A Novel Design Framework For Rumour Analysis in Twitter
P. Suthanthira Devi1, S. Karthika2

1P. Suthanthira Devi, Associate Professor, SSN College of Engineering, (Tamil Nadu), India.
2S. Karthika, Associate Professor, SSN College of Engineering, (Tamil Nadu), India.
Manuscript received on 22 April 2019 | Revised Manuscript received on 01 May 2019 | Manuscript Published on 07 May 2019 | PP: 23-26 | Volume-7 Issue-6S3 April 2019 | Retrieval Number: F1005376S19/2019©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: In social networking, a large amount of information can be disseminated to different social media users. Many times the social media users spread this information in unverified manner. The unverified information or misinformation is referred as rumors. Identifying source of rumor in a social media is a critical problem. Our main aim is to develop a rumor source detector, which will assist, in real time to determine the source of rumor in social media. In this paper the authors present, two methodologies to detect the source of rumor, first one is Graph Theoretical Framework and the second one is Veracity Assessment Framework. Graph Theoretical approach, the authors suggest to use regular trees, graphs and rumor centrality to estimate the source of the rumor. In Veracity Assessment framework, data coupled with real-time streaming and to understand the lifecycle of rumor. It is designed for automatically predicting rumor veracity at different time spans based on the conversation patterns.
Keywords: Rumor, Diffusion, Centrality, SIR, Ingest, Veracity, RSS.
Scope of the Article: Patterns and Frameworks