Sentiment Analysis of Code-Mixed Indian Languages: An Overview of SAIL_Code-Mixed Shared Task @ICON-2017
This work addresses sentiment analysis for multilingual social media users in India, but it is incremental as it focuses on organizing a shared task rather than introducing new methods.
The paper tackled sentiment analysis of code-mixed Hindi-English and Bengali-English data from social media, presenting an overview of a shared task that included dataset creation, evaluation, and baseline systems.
Sentiment analysis is essential in many real-world applications such as stance detection, review analysis, recommendation system, and so on. Sentiment analysis becomes more difficult when the data is noisy and collected from social media. India is a multilingual country; people use more than one languages to communicate within themselves. The switching in between the languages is called code-switching or code-mixing, depending upon the type of mixing. This paper presents overview of the shared task on sentiment analysis of code-mixed data pairs of Hindi-English and Bengali-English collected from the different social media platform. The paper describes the task, dataset, evaluation, baseline and participant's systems.