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Reality Check for the Chinese Microblog Space: A Random Sampling Approach

Overview of attention for article published in PLOS ONE, March 2013
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Title
Reality Check for the Chinese Microblog Space: A Random Sampling Approach
Published in
PLOS ONE, March 2013
DOI 10.1371/journal.pone.0058356
Pubmed ID
Authors

King-wa Fu, Michael Chau

Abstract

Chinese microblogs have drawn global attention to this online application's potential impact on the country's social and political environment. However, representative and reliable statistics on Chinese microbloggers are limited. Using a random sampling approach, this study collected Chinese microblog data from the service provider, analyzing the profile and the pattern of usage for 29,998 microblog accounts. From our analysis, 57.4% (95% CI 56.9%,58.0%) of the accounts' timelines were empty. Among the 12,774 non-zero statuses samples, 86.9% (95% CI 86.2%,87.4%) did not make original post in a 7-day study period. By contrast, 0.51% (95% CI 0.4%,0.65%) wrote twenty or more original posts and 0.45% (95% CI 0.35%,0.60%) reposted more than 40 unique messages within the 7-day period. A small group of microbloggers created a majority of contents and drew other users' attention. About 4.8% (95% CI 4.4%,5.2%) of the 12,774 users contributed more than 80% (95% CI,78.6%,80.3%) of the original posts and about 4.8% (95% CI 4.5%,5.2%) managed to create posts that were reposted or received comments at least once. Moreover, a regression analysis revealed that volume of followers is a key determinant of creating original microblog posts, reposting messages, being reposted, and receiving comments. Volume of friends is found to be linked only with the number of reposts. Gender differences and regional disparities in using microblogs in China are also observed.

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Geographical breakdown

Country Count As %
China 2 2%
United Kingdom 1 1%
Germany 1 1%
Canada 1 1%
Unknown 87 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 21 23%
Student > Master 19 21%
Researcher 12 13%
Student > Doctoral Student 5 5%
Student > Postgraduate 5 5%
Other 15 16%
Unknown 15 16%
Readers by discipline Count As %
Social Sciences 31 34%
Computer Science 12 13%
Arts and Humanities 6 7%
Psychology 4 4%
Nursing and Health Professions 3 3%
Other 16 17%
Unknown 20 22%