INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
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
"SENTIMENT CLASSIFICATION ACROSS MULTIPLE SOURCES USING AN INTEGRATED POLARITY-SCORE BASED EMBEDDING IN DEEP LEARNING MODEL", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.8, Issue 5, page no.j19-j31, May-2023, Available :http://www.ijnrd.org/papers/IJNRD2305918.pdf
Downloads:
000118749
ISSN:
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Facebook Twitter Instagram LinkedIn