Political Ideology Detection of News Articles Using Deep Neural Networks
نویسندگان
چکیده
Individuals inadvertently allow emotions to drive their rational thoughts predetermined conclusions regarding political partiality issues. Being well-informed about the subject in question mitigates emotions’ influence on humans’ cognitive reasoning, but it does not eliminate bias. By nature, humans tend pick a side based beliefs, personal interests, and principles. Hence, journalists’ leaning is defining factor rise of polarity news coverage. Political bias studies usually align subjects or controversial topics coverage particular ideology. However, politicians as private citizens public officials are also consistently media spotlight throughout careers. Detecting rather than adds new perspective. Determining best approach for detecting relies delivery method. Data types such videos, audio, text could summarize methods. Text one most prominent pattern recognition classification well-established research areas with applications many multidisciplinary domains. We propose use deep neural networks detect ideology articles that cover related officials, namely, President Obama Trump. Deep network models were able identify over 0.9 F1-Score. An evaluation analysis performance articles, articles’ authors, sources presented paper. Furthermore, this paper experiments provides detailed newly reconstructed datasets.
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ژورنال
عنوان ژورنال: Intelligent Automation and Soft Computing
سال: 2022
ISSN: ['2326-005X', '1079-8587']
DOI: https://doi.org/10.32604/iasc.2022.023914