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AI Driven Identification of Fake News Propagation in Twitter Social Media with Geo-Spatial Analysis

Published: 04 November 2021 Publication History

Abstract

With an explosion of online users over social media around the globe, we are no longer strangers to anything and anybody. With increased availability and exchange of information, the propagation of fake news and posts has also increased. Fake news refers to falsified versions of facts that get circulated among the general public to deliberately deceive people rapidly in the network. With the dawn of social networking, the dissemination of fake news has increased a lot due to share-ability, speed and lack of accountability. To address such problems on social media, we have presented an innovative geo-spatial detection mechanism for identifying fake news on Twitter. Our artificial intelligence based proposed strategy is implemented based on machine learning to improve accuracy for ensuring appropriate classification of news being posted on the social media platform so that online users may remain aware of getting duped by fake content.

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cover image ACM Other conferences
IC3-2021: Proceedings of the 2021 Thirteenth International Conference on Contemporary Computing
August 2021
483 pages
ISBN:9781450389204
DOI:10.1145/3474124
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 04 November 2021

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Author Tags

  1. Fake News
  2. Machine Learning
  3. Network Visualization
  4. Online Social Media
  5. Political Social Network
  6. Sentiment Analysis
  7. Twitter Science

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