Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Social Media is becoming major and popular technological platform that allows users discussing and sharing information. Information is generated and managed through either computer or mobile devices by one person and consumed by many other persons. Most of these user generated content are textual information, as Social Networks(Face book, Linked In), Microblogging(Twitter), blogs(Blogspot, Word press). Looking for valuable nuggets of knowledge, such as capturing and summarizing sentiments from these huge amount of data could help users make informed decisions. ,  develop a sentiment identification system called SES which implements three different sentiment identification algorithms.  augment basic compositional semantic rules in the first algorithm. In the second algorithm,  think sentiment should not be simply classified as positive, negative, and objective but a continuous score to reflect sentiment degree. All word scores are calculated based on a large volume of customer reviews. Due to the special characteristics of social media texts,  propose a third algorithm which takes emoticons, negation word position, and domain-specific words into account. Furthermore, a machine learning model is employed on features derived from outputs of three algorithms.  conduct our experiments on user comments from Face book and tets from twitter. The results show that utilizing Random Forest will acquire a better accuracy than decision tree, neural network, and logistic regression.  also propose a flexible way to represent document sentiment based on sentiments of each sentence contained. SES is available online.
['Kunpeng Zhang', 'Yu Cheng', 'Yusheng Xie', 'Daniel Honbo', 'Ankit Agrawal', 'Diana Palsetia', 'Kathy Lee', 'Wei-keng Liao', 'Alok N. Choudhary']
I am writing a research paper on a idea SES: Sentiment Elicitation System for Social Media Data
[{"from": "human", "value": "I am writing a research paper on a idea SES: Sentiment Elicitation System for Social Media Data"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Social Media is becoming major and popular technological platform that allows users discussing and sharing information. Information is generated and managed through either computer or mobile devices by one person and consumed by many other persons. Most of these user generated content are textual information, as Social Networks(Face book, Linked In), Microblogging(Twitter), blogs(Blogspot, Word press). Looking for valuable nuggets of knowledge, such as capturing and summarizing sentiments from these huge amount of data could help users make informed decisions. ,  develop a sentiment identification system called SES which implements three different sentiment identification algorithms.  augment basic compositional semantic rules in the first algorithm. In the second algorithm,  think sentiment should not be simply classified as positive, negative, and objective but a continuous score to reflect sentiment degree. All word scores are calculated based on a large volume of customer reviews. Due to the special characteristics of social media texts,  propose a third algorithm which takes emoticons, negation word position, and domain-specific words into account. Furthermore, a machine learning model is employed on features derived from outputs of three algorithms.  conduct our experiments on user comments from Face book and tets from twitter. The results show that utilizing Random Forest will acquire a better accuracy than decision tree, neural network, and logistic regression.  also propose a flexible way to represent document sentiment based on sentiments of each sentence contained. SES is available online."}]