Findings of Shared task on Sarcasm Identification in Code-Mixed Dravidian Languages

Sripriya N, Thenmozhi Durairaj, Nandhini K, Bharathi B, Kishore Kumar Ponnusamy, Charmathi Rajkumar, Prasanna Kumar Kumaresan, Rahul Ponnusamy, Subalalitha Chinnaudayar Navaneethakrishnan, Bharathi Raja Chakravarthi

Abstract: Identifying sarcasm in code-mixed languages presents a pivotal challenge within the domain of natural language processing, given the widespread use of multilingual and multicultural communication on social media platforms. This paper presents findings of the Sarcasm Identification shared task hosted as part of DravidianCodeMix@FIRE-2023. The principal objective of this task was to detect instances of sarcasm within a dataset of code-mixed comments in Tamil-English and Malayalam-English, collected from social media platforms. A total of 11 teams participated in this collaborative effort. This analysis provides a comprehensive assessment of the diverse models employed by the participating teams and the system’s performance was measured in terms of the macro-F1 score.