Sentiment Detection Using Fish Optimization Genetic Algorithm
|International Journal of Engineering Trends and Technology (IJETT)||
|© 2020 by IJETT Journal|
|Year of Publication : 2020|
|Authors : Sukhlal Sangule, Dr. Sunil Phulre
|DOI : 10.14445/22315381/IJETT-V68I12P223|
MLA Style: Sukhlal Sangule, Dr. Sunil Phulre. Sentiment Detection Using Fish Optimization Genetic Algorithm International Journal of Engineering Trends and Technology 68.12(2020):140-145.
APA Style:Sukhlal Sangule, Dr. Sunil Phulre. Sentiment Detection Using Fish Optimization Genetic Algorithm International Journal of Engineering Trends and Technology, 68(12), 140-145.
Digital platforms are growing day by day, as people invest a large time in them. So human thoughts for any product, service, organization are easily available on this media platform. Analysis of user comments was done by text mining for understanding the status of any service or product. The sentiment of digital comments was extracted in the form of positive or negative class. This paper has proposed a Fish Optimization Genetic Algorithm for Sentiment Detection (FOGASD) in digital content. Collective Volitive and Feeding operator has increased the sentiment performance of work as well. Patterns are extracted from the input content, and as per the genetic algorithm, the output class was assigned to the patterns. The experiment was performed on a real amazon dataset having two sentiment classes. Results show that the proposed work has increased the evaluation parameter values as compared to another existing algorithm.
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Classification, Sentiment analysis, Ontology, Text Mining, Un-directed Classification.