Role of Natural Language Processing in Social Media
DOI:
https://doi.org/10.26438/ijcse/v5i12.287289Keywords:
Natural Language Processing, Social media, text summarization, sentiment analysis, Named Entity Recognition, Part-Of-Speech, TaggingAbstract
This paper highlight role of Natural Language Processing in social media sources like twitter, Facebook, LinkedIn etc. As now a day’s social media playing the vital role in terms of current trends social issues awareness etc. The major area where social media analysis requires is business analytics. As every business need the customer reviews and preferences for their business growth. This paper explains the major steps involved in social media mining.
References
Saranyamol C S, Sindhu L, “A Survey on Automatic Text Summarization”, International Journal of Computer Science and Information Technologies, 2014,Vol. 5 Issue 6.
Rafael Ferreira et al.“Assessing Sentence Scoring Techniques for Extractive Text Summarization”, Elsevier Ltd., Expert Systems with Applications 40 (2013)5755-5764
H. P. Luhn, "The automatic creation of literature abstracts”, IBM Journal of Research and Development, vol. 2, pp. 159-165, 1958.
John Selvadurai “A Natural Language Processing based Web Mining System for Social Media Analysis”, International Journal of Scientific and Research Publications, Volume 3, Issue 1, January 2013 ISSN 2250-3153.
The Stanford Natural Language Processing Group. (2012, Nov 15). Stanford Named Entity recognizer (NER) [Online].
P. Radha and R.Divya,” Extracting Information from Social Network using NLP”, International Journal of Computational Intelligence Research ISSN 0973-1873 Volume 13, Number 4 (2017), pp. 621-630
Surabhi Thorat,” Opinion Mining and Sentiment analysis- Its Tools and Challenges”, International Journal of IT, engineering and Applied Sciences Research (IJIEASR) ISSN: 2319-4413 Volume 3, No. 11, November 2014, pp. 12-15
Downloads
Published
How to Cite
Issue
Section
License

This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors contributing to this journal agree to publish their articles under the Creative Commons Attribution 4.0 International License, allowing third parties to share their work (copy, distribute, transmit) and to adapt it, under the condition that the authors are given credit and that in the event of reuse or distribution, the terms of this license are made clear.
