General Information
    • ISSN: 1793-8201 (Print), 2972-4511 (Online)
    • Abbreviated Title: Int. J. Comput. Theory Eng.
    • Frequency: Quarterly
    • DOI: 10.7763/IJCTE
    • Editor-in-Chief: Prof. Mehmet Sahinoglu
    • Associate Editor-in-Chief: Assoc. Prof. Alberto Arteta, Assoc. Prof. Engin Maşazade
    • Managing Editor: Ms. Mia Hu
    • Abstracting/Indexing: Scopus (Since 2022), INSPEC (IET), CNKI,  Google Scholar, EBSCO, etc.
    • Average Days from Submission to Acceptance: 192 days
    • E-mail: ijcte@iacsitp.com
    • Journal Metrics:

Editor-in-chief
Prof. Mehmet Sahinoglu
Computer Science Department, Troy University, USA
I'm happy to take on the position of editor in chief of IJCTE. We encourage authors to submit papers concerning any branch of computer theory and engineering.

IJCTE 2013 Vol.5(3): 546-550 ISSN: 1793-8201
DOI: 10.7763/IJCTE.2013.V5.747

Analysis of the Temporal and Geographical Distribution of a Chinese Learning Website Visitors

Xiaochen Li and Yan Xu

Abstract—As China developing in a rapid step, there is a tremendous growing in the foreigners’ interest of learning Chinese and exploring the Chinese culture. Along with this, more and more foreigners choose the Internet as an access to Chinese learning resources. In this paper we process an important Chinese learning website’s Web logs and analyze the users’ distribution. Based on deep statistics and analysis, we propose several conclusions about the temporal and geographical distribution characteristics of the Chinese learning website visitors. For the temporal distribution, we observe an obvious pattern: (i) it’s a cyclic pattern with a period of one week, (ii)Thursday holds the peak of user numbers within a specific week, (iii) there is a downward trend of the user numbers per day during weekdays. For the geographical distribution of the users, we present experiments on two levels: (a) countries and regions ,(b) continents. Understanding the temporal and geographical distribution characteristics of Chinese learning website visitors brings us a better knowledge of the users’ preference and gives us pointers for research, so that we can improve the Chinese learning website and then attain a better adaption of the users’ habits and need.

Index Terms—Chinese learning, website usage, distribution of website visitors

The authors are with the College of Information Science, Beijing Language and Culture University, Beijing, 100083 China (e-mail: xcli@outlook.com, xuy@blcu.edu.cn).

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Cite:Xiaochen Li and Yan Xu, "Analysis of the Temporal and Geographical Distribution of a Chinese Learning Website Visitors," International Journal of Computer Theory and Engineering vol. 5, no. 3, pp. 546-550, 2013.


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