Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/59173
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dc.contributor.authorNg, Bao Zhang
dc.date.accessioned2014-04-25T01:17:53Z
dc.date.available2014-04-25T01:17:53Z
dc.date.copyright2014en_US
dc.date.issued2014
dc.identifier.urihttp://hdl.handle.net/10356/59173
dc.description.abstractWith the increase usage of using Twitter over the years, more people are using this portal to voice out their opinions and suggestions to their friends. This platform has been utilised by the politicians who are taking part in the upcoming General Election, 16th Lok Sabha in India to interact and share information in Twitter with the general public. As Twitter plays an increasing important role in the political scene thus it should be taken into consideration as a valid source of data analysis during election period. The objective of this project is to aggregate tweets related to the politics in India by capturing related keywords and creating a repository for storing the tweets and for further analysis. Twitter‘s Streaming API is used for this project to retrieve ongoing tweets related to the keywords defined. It also allows an accurate data set for analysis as the tweets being extracted are the most recent data. A total number of 13 million tweets were collected during the period from 10th March 2014 to 17th March 2014. The data collected was based on the general terms used during the Election and name of the political parties. Tweets were extracted with the help of the Twitter search engine and are further classified based on the respective keywords and grouped together to form the base of the project findings. The data collated in this project have predicted that Indian National Congress is more likely to win more seats in this General Election among the 6 national parties due to the fact of having higher frequency count mentioned in the tweets collected. In conclusion, this project provides us with a clearer picture on how Twitter correlates with the political scene. However, further experiment can be done by using different analytical methods to provide for a more comprehensive prediction.en_US
dc.format.extent41 p.en_US
dc.language.isoenen_US
dc.rightsNanyang Technological University
dc.subjectDRNTU::Engineeringen_US
dc.titleIndian political Tweets aggregation and analysisen_US
dc.typeFinal Year Project (FYP)en_US
dc.contributor.supervisorAnwitaman Dattaen_US
dc.contributor.schoolSchool of Computer Engineeringen_US
dc.description.degreeBachelor of Engineering (Computer Science)en_US
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Appears in Collections:SCSE Student Reports (FYP/IA/PA/PI)
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