Analysis on the User's Data of Tencent Micro-blog
Year: 2012
Type: article
Abstract: Based on data collected of Tencent Micro-blog,this paper proposes concept of the content's charm index of micro-blog,then uses Pearson and Spearman correlation coefficient to analyze relationship between number of listeners and number of users,and relationship between the content's charm index of and number of users.At last,the paper uses K-Means clustering algorithm to analyze characteristics of users.The conclusion is that content's charm index of micro-blog has moderate positive correlation with number of users.K-Means clustering classifies users into three types such as information-obtaining type,grassroots celebrities and ordinary social networking type.Thus,by optimizing algorithm and using content's charm index of micro-blog and result of clustering,service providers can reduce unnecessary recommendations of pages and application to meet needs of users so as to acquire commercial value.
Source: Journal of Intelligence
Author: Yue He
Institution: Sichuan University
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $3,137
OpenAlex ID: W2357504013