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http://hdl.handle.net/10263/7247
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DC Field | Value | Language |
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dc.contributor.author | Das, Dipayan | - |
dc.date.accessioned | 2022-01-24T07:08:57Z | - |
dc.date.available | 2022-01-24T07:08:57Z | - |
dc.date.issued | 2019 | - |
dc.identifier.citation | 37p. | en_US |
dc.identifier.uri | http://hdl.handle.net/10263/7247 | - |
dc.description | Dissertation under the supervision of Dr. Kuntal Ghosh | en_US |
dc.description.abstract | Social media has a great influence on our social life and extant literature finds that Twitter trends can capture the electoral sentiment. Twitter is a micro-blogging app, is the latest gift of globalization for social networking. We have gathered around 0.3 million tweets from 11 February 2019 to 31 March 2019 from the twitter accounts of about 200 political leaders belonging to the ruling as well as opponent parties. The research mainly aims to focus on social media data, data on political landscape, political inclination of different political groups, data mining of politically relevant tweets, data extraction with the help of Java and Twitter API. Several Graphs over different time periods have been generated based on a sense of their common contexts in the tweets during such periods. These contexts, in turn, identify the important events occurring during the same period. We have made two significant observations based on the above analysis. First, we found that the degree distributions of the generated graphs, each of whose nodes represent the political members only, during different periods corresponding to the events, follow power-law distribution. This result closely resembles real world complex network characteristics. Second, based on the data, it has been observed that with respect to such influential incidents like Pulwama explosion and killing or the Balakot airstrike when the ruling party was using, in their tweets, certain type of words related to the sensational events, the opposition parties’ tweet accounts show that such words were mostly absent and other words were more prevalent, a fact which may have crucial political significance in the context of the Indian General Election in determining which type of views on these issues may have played determining role in the final voting. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Indian Statistical Institute, Kolkata | en_US |
dc.relation.ispartofseries | Dissertation;2019:1 | - |
dc.subject | Indian General Election 2019 | en_US |
dc.title | Effects of Social Media in Indian Election | en_US |
dc.type | Other | en_US |
Appears in Collections: | Dissertations - M Tech (CS) |
Files in This Item:
File | Description | Size | Format | |
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DipayanDissertation.pdf | 1.06 MB | Adobe PDF | View/Open |
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