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Context Sensitive Sentiment Analysis of Financial Tweets: A New Dictionary

  • Narges Tabari
  • Mirsad Hadzikadic
Chapter
Part of the Studies in Big Data book series (SBD, volume 40)

Abstract

Sentiment analysis can make a contribution to behavioral economics and behavioral finance. It is concerned with the effect of opinions and emotions on economical or financial decisions. In sentiment analysis, or in opinion mining as they often call it, emotions or opinions of various degrees are assigned to the text (tweets in this case) under consideration. This paper describes an application of a lexicon-based domain-specific approach to a set of tweets in order to calculate sentiment analysis of the tweets. Further, we introduce a domain-specific lexicon for the financial domain and compare the results with those reported in other studies. The results show that using a context-sensitive set of positive and negative words, rather than one that includes general keywords, produces better outcomes than those achieved by humans on the same set of tweets.

Keywords

Sentiment analysis Twitter Financial sentiment analysis Lexicon 

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2019

Authors and Affiliations

  1. 1.UNC CharlotteCharlotteUSA

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