Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  focuses on performing Sentiment Analysis of Twitter by adapting data from other domains, commonly referred to as Domain Adaptation. While  show that Domain Adaptation is useful in predicting sentiments,  propose different techniques to select an out-of-domain data source that would aid in Sentiment Analysis. Additionally,  suggest two iterative algorithms based on Expectation-Maximization (EM) and Rocchio SVM that filter noisy data during adaptation and train only on valid data. Finally,  explore a couple of metrics, Mutual Information and Cosine distance to measure similarity beten different domains of data.  use Twitter and Blippr as data sources and perform binary sentiment (positive and negative sentiments) classification.
['Viswa Mani Kiran Peddinti', 'Prakriti Chintalapoodi']
I am writing a research paper on a idea Domain adaptation in sentiment analysis of Twitter
[{"from": "human", "value": "I am writing a research paper on a idea Domain adaptation in sentiment analysis of Twitter"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  focuses on performing Sentiment Analysis of Twitter by adapting data from other domains, commonly referred to as Domain Adaptation. While  show that Domain Adaptation is useful in predicting sentiments,  propose different techniques to select an out-of-domain data source that would aid in Sentiment Analysis. Additionally,  suggest two iterative algorithms based on Expectation-Maximization (EM) and Rocchio SVM that filter noisy data during adaptation and train only on valid data. Finally,  explore a couple of metrics, Mutual Information and Cosine distance to measure similarity beten different domains of data.  use Twitter and Blippr as data sources and perform binary sentiment (positive and negative sentiments) classification."}]