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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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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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.
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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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