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Classification of Tweets Into Facts and Opinions Using Recurrent Neural Networks

Classification of Tweets Into Facts and Opinions Using Recurrent Neural Networks
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Author(s): Murugan Pattusamy (University of Hyderabad, India)and Lakshmi Kanth (University of Hyderabad, India)
Copyright: 2023
Volume: 19
Issue: 1
Pages: 14
Source title: International Journal of Technology and Human Interaction (IJTHI)
Editor(s)-in-Chief: Anabela Mesquita (ISCAP/IPP and Algoritmi Centre, University of Minho, Portugal)and Chia-Wen Tsai (Ming Chuan University, Taiwan)
DOI: 10.4018/IJTHI.319358

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Abstract

In the last few years, the growth rate of the number of people who are active on Twitter has been consistently spiking. In India, even the government agencies have started using Twitter accounts as they feel that they can get connected to a greater number of people in a short span of time. Apart from the social media platforms, there are an enormous number of blogging applications that have popped up providing another platform for the people to share their views. With all this, the authenticity of the content that is being generated is going for a toss. On that note, the authors have the task in hand of differentiating the genuineness of the content. In this process, they have worked upon various techniques that would maximize the authenticity of the content and propose a long short-term memory (LSTM) model that will make a distinction between the tweets posted on the Twitter platform. The model in combination with the manually engineered features and the bag of words model is able to classify the tweets efficiently.

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