IJSRSET calls volunteers interested to contribute towards the scientific development in the field of Science, Engineering and Technology

Home > IJSRSET151657                                                     


Trend Analysis on Social Networking using Opinion Mining : A Survey

Authors(2):

Saurin Dave, Prof. Hiteishi Diwanji
  • Abstract
  • Authors
  • Keywords
  • References
  • Details
The increasing popularity of social media in recent years has created new opportunities to study the interactions of different groups of people. Never before have so many data about such a large number of individuals been readily avail-able for analysis. Two popular topics in the study of social networks are community detection and finding trends. Sentiment Analysis (SA) is an ongoing field of research in text mining field. SA is the computational treatment of opinions, sentiments and subjectivity of text. Trend Analysis also sometimes interchange the term with the “Sentiment Analysis” (SA). The related fields to Sentiment Analysis (transfer learning, emotion detection, and building resources) that attracted researchers recently are discussed. The main target of this survey is to give nearly full image of SA techniques and the related fields with brief details. The main contributions of this paper include the sophisticated categorizations of a large number of recent articles and the illustration of the recent trend of research in the trend analysis and integration of community detection along with the sentiment analysis.

Saurin Dave, Prof. Hiteishi Diwanji

Trend Analysis, Sentiment Analysis, Opinion Mining, Text Mining, Emotion Detection

  1. Walaa Medhat, Ahmed Hassan, Hoda Korashy, “Sentiment analysis algorithms and applications: A Survey”. (27 May 2014), Volume 5, Issue 4, December 2014.
    http://dx.doi.org/10.1016/j.asej.2014.04.011
  2. Xing Fang* and Justin Zhan “Sentiment analysis using product review data” Journal of Big Data (2015) 2:5, DOI 10.1186/s40537-015-0015-2
  3. Zhengzhang Chen, William Hendrix, Nagiza F. Samatova, “Community-based anomaly detection in evolutionary networks”, © Springer Science+Business Media, LLC 2011
  4. Stephen Ranshous, Shitian Shen, Danai Koutra, Steve Harenberg, Christos Faloutsos3 and Nagiza F. Samatova, “Anomaly detection in dynamic networks: a survey”, Volume 7, May/June 2015, © 2015 The Authors. WIREs Computational Statistics published by Wiley Periodicals, Inc.

Publication Details

Published in : Volume 1 | Issue 6 | November-December - 2015
Date of Publication Print ISSN Online ISSN
2015-12-25 2395-1990 2394-4099
Page(s) Manuscript Number   Publisher
302-305 IJSRSET151657   Technoscience Academy

Cite This Article

Saurin Dave, Prof. Hiteishi Diwanji, "Trend Analysis on Social Networking using Opinion Mining : A Survey", International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 1, Issue 6, pp.302-305, November-December-2015.
URL : http://ijsrset.com/IJSRSET151657.php

IJSRSET Xplore

Subscribe

Conferences

National Conference on Advances in Mechanical Engineering 2017(NCAME 2017)

National Conference on Emerging Trends in Civil Engineering 2017( NCETCE 2017)