Please use this identifier to cite or link to this item: http://hdl.handle.net/11718/24631
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dc.contributor.advisorGupta, Samrat-
dc.contributor.authorDas, Manideepto-
dc.contributor.authorSingh, Priya-
dc.date.accessioned2021-11-24T11:48:01Z-
dc.date.available2021-11-24T11:48:01Z-
dc.date.issued2020-
dc.identifier.urihttp://hdl.handle.net/11718/24631-
dc.description.abstractWith the advent and increasing popularity of the internet, the spread of false information has become a growing issue worldwide, especially due to the ease with which information can be shared. The spread of false information has now become synonymous with the term “fake news”. Fake news refers to false or fabricated information disguised as authentic news which is very similar to news content when looked at and read. During the 2016 US presidential elections, the term fake news became increasingly common in Google searches in the US. Since then, the term has remained quite popular and attracts a lot of attention from researchers. (Allcott, 2017). Fake news not only creates a hurdle for people taking a decision but also, in some cases, brainwashes many people into believing things that are not good for society as a whole. Governments across the globe have recognized this risk.en_US
dc.language.isoenen_US
dc.publisherIndian Institute of Management Ahmedabaden_US
dc.subjectTwitteren_US
dc.subjectSEIZ epidemiological modelen_US
dc.subjectEpidemiologyen_US
dc.subjectHealthen_US
dc.titleCharacterizing spread of information on twitter using SEIZ epidemiological modelen_US
dc.typeStudent Projecten_US
Appears in Collections:Student Projects

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