Title: Study on clustering of micro-blog business enterprise users reputation based on web crawler

Authors: Meiyu Fang; Qibei Lu

Addresses: School of Science and Technology, Zhejiang International Study University, Hangzhou, Zhejiang Province, China ' School of Science and Technology, Zhejiang International Study University, Hangzhou, Zhejiang Province, China

Abstract: Micro-blog is a social tool of the new network era. It swept the world with its convenience of usage and real-time release of information. PageRank and Hits algorithms are the most widely used method in the evaluation of micro-blog's influence. But the two algorithms have the deficiency of poor performance and unrelated to specified keywords. We proposed a micro-blog enterprise users' reputation analysis model based on clustering network and improved PageRank algorithm. The model was simulated with the Sina micro-blog data acquired by a web crawler, and the model was compared with Hits and PageRank algorithm. The results show that the model has better convergence and its computational efficiency is superior to the traditional evaluation model based on PageRank or Hits algorithm.

Keywords: web crawler; e-commerce; micro-blog.

DOI: 10.1504/IJCSM.2017.085729

International Journal of Computing Science and Mathematics, 2017 Vol.8 No.3, pp.279 - 290

Received: 01 Jul 2016
Accepted: 06 Dec 2016
Published online: 10 Aug 2017 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article