Findings of the Sentiment Analysis of Dravidian Languages in Code-Mixed Text
This work addresses sentiment analysis for under-resourced Dravidian languages in code-mixed settings, but it is incremental as it builds on a previous shared task.
The paper presents results from a shared task on sentiment analysis for Dravidian languages in code-mixed text, with top systems achieving weighted average F1-scores of 0.711 for Tamil-English, 0.804 for Malayalam-English, and 0.630 for Kannada-English.
We present the results of the Dravidian-CodeMix shared task held at FIRE 2021, a track on sentiment analysis for Dravidian Languages in Code-Mixed Text. We describe the task, its organization, and the submitted systems. This shared task is the continuation of last year's Dravidian-CodeMix shared task held at FIRE 2020. This year's tasks included code-mixing at the intra-token and inter-token levels. Additionally, apart from Tamil and Malayalam, Kannada was also introduced. We received 22 systems for Tamil-English, 15 systems for Malayalam-English, and 15 for Kannada-English. The top system for Tamil-English, Malayalam-English and Kannada-English scored weighted average F1-score of 0.711, 0.804, and 0.630, respectively. In summary, the quality and quantity of the submission show that there is great interest in Dravidian languages in code-mixed setting and state of the art in this domain still needs more improvement.