Predicting the Political Preference of Plurk Users

• Main Authors: Chiang, Chia Jung, 江家榕
• Other Authors: Chen, L. P.
• Format: Others
• Language: zh-TW
• Online Access: http://ndltd.ncl.edu.tw/handle/35786382886417136954

碩士 === 國立政治大學 === 資訊科學學系 === 103 === Nowadays, the use of social media is increasingly popular all over the world. People can easily express their thoughts or receive information that they are interested in via social media. Many studies have focused on exploring the predictive power of the large amount of data generated from social media. In this thesis, we address the problem of predicting the political preference of social media users given the data of their past activities on Plurk and evaluating our approach on the Taiwan 2012 presidential election. We first collected Plurk messages posted six months before the election day. By building predicting models based on a variety of contextual and behavioral features, we find that predicting political preference of active users achieved up to 94.08% classification accuracy. In the meanwhile, in order to extend the usability of our work, we further use our models to analyze the change of user political preference based on political events which happened before the election. Identifying people who change their political preference frequently or stay neutrally allows a candidate to design strategies to affect these people. All of the political events are automatically selected by the popularity of political keywords used in Plurk, and keywords can be extracted from daily political news. In the end, we get 208 swing voters from 275 voters, who become the main targets for enhancing the effectiveness of the campaign strategy.