An Analytical Approach to Customer Sentiments using NLP Techniques and Building a Brand Recommender Based on Popularity Score

Authors

  •   Sudesna Baruah Analyst, Tata Consultancy Services Ltd. Electronic City, Phase II, Bengaluru – 560 100
  •   Subhabaha Pal Senior Faculty, Data Science and Machine Learning with Manipal ProLearn (Manipal Academy of Higher Education – South Bangalore Campus), 3rd Floor, Salarpuria Symphony, 7, Service Road, Pragathi Nagar, Electronics City Post, Bengaluru – 560 100

DOI:

https://doi.org/10.17010/ijcs/2019/v4/i6/150421

Keywords:

Natural Language Processing

, Sentiment Analysis, Topic Modeling, LDA, VADER.

Manuscript Received

, November 11, 2019, Revised, November 19, Accepted, November 25, 2019. Date of Publication, December 5, 2019.

Abstract

Natural language processing (NLP) is a subfield of linguistics, computer science, information engineering, and artificial intelligence that is concerned with the interactions between computers and human (natural) languages, in particular how to program computers to process and analyze large amounts of natural language data.

This field has a great importance in many areas like retail stores and websites, social networking sites like Twitter, Facebook etc.; for understanding the various views or sentiments of the public or the consumers or end users, regarding a particular product or topic.

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Published

2019-12-31

How to Cite

Baruah, S., & Pal, S. (2019). An Analytical Approach to Customer Sentiments using NLP Techniques and Building a Brand Recommender Based on Popularity Score. Indian Journal of Computer Science, 4(6), 7–22. https://doi.org/10.17010/ijcs/2019/v4/i6/150421

Issue

Volume 4, Issue 6, November-December 2019

Section

Articles
Crossref
Scopus
Google Scholar
Europe PMC

References

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