Sentiment Analysis of Persian Political tweets using Machine Learning Techniques

سال انتشار: 1400
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 260

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تاریخ نمایه سازی: 21 اردیبهشت 1401

چکیده مقاله:

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.


Mohammad Dehghani

Industrial and Systems Engineering, Tarbiat Modares University, Iran

Elham Akhondzadeh Noughabi

Industrial and Systems Engineering, Tarbiat Modares University, Iran