prediction

• URL: http://arxiv.org/abs/2006.09723v1
• Date: Wed, 17 Jun 2020 08:55:11 GMT
• Title: A Tweet-based Dataset for Company-Level Stock Return Prediction
• Authors: Karolina Sowinska and Pranava Madhyastha
• Abstract summary: We present a dataset that allows for company-level analysis of tweet based impact on one-, two-, three-, and seven-day stock returns. Our dataset consists of 862, 231 labelled instances from twitter in English, we also release a cleaned subset of 85, 176 labelled instances to the community.
• Score: 8.606705921815985
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: Public opinion influences events, especially related to stock market movement, in which a subtle hint can influence the local outcome of the market. In this paper, we present a dataset that allows for company-level analysis of tweet based impact on one-, two-, three-, and seven-day stock returns. Our dataset consists of 862, 231 labelled instances from twitter in English, we also release a cleaned subset of 85, 176 labelled instances to the community. We also provide baselines using standard machine learning algorithms and a multi-view learning based approach that makes use of different types of features. Our dataset, scripts and models are publicly available at: https://github.com/ImperialNLP/stockreturnpred.

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