Predicting the Political Orientation of Facebook Users Based on Machine Learning Approach

碩士 === 國立臺北科技大學 === 電機工程系 === 106 === Online social networks have become more and more popular in recent years. They provide new platforms for users to exchange and share their information. This has resulted in rich research on predicting the personality traits of individuals from social media. This...

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Main Authors: Cheng-Hua Lin, 林政樺
Other Authors: 林敏勝
Format: Others
Language:zh-TW
Published: 2018
Online Access:http://ndltd.ncl.edu.tw/handle/j2t4j7
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spelling ndltd-TW-106TIT054410162019-07-04T05:59:56Z http://ndltd.ncl.edu.tw/handle/j2t4j7 Predicting the Political Orientation of Facebook Users Based on Machine Learning Approach 機器學習應用於預測臉書使用者 政治傾向之研究 Cheng-Hua Lin 林政樺 碩士 國立臺北科技大學 電機工程系 106 Online social networks have become more and more popular in recent years. They provide new platforms for users to exchange and share their information. This has resulted in rich research on predicting the personality traits of individuals from social media. This thesis proposes machine learning-based approaches to predict the users political orientation according to what fan pages theyve liked on Facebook. The experimental results show that (1) the prediction of political orientation on male dataset is more accurate than that on female dataset; (2) the traditional machine learning models perform well even with a small training dataset; (3) the deep learning models need to use a large dataset to get good prediction results. 林敏勝 2018 學位論文 ; thesis 39 zh-TW
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description 碩士 === 國立臺北科技大學 === 電機工程系 === 106 === Online social networks have become more and more popular in recent years. They provide new platforms for users to exchange and share their information. This has resulted in rich research on predicting the personality traits of individuals from social media. This thesis proposes machine learning-based approaches to predict the users political orientation according to what fan pages theyve liked on Facebook. The experimental results show that (1) the prediction of political orientation on male dataset is more accurate than that on female dataset; (2) the traditional machine learning models perform well even with a small training dataset; (3) the deep learning models need to use a large dataset to get good prediction results.
author2 林敏勝
author_facet 林敏勝
Cheng-Hua Lin
林政樺
author Cheng-Hua Lin
林政樺
spellingShingle Cheng-Hua Lin
林政樺
Predicting the Political Orientation of Facebook Users Based on Machine Learning Approach
author_sort Cheng-Hua Lin
title Predicting the Political Orientation of Facebook Users Based on Machine Learning Approach
title_short Predicting the Political Orientation of Facebook Users Based on Machine Learning Approach
title_full Predicting the Political Orientation of Facebook Users Based on Machine Learning Approach
title_fullStr Predicting the Political Orientation of Facebook Users Based on Machine Learning Approach
title_full_unstemmed Predicting the Political Orientation of Facebook Users Based on Machine Learning Approach
title_sort predicting the political orientation of facebook users based on machine learning approach
publishDate 2018
url http://ndltd.ncl.edu.tw/handle/j2t4j7
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