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- W4322731577 abstract "Even though sociolinguistic and psycholinguistic studies demonstrate that the qualities of the speaker and the intended audience have an impact on the message that is transmitted, the majority of NLP models used today assume language as universal. The difficulty of sentiment analysis, often known as opinion mining, in natural language processing (NLP) is one that is currently being faced. It’s also challenging for people to share their ideas on websites like Facebook, Twitter, and Yelp since innovation has grown dramatically. Social media’s widespread use has resulted in a huge volume of data generation, including evaluations, comments, and opinions. Researchers claim that the phrase, document, aspect, and user levels are the foundations for sentiment analysis. This data requires more time to analyse and is challenging to process. In order to categorize or determine positive, negative, and neutral opinions, an intelligent system must be developed." @default.
- W4322731577 created "2023-03-03" @default.
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- W4322731577 date "2022-11-25" @default.
- W4322731577 modified "2023-10-02" @default.
- W4322731577 title "Sentiment Analysis Approaches, Types, Challenges, and Applications: An Exploratory Analysis" @default.
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- W4322731577 doi "https://doi.org/10.1109/pdgc56933.2022.10053180" @default.
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