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Exploiting Emoticons to Generate Emotional Dictionaries from Facebook Pages

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Intelligent Decision Technologies 2016

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 57))

Abstract

During the first events of the Tunisian revolution, the social network, Facebook, played a key role in Tunisia and everywhere in the world. It became the first political tool that allows the Tunisian people to share trending news in actual time. Facebook provides the opportunity for users to comment on the news by expressing their sentiments. In this paper, we focus on emotion analysis of Tunisian Facebook pages. To do this, we first collect comments from the Facebook pages in order to analyze sentiments written in Tunisian dialect. Then, we propose a new method for emotional dictionaries construction. In fact, we distinguish nine emotional classes: surprised, satisfied, happy, gleeful, romantic, disappointed, sad, angry and disgusted. At this step, we focus on the use of emotion symbols as indicators of sentiment polarity. Finally, we present the experimental results of our method. Our system achieves effective and consistent results.

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Notes

  1. 1.

    http://wndomains.fbk.eu/wnaffect.html.

  2. 2.

    https://developers.facebook.com/docs/reference/apis/.

  3. 3.

    https://code.google.com/p/language-detection/.

References

  1. Abdul-Mageed, M., Diab, M.: Sana: a large scale multi-genre, multi-dialect Lexicon for Arabic subjectivity and sentiment analysis. In: Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC’14). ELRA, Reykjavik, Iceland (2014)

    Google Scholar 

  2. Alena, N., Helmut, P., Mitsuru, I.: Analysis of affect expressed through the evolving language of online communication. In: Proceedings of the 12th International Conference on Intelligent User Interfaces, pp. 278–281. ACM, New York, NY, USA (2007)

    Google Scholar 

  3. Ameur, H., Jamoussi, S.: Dynamic construction of dictionaries for sentiment classification. In: 13th IEEE International Conference on Data Mining Workshops. ICDM Workshops, pp. 896–903. TX, USA (2013)

    Google Scholar 

  4. Balabantaray, R.C., Mohammad, M., Sharma, N.: Article: Multi-class twitter emotion classification: a new approach. Int. J. Appl. Inf. Syst. 4(1), 48–53 (2012)

    Google Scholar 

  5. Diab, M., Albadrashiny, M., Aminian, M., Attia, M., Elfardy, H., Habash, N., Hawwari, A., Salloum, W., Dasigi, P., Eskander, R.: Tharwa: A large scale dialectal Arabic—standard Arabic—English Lexicon. In: Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC’14). ELRA, Reykjavik, Iceland (2014)

    Google Scholar 

  6. Douglas, R.R., Christopher, Z.: Corpus-based dictionaries for sentiment analysis of specialized vocabularies. In: New Directions in Analyzing Text as DataWorkshop (2013)

    Google Scholar 

  7. Duyu, T., Bing, Q., Ting, L., Zhenghua, L.: Learning sentence representation for emotion classification on microblogs. In: Natural Language Processing and Chinese Computing—Second CCF Conference, pp. 212–223. Chongqing, China (2013)

    Google Scholar 

  8. Ekman, P.: An argument for basic emotions. Cogn. Emot. 6, 169–200 (1992)

    Article  Google Scholar 

  9. Kamps, J., Marx, M.: Words with attitude. In: 1st International WordNet Conference, pp. 332–341. Mysore, India (2002)

    Google Scholar 

  10. Kim, S.M., Hovy, E.: Determining the sentiment of opinions. In: Proceedings of the 20th International Conference on Computational Linguistics. ACL, Stroudsburg, PA, USA (2004)

    Google Scholar 

  11. Mihalcea, R., Liu, H.: A corpus-based approach to finding happiness. In: Proceedings of the AAAI Spring Symposium on Computational Approaches to Weblogs (2006)

    Google Scholar 

  12. Mohammad, S.M.: Sentiment analysis: detecting valence, emotions, and other affectual states from text. In: Meiselman, H. (ed.) Emotion Measurement. Elsevier (2016)

    Google Scholar 

  13. Solakidis, G., Vavliakis, K., Mitkas, P.: Multilingual sentiment analysis using emoticons and keywords. In: 2014 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT), pp. 102–109. Warsaw, Poland (2014)

    Google Scholar 

  14. Taboada, M., Anthony, C., Voll, K.: Methods for creating semantic orientation dictionaries. In: Conference on Language Resources and Evaluation (LREC), pp. 427–432 (2006)

    Google Scholar 

  15. Wilson, T., Wiebe, J., Hoffmann, P.: Recognizing contextual polarity in phrase-level sentiment analysis. In: Proceedings of the Conference on Human Language Technology and Empirical Methods in Natural Language Processing, pp. 347–354. ACL, Stroudsburg, PA, USA (2005)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Multimedia InfoRmation Systems and Advanced Computing Laboratory, MIRACL-Sfax University, Sfax-Tunisia Technopole of Sfax, Av.Tunis Km 10 B.P. 242, 3021, Sfax, Tunisia

    Hanen Ameur, Salma Jamoussi & Abdelmajid Ben Hamadou

Authors
  1. Hanen Ameur
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  2. Salma Jamoussi
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  3. Abdelmajid Ben Hamadou
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Corresponding author

Correspondence to Hanen Ameur .

Editor information

Editors and Affiliations

  1. Gdynia Maritime University, Gdynia, Poland

    Ireneusz Czarnowski

  2. Artificial Intelligence Department, Universidad Politécnica de Madrid, Madrid, Spain

    Alfonso Mateos Caballero

  3. KES International, Shoreham-by-sea, UK

    Robert J. Howlett

  4. University of Canberra, Canberra, Australia

    Lakhmi C. Jain

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© 2016 Springer International Publishing Switzerland

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Ameur, H., Jamoussi, S., Ben Hamadou, A. (2016). Exploiting Emoticons to Generate Emotional Dictionaries from Facebook Pages. In: Czarnowski, I., Caballero, A.M., Howlett, R.J., Jain, L.C. (eds) Intelligent Decision Technologies 2016. Smart Innovation, Systems and Technologies, vol 57. Springer, Cham. https://doi.org/10.1007/978-3-319-39627-9_4

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  • DOI: https://doi.org/10.1007/978-3-319-39627-9_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-39626-2

  • Online ISBN: 978-3-319-39627-9

  • eBook Packages: EngineeringEngineering (R0)

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