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Erschienen in:
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2019 | OriginalPaper | Buchkapitel

Context Sensitive Sentiment Analysis of Financial Tweets: A New Dictionary

verfasst von : Narges Tabari, Mirsad Hadzikadic

Erschienen in: Intelligent Methods and Big Data in Industrial Applications

Verlag: Springer International Publishing

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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.

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Vorheriges Kapitel To Improve, or Not to Improve; How Changes in Corpora Influence the Results of Machine Learning Tasks on the Example of Datasets Used for Paraphrase Identification
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Metadaten
Titel
Context Sensitive Sentiment Analysis of Financial Tweets: A New Dictionary
verfasst von
Narges Tabari
Mirsad Hadzikadic
Copyright-Jahr
2019
Buch
Intelligent Methods and Big Data in Industrial Applications

Print ISBN: 978-3-319-77603-3

Electronic ISBN: 978-3-319-77604-0

Copyright-Jahr: 2019

DOI
https://doi.org/10.1007/978-3-319-77604-0_26