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Towards Rumors Detection Framework for Social Media

by Hadeer Sanaa, Nagy Ramadan, Hesham A. Hefny
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 177 - Number 31
Year of Publication: 2020
Authors: Hadeer Sanaa, Nagy Ramadan, Hesham A. Hefny
10.5120/ijca2020919780

Hadeer Sanaa, Nagy Ramadan, Hesham A. Hefny . Towards Rumors Detection Framework for Social Media. International Journal of Computer Applications. 177, 31 ( Jan 2020), 48-56. DOI=10.5120/ijca2020919780

@article{ 10.5120/ijca2020919780,
author = { Hadeer Sanaa, Nagy Ramadan, Hesham A. Hefny },
title = { Towards Rumors Detection Framework for Social Media },
journal = { International Journal of Computer Applications },
issue_date = { Jan 2020 },
volume = { 177 },
number = { 31 },
month = { Jan },
year = { 2020 },
issn = { 0975-8887 },
pages = { 48-56 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume177/number31/31101-2020919780/ },
doi = { 10.5120/ijca2020919780 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:47:25.879652+05:30
%A Hadeer Sanaa
%A Nagy Ramadan
%A Hesham A. Hefny
%T Towards Rumors Detection Framework for Social Media
%J International Journal of Computer Applications
%@ 0975-8887
%V 177
%N 31
%P 48-56
%D 2020
%I Foundation of Computer Science (FCS), NY, USA
Abstract

A Rumor is considered as unverified pieces of information circulating, that arise in the context of uncertainty, with negative impact, and falsely attributes. Unfortunately, terribly damaging form of communication are the results of rumors. Rumors spread on social media with no exception, and only serve to amplify the negative effects on people and businesses. This paper aims to present literature related to rumor detection on social network and try to find a link on how human behavior is affected by it. Therefore, it surveys the rumors detection frameworks, algorithms, and computational techniques that help in detecting and blocking rumors from spreading on social media. Also, attributes that may identify and describe a rumor and human behavior towards rumors are gathered, unified, and arranged in an integrated recommended list. This list of attributes may be the guide for detecting and capturing rumors with their changeable inconstant form. As a result, from this trial a proposed framework is presented to offer an idea for dealing with human behavior on rumors. This model presents open issues and forwarded ideas to provide an insight for future work in the area of building Rumor-Human Behavior computational models.

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Index Terms

Computer Science
Information Sciences

Keywords

Rumors Rumors attributes Human Behavior Social media rumors

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