Volume- 10
Issue- 2
Year- 2023
DOI: 10.55524/ijirem.2023.10.2.24 | DOI URL: https://doi.org/10.55524/ijirem.2023.10.2.24 Crossref
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0) (http://creativecommons.org/licenses/by/4.0)
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J Krishna Kishore , Jayasankar Sai Krishan, SK Arafath3, CH Ashok, K Nithin Reddy
Twitter, a popular social media platform, has become a rich source of user-generated content. The classification of Twitter users based on their characteristics and behavior has gained significant attention. Deep learning techniques, with their ability to capture complex patterns and representations, have emerged as powerful tools for Twitter user classification. This research article presents a comprehensive review of deep learning approaches for Twitter user classification. We discuss various deep learning architectures, pretraining techniques, and transfer learning strategies used in the classification task. Through a thorough analysis of existing studies, we highlight the strengths and limitations of deep learning approaches and provide recommendations for future research in this field.
Department of Computer Science &Engineering, PACE Institute of Technology & Sciences, Ongole, Andhra Pradesh, India
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