0000000000640542

AUTHOR

Gautam Kishore Shahi

0000-0001-6168-0132

showing 2 related works from this author

An exploratory study of COVID-19 misinformation on Twitter.

2020

During the COVID-19 pandemic, social media has become a home ground for misinformation. To tackle this infodemic, scientific oversight, as well as a better understanding by practitioners in crisis management, is needed. We have conducted an exploratory study into the propagation, authors and content of misinformation on Twitter around the topic of COVID-19 in order to gain early insights. We have collected all tweets mentioned in the verdicts of fact-checked claims related to COVID-19 by over 92 professional fact-checking organisations between January and mid-July 2020 and share this corpus with the community. This resulted in 1 500 tweets relating to 1 274 false and 276 partially false cla…

FOS: Computer and information sciencesCoronavirus disease 2019 (COVID-19)Computer Networks and CommunicationsDiffusion of informationInternet privacyTwitterExploratory research02 engineering and technologyCrisis managementFalse accusationArticleSocial mediaComputer Science - Computers and SocietyOrder (exchange)Computers and Society (cs.CY)0202 electrical engineering electronic engineering information engineeringSocial mediaMisinformationSocial and Information Networks (cs.SI)business.industryCommunicationCOVID-19Computer Science - Social and Information Networks020206 networking & telecommunicationsExploratory analysisVDP::Samfunnsvitenskap: 200::Sosiologi: 220CoronavirusInformatikFake newsMisinformation020201 artificial intelligence & image processingPsychologybusinessInformation SystemsOnline social networks and media
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AMUSED: An Annotation Framework of Multi-modal Social Media Data

2020

In this paper, we present a semi-automated framework called AMUSED for gathering multi-modal annotated data from the multiple social media platforms. The framework is designed to mitigate the issues of collecting and annotating social media data by cohesively combining machine and human in the data collection process. From a given list of the articles from professional news media or blog, AMUSED detects links to the social media posts from news articles and then downloads contents of the same post from the respective social media platform to gather details about that specific post. The framework is capable of fetching the annotated data from multiple platforms like Twitter, YouTube, Reddit.…

Social and Information Networks (cs.SI)FOS: Computer and information sciencesComputer Science - Computation and LanguageComputer Science - Social and Information NetworksComputation and Language (cs.CL)Information Retrieval (cs.IR)Computer Science - Information Retrieval
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