Characterizing and Countering Communal and Anti-Communal Tweets During Disasters
Archana K. S1, Latha M2, Sheela Gowr P3
1Archana K. S, UG student, Department of computer science and Engineering Vels Institute of science,Technology and Advanced Studies, Tamil Nadu, India.
2Latha M, Assistant Professor Department of computer science and Engineering Vels Institute of science,Technology and Advanced Studies, Tamil Nadu, India. |
3Sheela Gowr P, Assistant Professor Department of computer science and Engineering Vels Institute of science,Technology and Advanced Studies, Tamil Nadu, India.
Manuscript received on November 22, 2019. | Revised Manuscript received on December 15, 2019. | Manuscript published on December 30, 2019. | PP: 2174-2177 | Volume-9 Issue-2, December, 2019. | Retrieval Number: B3719129219/2019©BEIESP | DOI: 10.35940/ijeat.B3719.129219
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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: Various tweets shared during a disaster situation encompasses data related to current scenario and about emotions/opinions. By analyzing these communal tweets, abusive posts which targets various religiousandracial groups during natural calamities has been found. By reviewingits effects, a classifier has been developed to distinguish between communal and non-communalmessages, which shows better performance. People posting such communal tweets has been analyzed which says that most of them are posted by popular users from media, politicsand form strong correlated groups in the social network which makes it to reach higher. An event-independent classifier has been proposed whichidentifiesanti-communal tweets automatically and propose a way to counter back. A real-time service has been developed to find tweets automatically related to an emergency segregating communal and anti-communal tweets. Government and local monitoring agencies can use this system for making decisions like filtering or to promote some news.
Keywords: Tweets, Communal, Non-Communal, EventIndependent classifier.