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A Survey of Various Opinion Mining in Social Media

International Journal of Computer Science (IJCS) Published by SK Research Group of Companies (SKRGC)

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Abstract

Opinion Mining is a technique of providing and giving opinion on a particular topic so that a final conclusion can be extracted from it. Here in this paper a complete survey of all the technique that is used for the opinion mining. A complete survey of all the technique implemented for the social media opinion is discussed and analyzed here so that various advantages and limitations can be analyzed and hence on the basis of which a new and efficient technique can be implemented in future

References

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[3] Liaoruo Wang, Tiancheng Lou, Jie Tang and John E. Hopcroft “Detecting Community Kernels in Large Social Networks”, 2011
[4] Wayne Xin Zhao, Jing Jiang, Jianshu Weng, Jing He, Ee-Peng Lim, Hongfei Yan and Xiaoming Li, “Comparing Twitter and Traditional Media using Topic Models”, 2011
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[6] Liangjie Hong, Ovidiu Dan and Brian D. Davison “Predicting Popular Messages in Twitter”, ACM, 2011.
[7] Roja Bandari, Sitaram Asur and Bernardo Huberman, “The Pulse of News in So cial Media: Forecasting Popularity”, 2011.
[8] Phil Long and George Siemens “Penetrating the Fog: Analytics in Learning and Education”, Educause Review, 2011.
[9] Mattias Rost, Louise Barkhuus, Henriette Cramer and Barry Brown “Representation and Communication: Challenges in Interpreting Large Social Media Datasets”, ACM, 2013.
[10] Xin Chen, Mihaela Vorvoreanu and Krishna Madhavan, “Mining Social Media Data for Understanding Students’ Learning Experiences”, IEEE Transactions, 2014

Keywords

World Wide Web, Opinion Mining, WCM, WUM, Social Network.

Image
  • Format Volume 4, Issue 1, No 1, 2016.
  • Copyright All Rights Reserved ©2016
  • Year of Publication 2016
  • Author Jata Shankar Jha, Asst. Prof. Vimal Shukla
  • Reference IJCS-108
  • Page No 625-629

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