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文章基本信息

  • 标题:Social Media Based Behavior Prediction for Pakistan’s Peoples
  • 本地全文:下载
  • 作者:Nasir Amin ; Muhammad Awais ; Asad Cheema
  • 期刊名称:International Journal of Computer Science and Network Security
  • 印刷版ISSN:1738-7906
  • 出版年度:2018
  • 卷号:18
  • 期号:10
  • 页码:36-42
  • 出版社:International Journal of Computer Science and Network Security
  • 摘要:Behavior prediction from sentiment analysis is a field of Natural Language Processing which addresses the problem of extracting sentiment or, more generally, opinion from text. In this research paper specifically predict the behavior of the Pakistan’s peoples from tweeter datasets and sentiment polarity classification problem in Twitter aiming to classify messages based on the polarity of the sentiment towards behavior, where the tweets of behavior are extracted from twitter API. In the Methodology, implementation of machine learning models and experimental test to prove this research study. Machine learning models that are using in methodology are Random Forest Model (RFM), Decision Tree (DT) and Na?ve Bays (NB) classifier. It is also observed and compare the results as well as to improve the results by using the python that can never use before it for this research work.
  • 关键词:Social Media; Prediction; Behavior; PTA; CSV; Machine Learning; Sentiments
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