SENTIMENT CLASSIFICATION ACROSS MULTIPLE SOURCES USING AN INTEGRATED POLARITY-SCORE BASED EMBEDDING IN DEEP LEARNING MODEL

Registration ID: IJNRD_197515

Published ID: IJNRD2305918

: http://doi.one/10.1729/Journal.34906

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PARVATI KADLI, Dr. VIDYAVATHI B M

Convolutional neural network; cross-domain data; sentiment analysis; social media; Facebook; Twitter; Amazon; Tripadvisor.

The increasing prevalence of the Internet and the advent of Web 2.0 have led to a heightened focus on sentiment analysis of freely expressed opinions in different social media platforms. Sentiment analysis plays significant role in various applications such as review-based product recommendations and opinion mining. This study presents cross-domain-labeled Web sources (Amazon and Tripadvisor) in a unique cross-source cross-domain sentiment categorization approach. We propose a novel architecture named the Deep Learned Model with Integrated binary embedding. This model combines the strengths of Bidirectional Long-Short Term Memory (Bi-LSTM), Bi-Gated Recurrent Unit (GRU), and Convolutional Neural Network (CNN).. The proposed approach achieves an accuracy of over 80% in sentiment analysis of Facebook and Twitter datasets

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PARVATI KADLI & Dr. VIDYAVATHI B M (May-2023). SENTIMENT CLASSIFICATION ACROSS MULTIPLE SOURCES USING AN INTEGRATED POLARITY-SCORE BASED EMBEDDING IN DEEP LEARNING MODEL. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 8(5), j19-j31. http://doi.one/10.1729/Journal.34906

Volume 8 Issue 5, May-2023

Pages : j19-j31

Paper Reg. ID: IJNRD_197515

Published Paper Id: IJNRD2305918

Research Area: Computer Science & Technology 

Author Type: Indian Author

Country: HOSPET, VIJANAGARA DISTRICT, KARNATAKA, INDIA

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Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2305918

Crossref DOI: http://doi.one/10.1729/Journal.34906

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

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