IIT Gandhinagar at SemEval-2020 Task 9: Code-Mixed Sentiment Classification Using Candidate Sentence Generation and Selection
Vivek Prakash Srivastava, Mayank Pratap Singh · 2020
Code-mixing is the phenomenon of using multiple languages in the same utterance of a text or speech.It is a frequently used pattern of communication on various platforms such as social media sites, online gaming, product reviews, etc. Sentiment analysis of the monolingual text is a well-studied task.Code-mixing adds to the challenge of analyzing the sentiment of the text due to the non-standard writing style.We present a candidate sentence generation and selection based approach on top of the Bi-LSTM based neural classifier to classify the Hinglish code-mixed text into one of the three sentiment classes positive, negative, or neutral.The proposed approach shows an improvement in the system performance as compared to the Bi-LSTM based neural classifier.The results present an opportunity to understand various other nuances of code-mixing in the textual data, such as humor-detection, intent classification, etc.