Rumour Detection from Social Media : A Review

Authors(2) :-Shital Lathiya, M B Chaudhari

In this era, social media platform are increasingly used by people to follow newsworthy events because it is fast, easy to access and cheap comparatively. Despite the increasing use of social media for information and news gathering, its nature leads to the emergence and spread of rumours i.e., information that are unverified at the time of posting, which may causes serious damage to government, markets and society. Therefore, there is necessity of effective system for detecting rumours as early as possible before they widely spread. Effective system should consist of four components: Rumour detection, rumour tracking, stance classification, and veracity classification. Lots of work has been done in later component while very less work in component rumour detection. So, now we should work on rumour detection. In this paper, we will summarise efforts done till now in this area. Most of existing methods detects a priori rumours, i.e., predefined rumours. So it is required to have automated rumour detection method which detects new emerging rumours effectively and as early as possible.

Authors and Affiliations

Shital Lathiya
Student, Government engineering college, Gandhinagar, Gujarat, India
M B Chaudhari
Professor, Government engineering college, Gandhinagar, Gujarat, India

Rumour Detection, Rumour Classification, Misinformation, News Events, Social Media

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Publication Details

Published in : Volume 3 | Issue 7 | September-October 2018
Date of Publication : 2018-10-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 384-389
Manuscript Number : CSEIT183780
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Shital Lathiya, M B Chaudhari, "Rumour Detection from Social Media : A Review", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 7, pp.384-389, September-October-2018.
Journal URL : http://ijsrcseit.com/CSEIT183780

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