Sentiment Analysis in Social Media with a Semantic Web Based Approach: Application to the French Presidential Elections 2017

  • Mohamed El Hamdouni
  • Hamza Hanafi
  • Adil Bouktib
  • Mohamed Bahra
  • Abdelhadi Fennan
Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 37)

Abstract

Sentiment Analysis is one of the recent fields that attracts the attention of many researchers to contribute in its improvement and to get the fruits of its applications. This paper presents a novel framework that aims to empower the sentiment analysis task by combining an unsupervised approach that relies on a lexicon-based strategy and domain ontologies to identify the sentiment of the textual content, and a visual sentiment ontology to analyze the emotions expressed by images, this hybrid method ensure the accuracy of results on data retrieved from social networks to get insights about the reaction of public towards a specific topic. The framework was put into test to analyze the data flowing in social networks during French elections 2017 to rank the candidates and detect the regions where they are leading and the results obtained were promising.

Keywords

Semantic web Ontology Sentiment analysis Twitter and Facebook APIs 

References

  1. 1.
    Abel, F., Geert-Jan Houben, C.H., Stronkman, R., Tao, K.: Twitcident: fighting fire with information from social web streams, pp. 305–308. ACM (2012)Google Scholar
  2. 2.
    Ereteo, G.: Analyse sémantique des réseaux sociaux. Autre [cs.OH]. Telecom ParisTech (2011)Google Scholar
  3. 3.
  4. 4.
    Medhata, W., Hassanb, A., Korashyb, H.: Sentiment analysis algorithms and applications: JIS Juin (2015)Google Scholar
  5. 5.
    Orsucci, F., Paoloni, G., Fulcheri, M., Annunziato, M., Meloni, C.: Smart communities: social capital and psycho-social factors in SmartCities (2012)Google Scholar
  6. 6.
    Developing Smart Cities Services through Semantic Analysis of Social Streams. ACM (2015)Google Scholar
  7. 7.
    Borth, D., Ji, R., Chen, T., Breuel, T., Chang, S.-F.: Large-scale Visual Sentiment Ontology and Detectors Using Adjective Noun PairsGoogle Scholar

Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Mohamed El Hamdouni
    • 1
  • Hamza Hanafi
    • 2
  • Adil Bouktib
    • 2
  • Mohamed Bahra
    • 2
  • Abdelhadi Fennan
    • 1
  1. 1.Faculty of Sciences and Technologies of Tangier, LIST LaboratoryAbdelmalek Essaadi UniversityTétouanMorocco
  2. 2.Faculty of Sciences and Technologies of TangierAbdelmalek Essaadi UniversityTétouanMorocco

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