Research And Analysis On The Influence Of Micro Blogging Users Based On Micro Blogging Data

In recent years, with the rapid development of the Internet, the influence of traditional media such as television, newspapers and radio has been gradually caught up with by new media from the internet. Internet has become the main channel that people used to send and receive information in the daily lives. As a fast developing new media on the Internet, micro blogging has accumulated hundreds of millions of users. The micro blogging platform contains a large amount of information and the update speed of the information is fast so that it often makes users could not find the information they need. It is important to help users find the information which was sent by people who have a great influence. Micro blogging content search system launched by micro blogging platform is a good way to help users find the micro blogging content from large amount of information. Traditional information retrieval system have three key factors which are relevant, authoritative and timeliness. The content of the micro blogging platform published and updated is very fast, and the content is not standardized, so that the timeliness and authoritativeness tend to be more important. The analysis of micro blogging users is also for researching the authoritative of users.In this paper, I study on micro blogging users’ influence by using micro blogging data, and the major achievements is as follows. The crawling of micro blogging data. In the beginning of my research, I crawled a large amount of micro blogging data from the micro blogging platform, including detailed information of the users, users’ concerned relationship, reply and repost relationship. These micro blogging data are the basis of my research of this paper and it can also be used as the basic data of other micro blogging relative research.The purpose of research on influence of micro blogging users in this paper is to identify the influence of different users in different areas. In this paper,I divided the users in different areas by using two different features which are the content of the micro blogging and the concerned relationship of the users. During this research, I also calculate the weight of the micro blogging users in different areas. The classification of the micro blogging users has high accuracy by some semi-automatic annotation sample validationDuring I did the text mining on the micro blogging content, I used the parallel new word recognition algorithm to recognition the new words in the micro blogging content and used the relative search of the searching engine to do semantic extensions on some important text feature. By using these, we solved a series of questions which are only belong to the micro blogging content such as text content is short, the features vector are sparse, and too many meaningless features.In this paper, I build a topic relative influence propagation model based on the reply and repost relationship between micro blogging users by using the users’ different classification weights in different areas. The propagation model has a good performance by doing some contrast experiment.