NUIG-Shubhanker@Dravidian-CodeMix-FIRE2020: Sentiment Analysis of Code-Mixed Dravidian text using XLNet
This addresses sentiment analysis for multilingual social media users in Dravidian language communities, but is incremental as it applies an existing method to a specific data type.
The researchers tackled sentiment analysis on code-mixed Dravidian text (Tamil-English and Malayalam-English) by applying an XLNet model, achieving competitive performance on benchmark datasets.
Social media has penetrated into multilingual societies, however most of them use English to be a preferred language for communication. So it looks natural for them to mix their cultural language with English during conversations resulting in abundance of multilingual data, call this code-mixed data, available in todays' world.Downstream NLP tasks using such data is challenging due to the semantic nature of it being spread across multiple languages.One such Natural Language Processing task is sentiment analysis, for this we use an auto-regressive XLNet model to perform sentiment analysis on code-mixed Tamil-English and Malayalam-English datasets.