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.
翻译：感官分析在许多现实世界的应用中至关重要,例如姿态检测、审查分析、建议系统等等。当数据噪音时,从社交媒体收集的数据就变得更加困难。印度是一个多语言国家,人们使用多种语言进行交流。在不同社会媒体平台上收集的印地语-英语和孟加拉语-英语的代码混合数据对的情感分析共同任务由不同语言转换称为代码转换或代码混合。本文概述了从不同社会媒体平台上收集的印度语-英语和孟加拉语-英语的代码混合数据对的情绪分析共同任务。本文描述了任务、数据集、评估、基线和参与者系统。
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