NLP in social Networking: An Overview

  IJCTT-book-cover
 
International Journal of Computer Trends and Technology (IJCTT)          
 
© 2017 by IJCTT Journal
Volume-54 Number-1
Year of Publication : 2017
Authors : Amit Kumar
DOI :  10.14445/22312803/IJCTT-V54P101

MLA

Amit Kumar "NLP in social Networking: An Overview". International Journal of Computer Trends and Technology (IJCTT) V53(1):1-3, December 2017. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.

Abstract -
Today social network is so popular. So Analysis in this area is so important .social Network analysis refers to the process of discover distributed structures through the use of network and graphs. All the information on the social network is unstructured and we have need to get the structured information that will helpful for making use of the important information. Natural language processing improve the accuracy in envisage the structured information that is speckled over social network. The basic overview of NLP and its technique are showing in this paper. This paper shows various text mining systems which is the foundation of NLP to analyze social network information.

References
[1] Bandyopadhyay, S. (Ed.). (2012). Emerging Applications of Natural Language Processing: Concepts and New Research: Concepts and New Research. IGI Global.
[2] Princeton University. (2012, Nov 10). WordNet: A Lexical database for English [Online]. Available: http://word net.princeton.edu/.
[3] Bandyopadhyay, S. (Ed.). (2012). Emerging Applications of Natural Language Processing: Concepts and New Research: Concepts and New Research. IGI Global.
[4] Agrawal R, Srikant R (1994) Fast algorithms for mining association rules. In: Proceedings of the 20th VLDB conference, pp 487–499.
[5] Aggarwal, C. C., & Zhai, C. (Eds.). (2012). Mining text data. Springer Science & Business Media.
[6] Bikel, D., & Zitouni, I. (2012). Multilingual natural language processing applications: from theory to practice. IBM Press pp 400.
[7] Xiang, R., Neville, J., & Rogati, M. (2010, April). Modeling relationship strength in online social networks. In Proceedings of the 19th international conference on World wide web (pp. 981-990). ACM.
[8] Louis, A. (2017). Natural Language Processing for Social Media.
[9] Liu, B. (2012). Sentiment analysis and opinion mining. Synthesis lectures on human language technologies, 5(1), 1-167.
[10] Kasemsap, K. (2016). Text Mining: Current Trends and Applications. Web Data Mining and the Development of Knowledge-Based Decision Support Systems, 338.
[11] Lin, J., & Dyer, C. (2010). Data-intensive text processing with Map Reduce. Synthesis Lectures on Human Language Technologies, 3(1), 1-177.
[12] M. Song and Y. Wu, Handbook of Research on Text and Web Mining Technology, Hershey, PA, USA: IGI Global, 2009, pp. 228.
[13] Gupta, V., & Lehal, G. S. (2009). A survey of text mining techniques and applications. Journal of emerging technologies in web intelligence, 1(1), 60-76.

Keywords
Natural Language Processing, distributed Network, Information Extraction, Text Mining.