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Investigating the correlation between sentiment and stock-price fluctuations: Investigating the correlation between sentiment and stock-price fluctuations
Investigating the correlation between sentiment and stock-price fluctuations: Investigating the correlation between sentiment and stock-price fluctuations
This paper, seeks to examine the correlation between stock price and public sentiment expressed through social media. Through twitter scraping and pre- processing, sentiment can be extracted from text. The paper will be based on a heuristic approach to natural language processing. Furthermore, the paper will rely on the most common forms of sentiment analysis, using a rule-based and a machine-learning approach as a starting point and weigh these up against each other. Finally, we will continue with the best performing method, and weigh this up against real market data in a pursuit to find a correlation, should one exist. The paper found a sentiment-to-market accuracy 75%. And the accuracy score utilizing the rules-based approach of 72,72%.
- Roskilde University Denmark
EOSC: Twitter Data
Sentiment Analysis, space, web-scraping, NLP, Natural Language Processing, Tweepy
Sentiment Analysis, space, web-scraping, NLP, Natural Language Processing, Tweepy
EOSC: Twitter Data
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).0 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Average influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).0 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Average influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average
Popularity provided by BIP!- Roskilde University Denmark
This paper, seeks to examine the correlation between stock price and public sentiment expressed through social media. Through twitter scraping and pre- processing, sentiment can be extracted from text. The paper will be based on a heuristic approach to natural language processing. Furthermore, the paper will rely on the most common forms of sentiment analysis, using a rule-based and a machine-learning approach as a starting point and weigh these up against each other. Finally, we will continue with the best performing method, and weigh this up against real market data in a pursuit to find a correlation, should one exist. The paper found a sentiment-to-market accuracy 75%. And the accuracy score utilizing the rules-based approach of 72,72%.