Fundamentals of Sentiment Analysis: Concepts and Methodology

  • A. B. PawarEmail author
  • M. A. Jawale
  • D. N. Kyatanavar
Part of the Studies in Computational Intelligence book series (SCI, volume 639)


Internet has opened the new doors for information exchange and the growth of social media has created unprecedented opportunities for citizens to publicly raise their opinions, but it has serious bottlenecks when it comes to do analysis of these opinions. Even urgency to gain a real time understanding of citizens concerns has grown very rapidly. Since, the viral nature of social media which is fast and distributed one, some issues get rapidly distributed and unpredictably become important through this word of mouth opinions expressed online which in turn has known as sentiments of the users. The decision makers and people do not yet realized to make sense of this mass communication and interact sensibly with thousands of others with the help of sentiment analysis. To understand thoroughly use of sentiment analysis in today’s business world, this chapter covers the brief about sentiment analysis including introduction of sentiment analysis, early history of sentiment analysis, problems of sentiment analysis, basic concepts of sentiment analysis with mathematical treatment, sentiment and subjectivity classification comprises of opinion mining and summarization, past scenarios of opinion or sentiment collection and their analysis. Methodologies like Sentiment Analysis as Text Classification Problem, Sentiment analysis as Feature Classification with mathematical treatment are explored. Also, Economic consequences of sentiment analysis on individual, society and organization with the help of social media sentiment analysis are provided as supporting component.


Feature extraction Sentiment analysis Opinion mining 


  1. 1.
    Dalal, M.K., Zave, M.A.: Automatic text classification: a technical review. Int. J. Comput. Appl. (0975–8887) 28(2), 37–40 (2011)Google Scholar
  2. 2.
    Eirinaki, M., Pisal, S., Singh, J.: Feature-based opinion mining and ranking. J. Comput. Syst. Sci. 1175–1184 (2012)Google Scholar
  3. 3.
    Horrigan, J.A.: Online Shopping (2008)
  4. 4.
  5. 5.
  6. 6.
    Jawale, M.A., Dr., Kyatanavar, D.N., Pawar, A.B.: Design of automated sentiment or opinion discovery system to enhance its performance. In: Proceedings of International Conference on Advances in Information Technology and Mobile Communication 2013 and In: Journal of ACEEE 2013, pp. 48–53 (2013)
  7. 7.
    Jawale, M.A., Dr., Kyatanavar, D.N., Pawar, A.B.: Development of automated sentiment or opinion discovery system: review. In: Proceedings of ICRTET 2013 (2013)Google Scholar
  8. 8.
    Jawale, M.A., Dr., Kyatanavar, D.N., Pawar, A.B.: Implementation of automated sentiment discovery system. In: Proceedings of IEEE International Conference on Recent Advances and Innovations in Engineering (ICRAIE- 2014), pp. 1–6 (2014). ISBN: 978-1-4799-4041-7Google Scholar
  9. 9.
    Leong, C.K., Lee, Y.H., Mak, W.K.: Mining sentiments in SMS texts for teaching evaluation. In: Expert Systems with Applications, pp. 2584–2589 (2012)Google Scholar
  10. 10.
    Liu, B.: Sentiment analysis and subjectivity. In: Handbook of Natural Language Processing, 2nd edn. pp. 1–38 (2012)Google Scholar
  11. 11.
    Liu, B.: Sentiment analysis: a multi-faceted problem. In: IEEE Intelligent Systems, pp. 1–5 (2010)Google Scholar
  12. 12.
    Rainie, L., Horrigan, J.: Election 2006 online, Pew Internet & American Life Project Report, Jan 2007Google Scholar
  13. 13.
    Tang, H., Tan, S., Cheng, X.: A survey on sentiment detection of reviews. In: Science Direct, Expert Systems with Applications, pp. 10760–10773 (2009)Google Scholar
  14. 14.
    Yin, C., Peng, Q.: Sentiment analysis for product features in Chinese reviews based on semantic association. In: International Conference on Artificial Intelligence and Computational Intelligence, pp. 82–85 (2009)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • A. B. Pawar
    • 1
    Email author
  • M. A. Jawale
    • 2
  • D. N. Kyatanavar
    • 3
  1. 1.Department of Computer EngineeringS.R.E.S’, College of EngineeringKopargaonIndia
  2. 2.Department of Information TechnologyS.R.E.S’, College of EngineeringKopargaonIndia
  3. 3.Savitribai Phule Pune UniversityPuneIndia

Personalised recommendations