Abstract
The World Wide Web has always been a huge repository for information. With this, an era of social networking came into existence that allowed people across the globe to connect and communicate with each other. The data present here is of various types like text, images, videos, audios, etc. The major part of the internet includes textual data which is written in different human-understandable languages. Recently, there has been tremendous increase in this data written in different languages over social media. This paper analyzes the semantic nature of a text, classifying them as either positive or negative for English, Hindi and Kannada languages. The following classification task is resolved with a CNN-LSTM-based neural network.
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Shetty, S. et al. (2022). Sentiment Analysis of Twitter Posts in English, Kannada and Hindi languages. In: Shetty D., P., Shetty, S. (eds) Recent Advances in Artificial Intelligence and Data Engineering. Advances in Intelligent Systems and Computing, vol 1386. Springer, Singapore. https://doi.org/10.1007/978-981-16-3342-3_29
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DOI: https://doi.org/10.1007/978-981-16-3342-3_29
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