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INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016 open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15 |
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| Paper Title: | Enhancing Sentiment Analysis with Hybrid Deep Learning Architectures |
| Authors Name: | Vikash Sawan , Durga Prasad Roy |
| Unique Id: | IJSDR2310109 |
| Published In: | Volume 8 Issue 10, October-2023 |
| Abstract: | Enhancing sentiment analysis on public opinion expressed in social networks, such as Twitter or Facebook, has been developed into a wide range of applications, but there are still many challenges to be addressed. Hybrid techniques have shown to be potential models for reducing sentiment errors on increasingly complex training data. This paper aims to test the reliability of several hybrid techniques on various datasets of different domains. Our research questions are aimed at determining whether it is possible to produce hybrid models that outperform single models with different domains and types of datasets |
| Keywords: | sentiment analysis; deep learning; Transformer; LSTM, SVM & ReLU. |
| Cite Article: | "Enhancing Sentiment Analysis with Hybrid Deep Learning Architectures", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.8, Issue 10, page no.661 - 672, October-2023, Available :http://www.ijsdr.org/papers/IJSDR2310109.pdf |
| Downloads: | 000338720 |
| Publication Details: | Published Paper ID: IJSDR2310109 Registration ID:208950 Published In: Volume 8 Issue 10, October-2023 DOI (Digital Object Identifier): Page No: 661 - 672 Publisher: IJSDR | www.ijsdr.org ISSN Number: 2455-2631 |
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