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"Challenges and future in deep learning for sentiment analysis: a comprehensive review and a proposed novel hybrid approach"

Social media is used to categorise products or services, but analysing vast comments is time-consuming. Researchers use sentiment analysis via natural language processing, evaluating methods and results conventionally through literature reviews and assessments. However, our approach diverges by offe...

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Bibliographic Details
Main Authors: Islam, Md Shofiqul, Kabir, Muhammad Nomani, Ngahzaifa, Ab Ghani, Kamal Zuhairi, Zamli, Nor Saradatul Akmar, Zulkifli, Rahman, Md Mustafizur, Moni, Mohammad Ali
Format: Article
Language:English
English
Published: Springer Nature 2024
Subjects:
QA75 Electronic computers. Computer science
QA76 Computer software
T Technology (General)
TA Engineering (General). Civil engineering (General)
TJ Mechanical engineering and machinery
Online Access:http://umpir.ump.edu.my/id/eprint/41421/1/Challenges%20and%20future%20in%20deep%20learning%20for%20sentiment%20analysis.pdf
http://umpir.ump.edu.my/id/eprint/41421/2/Challenges%20and%20future%20in%20deep%20learning%20for%20sentiment%20analysis_A%20comprehensive%20review%20and%20a%20proposed%20novel%20hybrid%20approach_ABS.pdf
http://umpir.ump.edu.my/id/eprint/41421/
https://doi.org/10.1007/s10462-023-10651-9
https://doi.org/10.1007/s10462-023-10651-9
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Internet

http://umpir.ump.edu.my/id/eprint/41421/1/Challenges%20and%20future%20in%20deep%20learning%20for%20sentiment%20analysis.pdf
http://umpir.ump.edu.my/id/eprint/41421/2/Challenges%20and%20future%20in%20deep%20learning%20for%20sentiment%20analysis_A%20comprehensive%20review%20and%20a%20proposed%20novel%20hybrid%20approach_ABS.pdf
http://umpir.ump.edu.my/id/eprint/41421/
https://doi.org/10.1007/s10462-023-10651-9
https://doi.org/10.1007/s10462-023-10651-9

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