Please use this identifier to cite or link to this item:
http://hdl.handle.net/11718/24631
Title: | Characterizing spread of information on twitter using SEIZ epidemiological model |
Authors: | Das, Manideepto Singh, Priya |
Keywords: | Twitter;SEIZ epidemiological model;Epidemiology;Health |
Issue Date: | 2020 |
Publisher: | Indian Institute of Management Ahmedabad |
Abstract: | With 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. |
URI: | http://hdl.handle.net/11718/24631 |
Appears in Collections: | Student Projects |
Files in This Item:
File | Description | Size | Format | |
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SP_2912.pdf Restricted Access | 2.03 MB | Adobe PDF | View/Open Request a copy |
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