期刊名称：International Journal of Computer Science and Information Technologies
电子版ISSN：0975-9646
出版年度：2013
卷号：4
期号：4
页码：642-644
出版社：TechScience Publications
摘要：In today’s world there is significant role of knowing the emotions or the sentiment of the people for various social aspects like politics, war, products launched, elections and many more. But the task in our research work is to how to know and cluster that data which have been collected from various micro blogging sites and perform clustering analysis on tweets and know the sentiment of the people regarding certain topic. In this research paper we have done work on collecting data from various micro blogging sites like tweeter. We collect the tweets of various people and then create the score matrices based on tweets. By using these score matrices we can analyze that what are the opinion of the people regarding certain topic by applying clustering on tweets. For example if we are collecting topic regarding certain government policy. Then firstly we will collect the tweets of people that have tweeted regarding that topic and then we will cluster the similar tweets regarding that topic. From this clustered data we will find the similar words and then score them and create the score matrices based by using rule base engine on number of word that have occurred again and again in the tweets . A word that have occurred in the score matrices repeatedly depicts that what the people think about that thing such as if people are happy with that thing then the score of that particular word is high in the matrices. Using this technique we will we be efficiently able to know the sentiment of the people on various topic. It is also use full in commercial environment where the companies can know the opinion of the people based data collected from the micro blogging sites and can make changes to the product according to the needs of the people. In today’s worlds where everything is web based this technique will play important role in knowing the opinion of people on various social aspects.
