Emotion Analysis on Social Media: Natural Language Processing Approaches and Applications

  • Dipankar DasEmail author
  • Sivaji Bandyopadhyay
Part of the Lecture Notes in Social Networks book series (LNSN)


The rapidly growing online activities in the Web motivate us to analyze the reactions of different emotional catalysts on various social networking substrates. Thus, in the present chapter, different concepts, motivations, approaches and applications of emotion analysis are discussed in order to achieve the main challenging tasks such as feature representation schema, emotion classification, holder and topic detection and identifying their co-references, etc. as these are the main salient points to cover while analyzing emotions in social media. Additionally, a prototype is also described and assessed to analyze emotions, its collective actions based on users and topics, its components and their association from different available data sets of English and Bengali as case studies. Experiments and final outcomes highlight the promise of the approach and some open research problems.


Emotional Expression Natural Language Processing Conditional Random Field Discourse Marker Emotion Analysis 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The work reported in this paper was supported by a grant from the India-Japan Cooperative Programme (DSTJST) 2009 Research project entitled “Sentiment Analysis where AI meets Psychology” funded by Department of Science and Technology (DST), Government of India.


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© Springer-Verlag Wien 2014

Authors and Affiliations

  1. 1.Computer Science & Engineering DepartmentJadavpur UniversityKolkataIndia

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