Sentimental Analysis using Capsule Network with Gravitational Search Algorithm
DOI:
https://doi.org/10.13052/jwe1540-9589.19569Keywords:
Deep Learning, Capsule Network, Machine Learning, Sentimental ClassificationAbstract
Day by day the recent development of communication and the data on the web is increasing tremendously. Moreover, the use of social media among people to express their opinion has greatly increased. Therefore, analyzing this textual data using sentimental analysis techniques can be very helpful in capturing and categorizing people’s opinions. This work aims to propose an algorithm which is combination of Capsule Network (CN) with Gravitational Search Algorithm (GSA) to analyze people’s sentiments from twitter data. In text data mining, CN works to an excessive extent for sentiment analysis compared with other models. The performance of the proposed approach is studied using existing benchmark datasets and COVID-19 twitter posts. The results showed that the proposed approach could automatically classify the sentiments with high performance. It works better compared to other algorithms and results also encourage further research.
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