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Erschienen in:
2015 | OriginalPaper | Buchkapitel
Shared Task on Sentiment Analysis in Indian Languages (SAIL) Tweets - An Overview
verfasst von : Braja Gopal Patra, Dipankar Das, Amitava Das, Rajendra Prasath
Erschienen in: Mining Intelligence and Knowledge Exploration
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Abstract
Sentiment Analysis in Twitter has been considered as a vital task for a decade from various academic and commercial perspectives. Several works have been performed on Twitter sentiment analysis or opinion mining for English in contrast to the Indian languages. Here, we summarize the objectives and evaluation of the sentiment analysis task in tweets for three Indian languages namely Bengali, Hindi and Tamil. This is the first attempt to sentiment analysis task in the context of Indian language tweets. The main objective of this task was to classify the tweets into positive, negative, and neutral polarity. For training and testing purpose, the tweets from each language were provided. Each of the participating teams was asked to submit two systems, constrained and unconstrained systems for each of the languages. We ranked the systems based on the accuracy of the systems. Total of six teams submitted the results and the maximum accuracy achieved for Bengali, Hindi, and Tamil are 43.2 %, 55.67 %, and 39.28 % respectively.