Abstract
Emotions are important in communication to effectively convey messages and to understand reactions to messages. Large scale studies of communication need methods to detect sentiment in order to investigate or model the processes involved. This chapter describes the sentiment strength detection program SentiStrength that was developed during the CyberEmotions project to detect the strength of sentiments expressed in social web texts. SentiStrength uses a lexical approach that exploits a list of sentiment-related terms and has rules to deal with standard linguistic and social web methods to express sentiment, such as emoticons, exaggerated punctuation and deliberate misspellings. This chapter also describes how SentiStrength can be refined for particular topics and contexts and how variants can be created for different languages. The chapter also briefly describes some studies that have applied SentiStrength to analyse trends in Twitter and You Tube comments.
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Acknowledgements
This work was supported by a European Union grant by the 7th Framework Programme, Theme 3: Science of complex systems for socially intelligent ICT. It is part of the CyberEmotions project (contract 231323).
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Thelwall, M. (2017). The Heart and Soul of the Web? Sentiment Strength Detection in the Social Web with SentiStrength. In: Holyst, J. (eds) Cyberemotions. Understanding Complex Systems. Springer, Cham. https://doi.org/10.1007/978-3-319-43639-5_7
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