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Sentiment analysis and Twitter: a game proposal

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Abstract

Pervasive sensing of people’s opinions is becoming critical in strategic decision processes, as it may be helpful in identifying problems and strengthening strategies. A recent research trend is to understand users’ opinions through a sentiment analysis of contents published in the Twitter platform. This approach involves two challenges: the large volume of available data and the large variety of used languages combined with the brevity of texts. The former makes manual analysis unreasonable, whereas the latter complicates any type of automatic analysis. Since sentiment analysis is a difficult process for computers, but it is quite simple for humans, in this article, we transform the sentiment analysis process into a game. Indeed, we consider the game with a purpose approach and we propose a game that involves users in classifying the polarity (e.g., positive, negative, neutral) and the sentiment (e.g., joy, surprise, sadness) of tweets. To evaluate the proposal, we used a dataset of 52,877 tweets, we developed a Web-based game, we invited people to play the game, and we validated the results through two different methods: ground-truth and manual assessment. The obtained results showed that the game approach is effective in measuring people’ sentiments and also highlighted that participants liked to play the game.

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Notes

  1. http://wing.comp.nus.edu.sg/SMSCorpus/

  2. http://www.mturk.com/mturk/

  3. http://www.felicitta.net

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Acknowledgments

The authors would like to thank the students who played the game and the ones who performed the ground-truth and the manual evaluation. The authors wish also to thank the anonymous referees that, with their comments, helped us to improve the readability and the quality of the paper.

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Authors and Affiliations

  1. Dipartimento di Comunicazione ed Economia, Universtà di Modena and Reggio Emilia, Viale Allegri 9, Reggio Emilia, 42121, Italy

    Marco Furini

  2. Dipartimento di Scienze Fisiche, Informatiche e Matematiche, Universtà di Modena and Reggio Emilia, Via Campi 213, Modena, 42121, Italy

    Manuela Montangero

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  1. Marco Furini
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  2. Manuela Montangero
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Correspondence to Marco Furini.

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Furini, M., Montangero, M. Sentiment analysis and Twitter: a game proposal. Pers Ubiquit Comput 22, 771–785 (2018). https://doi.org/10.1007/s00779-018-1142-5

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  • DOI: https://doi.org/10.1007/s00779-018-1142-5

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