Data Mining And Analysis In The Social Network

First of all, with the rapid development and innovation of Internet, we are surrounded by large index data. Every day a large number of data from the electronic commerce, science, social networks and other massive amounts of data are stored in the Internet and various kinds of data storage devices. Secondly, the development of mobile Internet promoted the development of the social network, We can use weibo,Twitter and other social networking platform to publish ourselves views, opinions and mood, Through social networks make our contacts more rich. we carry out data mining to realize topic detection and network monitoring of public opinion through the Wei Bo social platform of huge amounts of data. The purpose of extracting Wei Bo text is to ensure the stability and security of the society though monitoring the negative information and rumors. Data Mining can excavate interesting knowledge or pattern from clutter, amounts of data, having a positive role to ours economic,political and people's production and life.This article first briefly expounds how to use the crawler and Sina weibo API method fetching data. And then through the analysis of the social network platform of sina micro blog, puts forward the extension method based on the classification of weibo text. By analyzing the common algorithms we finally choose Single-Pass algorithms applied in weibo topic detection. Single- Pass algorithm relies heavily on text input sequence and sensitive to input order, in this article we improved it aiming at the shortcoming. Finally the improved algorithm is verified through the experiment and analysis, to improve the classification accuracy and efficiency.