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Reflections on authoritarianism in China, on Chinese-language Internet, and beyond.

In a nutshell, as democratic and civic practices have the potentials to spread across cultural-political boundaries online, authoritarian techniques and practices can be spread as well. Both methods and theories must be developed to, not only explain the often softer kind of authoritarian techniques (including “guiding public opinion”, see “Guidance of Public Opinion 舆论导向” and “State Media and Public Opinion on the HK Protests”), but also begin to contextualize the Chinese-language Internet (involving Hong Kong, Taiwan and overseas Chinese users) in their centripetal vs centrifugal relationship towards Beijing. After all, one of the major (but untested) assumption underlying the necessity for a party-state for China is that, it would be impossible to maintain an orderly, stable and unified country without Beijing and its current authoritarian techniques and practices.
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征文:《政策和互联网》特刊〈社会数据科学及中国/华文网络〉

政策和互联网》是研究互联网对公共政策冲击的第一份主要跨领域期刊。该刊计划于2015年下半年发布特刊〈社会数据科学及中国/华文网络〉讨论社会数据科学于中国及广大华文网络的发展,包括数据科学方法(如大数据)的创新使用以及能增进中国/华文网络研究方法。征稿面向世界各地,论文投稿仅限于英文,截稿日期为2015年3月1日。征稿完整英文原文详见:http://www.oii.ox.ac.uk/news/?id=1128

Some thesis chapters are now available at SSRN

My DPhil (PhD) thesis contains the following chapters, some of which can be downloaded at the Social Science Research Network (SSRN):

If you are interested in reading the substantial chapters (Chapter 4, Chapter 5, and Chapter 6), please contact me. Also, two additional files contain the remaining parts of the thesis:

 

Yes, I am on the market.

After successfully defending my PhD/DPhil and submitting revisions, I am “on the market” for academic or corporate opportunities that have substantial research components. Meanwhile, I will be finishing some publication work (including DPhil thesis and new/old collaboration work) within two or three months and continuing some academic duties using my spare time including this one for the special issue of Policy and Internet.

How to even out an uneven analytics of user-generated content: geolinguistic normalization as one possibility

In response to the “Uneven Geographies of User-Generated Information“, I argue that researchers and analysts must be explicit and transparent about the parameters of ideal “eveness”. Ideal evenness could be as simple as a sense of proportionality to the number of speakers, the number of Internet users, or the number of offline publications. Such sense of “evenness” provides essential and concrete baselines for online/offline, cross-country, and/or cross-language comparison. In a poster for the upcoming Opensym 2014, my coauthor and I propose one such possibility of using the number of language speakers across different countries (e.g. Arabic speaking population in Egypt, Israel, Kuwait, etc.) to showcase how the viewing and editing traffic is unevenly distributed.

In a nutshell, it is not surprising that Egypt and Saudi Arabia as major contributing country for reading and editing Arabic Wikipedia, but it is interesting to see, *per capita*(as defined here as per the number of Arabic language speakers for each region), smaller and yet more Internet-ready countries such as Israel, Kuwait, UAE, Bahrain, Qatar, Jordan, etc., contribute significantly more.

Normalized viewing traffic trend lines: Arabic Wikipedia

Normalized viewing traffic trend lines: Arabic Wikipedia

Normalized editing traffic trend lines: Arabic Wikipedia

Normalized editing traffic trend lines: Arabic Wikipedia

It is particularly interesting that Israel contribute the most *per-capita* viewing traffic to Arabic Wikipedia. The pilot findings however relies on the accuracy of the data on the number of speakers listed in “Language-Territory Information” compiled by the Unicode Consortium in CLDR version 25. Regardless, the proposed *per capita* metrics opens the doors not only for better and more detailed understanding of the “unevenness” of analytics of user-generated content, but also for more tangible baselines for our assumptions of “evenness”.

For pre-normalization results, please download the Opensym paper here or try the interactive infographics here

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