Predicting U.S. Presidential Election through mining social media data. (Twitter)
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Authors
Gore, Palash
Issue Date
2016-04-01
Type
Presentation
Language
en_US
Keywords
Data analysis , Data mining , Presidential election , Social media
Alternative Title
Abstract
Data mining is a term that refers to extraction of knowledge or information hidden in large volumes of raw data. The purpose of this project is to predict the popularity of a candidate for US presidential election, 2016 form each state using social media for a given time interval [t1, t2], where t1 is the set of tweets observed between the timestamp t2. Until recently, political parties used information that limited pursing or reaching out to the masses which restricted the scope of a widespread campaign. The outcome of the project will help political parties make proper decision and target the right audience. This project is making use of twitter API which introduce simple concepts to analyze data. It will emphasize on techniques and considerations for mining large amount of data that is posted on twitter in real time.