Sentiment Analysis of Persian Political tweets using Machine Learning Techniques
Publish place: Seventh international Conference on Knowledge and Technology of Mechanical, Electrical Engineering and Computer Of Iran
Publish Year: 1400
نوع سند: مقاله کنفرانسی
زبان: English
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شناسه ملی سند علمی:
DMECONF07_096
تاریخ نمایه سازی: 21 اردیبهشت 1401
Abstract:
Sentiment Analysis is a subfield of Natural Language Processing that has been extensively studied. Although Persian is the language of most modern information, the tools for processing it are limited. However, the ever-increasing impact of this task motivated this research to tackle it using Persian tweets. With the help of Iranian tweet datasets, we aim to predict polarity among tweets related to governance. We present the first study in this area of Persian tweets machine learning methods such as Decision Tree, Gradient Boosting, Random Forest and Support Vector Machines. With an accuracy of .۸۶, Random Forest had the best performance.
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Authors
Mohammad Dehghani
Industrial and Systems Engineering, Tarbiat Modares University, Iran
Elham Akhondzadeh Noughabi
Industrial and Systems Engineering, Tarbiat Modares University, Iran