Online analyzing of texts in social network of Twitter

Abstract

Appearing social networks these days, the capacity of produced information has an increasing growing. The usual learning techniques don't have an efficient performance and the need of utilizing increasing learning methods is seen as a necessary factor. In mining the text in social networks we can see that text mining and social analyzing in texts are new topics in data analyzing which are considered as important factors growing very fast. Developing Microblogging sites like Twitter leads to make opportunities to make and applying some theories and technologies leading to mine and research trends. In this article we will evaluate Twitter the social network its characteristics and introducing and comparing data mining algorithms to online investigation on texting data. Researches show that stochastic gradient descent superior than other online evaluating techniques in analyzing text.