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Publication Type : Conference Paper
Publisher : 2018 International Conference on Advances in Computing, Communications and Informatics (ICACCI)
Source : 2018 International Conference on Advances in Computing, Communications and Informatics (ICACCI) (2018)
Keywords : Bengali-English languages, Bi-LSTM, CNN, code-mixed data, code-mixed Indian social media text, code-mixed Kannada-English sentiment analysis, Convolution, Deep learning, distributed representation methods, Doc2Vec, Facebook, Facebook comments, fastText, Hindi-English languages, Kannada-English code mixed corpus, learning (artificial intelligence), Linguistics, Machine learning, Neural networks, Online Social Networks, SAIL-2017, Sentiment analysis, sentiment analysis code-mixed corpus, Sentiment Analysis for Indian Languages-2017, Social networking (online), Task analysis, Training
Campus : Coimbatore
School : School of Engineering
Center : Computational Engineering and Networking, Electronics Communication and Instrumentation Forum (ECIF)
Department : Center for Computational Engineering and Networking (CEN), Electronics and Communication
Year : 2018
Abstract : The enormous number of user activity on online social networks results in a considerable amount of data which expresses the opinion from millions of people with diversity in their social aspects. The freedom of language usage shared through social media paves the way for the existence of code-mixed data that turns out to be more complex for mining the information out of it. Considering this, we created Kannada-English code mixed corpus by crawling Facebook comments. As of now, there is no relevant corpus as well as literature available for code-mixed Kannada-English sentiment analysis. In addition to the crawled corpus, we also used sentiment analysis code-mixed corpus provided by Sentiment Analysis for Indian Languages (SAIL)-2017 which includes Bengali-English and Hindi-English languages. This paper also addresses the performance of distributed representation methods in sentiment analysis task. We have reported comparisons among different machine learning and deep learning techniques.
Cite this Research Publication : K. Shalini, Ganesh, H. B., Anand Kumar M., and Dr. Soman K. P., “Sentiment Analysis for Code-Mixed Indian Social Media Text With Distributed Representation”, in 2018 International Conference on Advances in Computing, Communications and Informatics (ICACCI), 2018.