Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: 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,  summarize the objectives and evaluation of the sentiment analysis task in tets for three Indian languages namely Bengali, Hindi and Tamil. This is the first attempt to sentiment analysis task in the context of Indian language tets. The main objective of this task was to classify the tets into positive, negative, and neutral polarity. For training and testing purpose, the tets from each language re provided. Each of the participating teams was asked to submit two systems, constrained and unconstrained systems for each of the languages.  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 43.2i¾?%, 55.67i¾?%, and 39.28i¾?% respectively.
['Braja Gopal Patra', 'Dipankar Das', 'Amitava Das', 'Rajendra Prasath']
I am writing a research paper on a idea Shared Task on Sentiment Analysis in Indian Languages SAIL Tweets - An Overview
[{"from": "human", "value": "I am writing a research paper on a idea Shared Task on Sentiment Analysis in Indian Languages SAIL Tweets - An Overview"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: 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,  summarize the objectives and evaluation of the sentiment analysis task in tets for three Indian languages namely Bengali, Hindi and Tamil. This is the first attempt to sentiment analysis task in the context of Indian language tets. The main objective of this task was to classify the tets into positive, negative, and neutral polarity. For training and testing purpose, the tets from each language re provided. Each of the participating teams was asked to submit two systems, constrained and unconstrained systems for each of the languages.  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 43.2i\u00be?%, 55.67i\u00be?%, and 39.28i\u00be?% respectively."}]