A Review on Epidemiological Methods to Detect Untrue Information
Akanksha Mathur1, C.P Gupta2
1Akanksha Mathur, Professor, Department of Computer Science and Engineering, Engineering College Bikaner, Bikaner (Rajasthan), India.
2Prof. C. P. Gupta, Professor, Department of Computer Science and Engineering, Engineering College Bikaner, Bikaner (Rajasthan), India.
Manuscript received on August 26, 2021. | Revised Manuscript received on September 03, 2021. | Manuscript published on September 30, 2021. | PP: 16-19 | Volume-10 Issue-11, September 2021. | Retrieval Number: 100.1/ijitee.K945609101121 | DOI: 10.35940/ijitee.K9456.09101121
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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: Online propagation of untrue information has been and is becoming an increasing problem. Understanding and modeling the diffusion of information on Online Social Networks (OSN’s) of voluminous data is the prime concern. The paper provides the history of the epidemic spread and its analogy with untrue information. This paper provides a review of untrue information on online social networks and methods of detection of untrue information based on epidemiological models. Open research challenges and potential future research directions are also highlighted. The paper aimed at aiding research for the identification of untrue information on OSNs.
Keywords: Epidemics, Misinformation, Rumor Modelling, Social Networks.