Overview of the shared task on code-mixed information retrieval from social media data

The rise of multilingual communication on social media platforms such as Facebook, Twitter, and WhatsApp presents a compelling challenge for information retrieval in code-mixed contexts within natural language processing.This paper provides an overview of the Code-Mixed Information Retrieval Shared Task, which is part of the FIRE-2024 conference.The main focus of this experiment was the evaluation of how relevant documents code-mixed from a corpus of Bengali-English comments were to be given for a set of code-mixed queries.Six teams showed interest in participating in the shared task; two teams provided their runs.This article describes the models used by the competing teams and their performance evaluated on the Mean Average Precision (MAP), a significant metric used for information retrieval tasks.