Home // CLOUD COMPUTING 2021, The Twelfth International Conference on Cloud Computing, GRIDs, and Virtualization // View article

Detecting and Identifying Fake News on Twitter

Authors:
Lenna Nashif

Keywords: social media; misinformation; Covid-19

Abstract:
This paper delves into the profound impact of social media on relaying information, which is often stored and hosted in the cloud. The ability to differentiate between correct information and information that can be termed “misinformation” or “fake news” is integral for social media platforms. The spread of misinformation can lead to severe and possibly negative effects. To understand this further, this paper uses Big Data Analytics, often applicable in cloud computing, cross-referenced with reliable newspaper sources, to understand a tweet's validity in the context of the Covid-19 pandemic. Tweepy and TextBlob are Python libraries that are used to extract, derive sentiment analysis and subjectivity, and critically analyze the data for trends and implications in tweets. This analysis then is used to locate where the misinformation is spreading from. Through rigorous testing and verification, it becomes possible to determine and indicate in a simple and effective way which tweets are reliable and which are not. Implementing cloud storage to build this out on a larger scale opens up the exciting possibility of applying this method of locating fake news on Twitter to other trending topics, including elections, scientific discussions, and sporting events.

Pages: 37 to 40

Copyright: Copyright (c) IARIA, 2021

Publication date: April 18, 2021

Published in: conference

ISSN: 2308-4294

ISBN: 978-1-61208-845-7

Location: Porto, Portugal

Dates: from April 18, 2021 to April 22, 2021