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Sentiment analysis methods, applications, and challenges: A systematic literature review
With the expansion of Internet-based applications, the number of comments shows explosive growth. Analyzing the attitudes and emotions behind comments provides powerful assistance for businesses, governments, and scholars.
Yanying Mao, Qun Liu, Yu Zhang
doaj +1 more source
Sentiment analysis is a cornerstone in many contextual data analyses, from opinion mining to public discussion analysis. Gender bias is one of the well-known issues in sentiment analysis models, which can produce different results for the same text ...
Mohammad Reza Yeganegi +2 more
doaj +1 more source
The shift in human sentiments across cyberspace during a pandemic was unprecedented before COVID-19, as no prior pandemic had occurred alongside an interactive online environment. In response, we conducted a comprehensive bimodal longitudinal analysis of
Md. Saidul Hoque Anik +11 more
doaj +1 more source
A global twitter sentiment analysis model for COVID-vaccination. [PDF]
Chakrabarty D +2 more
europepmc +1 more source
EMSA: Explainable multilingual sentiment analysis models providing sentiment analysis across multiple languages. [PDF]
Zhao L, Zhou J, Cao J, Zhu W.
europepmc +1 more source
BABSA: A large scale bangla aspect based sentiment analysis dataset. [PDF]
Siam MFR, Wafa N.
europepmc +1 more source
Scientific reports multi relational dual attention graph transformer for fine grained sentiment analysis. [PDF]
Anilkumar AP, Kim SK, Yoon YC.
europepmc +1 more source
BERT based sentiment analysis of consumer hesitancy toward solar energy adoption. [PDF]
Jabbar A +3 more
europepmc +1 more source
BanglaMUSE: A multimodal Bangla sentiment dataset of text-audio pairs for speech and sentiment analysis. [PDF]
Nayeem MD +5 more
europepmc +1 more source

