Dr Ning Wang
Ning Wang holds a joint position between the OII and Oxford's Mathematical Institute. His work involves in the collection and analysis of a big dataset tracking patterns of communication in online social networks.
Policy and Internet, the first major peer-reviewed multi-disciplinary journal investigating the impact of the Internet on public policy, is inviting submissions for a special issue on the development of social data science in China – the use of innovative data science tools, methods and big data in order to advance research on the Chinese Internet and society. The issue will be published in late 2015. The paper submission deadline is 1 March 2015.
There are over 600 million Chinese-language Internet users today, and increasing Chinese participation marks an important expansion and shift in the global network of the Web. Massive datasets that track the daily interactions of Internet users are relatively more accessible than ever before, and Chinese web data – including user-generated content, and data on user activity and behaviour – has attracted much attention from the political, academic, and commercial sectors. As the burgeoning field of data science expands to include the analysis of big data generated from the Web to understand the social world, it is increasingly important to incorporate methodological development, insight and comparative analysis from research communities across the world, particularly China.
Uncovering what the digital world reveals about online/offline interactions and collective dynamics requires researchers to operate at the intersection of cutting-edge methods to parse and manage large data sets; as well as to take into account privacy concerns and policies that regulate online behavior. Users of Chinese Web data – not only academic researchers but also industry and government institutions, both inside and outside China – have varied resources, expertise and purposes in creating, hosting, collecting, and analysing these data. They face a range of methodological, ethical and practical concerns and challenges regarding the intensive use (and misuse) of the data. This special issue will address how current research efforts navigate these issues, and the methods deployed to overcome limitations.
The issue responds to the need for an informed and broader discussion on the development of data science based on the Chinese Web, and what it reveals about large-scale social dynamics as well as microscopic patterns of interpersonal communication. This is an important and timely discussion not only for Chinese Internet researchers, but also for the larger audience of researchers and policy makers interested in using data science methods and web-based big data to understand the social world. While the Chinese Web represents an increasing share of the global web, it has received significantly less attention than Western services and online platforms in the growing field of social data science, or computational social science. This special issue aims to fill that gap.
We invite high quality empirical and evidence-based research articles that showcase the theoretical and methodological tools that are being applied to uncover the user, business, and policy practices around the Chinese Web. We welcome articles that discuss the peculiarities of Chinese data, the analytical approaches required to analyze online behavior, and the theoretical questions that those data and methods help tackle. The journal is fully multi-disciplinary in scope, and perspectives from any academic discipline are welcomed, provided that the papers consider the policy implications of the research discussed and are motivated by compelling questions.
Possible topics might include (but are not limited to):
The online submission deadline for papers is 1 March 2015. Please indicate in a cover note that the paper is intended for the special issue. Papers can be submitted though the journal’s online submission form. Authors are advised to consult the journal’s guide for authors before submitting their paper.
King-wa Fu (Ph.D.) is Assistant Professor at the Journalism and Media Studies Centre (JMSC), The University of Hong Kong. His research focuses on social media in China, political participation and media use, computational media studies, and mental health/suicide and the media, and statistics for journalism. He has a PhD from the JMSC, a MA in Social Sciences and an MPhil in Engineering from the Hong Kong University of Science and Technology. He was a journalist at the Hong Kong Economic Journal.
Min Jiang (Ph.D.) is Associate Professor of Communication at UNC Charlotte and an Affiliate Researcher at the Center for Global Communication Studies, University of Pennsylvania. Her research focuses on Chinese Internet technologies, politics, and policies. She has published nearly 20 journal articles, book chapters and conference proceedings. Her research has appeared in New Media & Society, Social Computer Science Review, Policy & Internet, Electronic Journal of Communication, and Information Visualization, among others. A recipient of over two dozen research grants, she has received funding from and presented her work at various institutions including the Social Science Research Council (SSRC), The University of Oxford, Harvard University, and University of Pennsylvania.
Ning Wang (Ph.D) works as a Researcher at the Oxford Internet Institute, University of Oxford. Prior to Oxford, he was a postdoctoral researcher at the Computer Laboratory, University of Cambridge. His work involves in using computational and Big Data approaches to analyse a wide range of sociotechnical problems. His research interests lie in the broad area of social computing, data mining, social networks analysis, Chinese Internet and social media, among others. He has been working recently on a range of projects on open data and civic engagement; big data for social science research; online activism; and using Twitter to map and measure online cultural diffusion. His research has appeared in Elsevier Journal of Social Networks, Entropy, etc.
Han-Teng Liao examines how geographic and linguistic factors (humanities and social science) and hyperlinked web data (webometrics and information science) shape the sense of “fellow users” in digital networked environments. With more than twelve years of combined information science, media/communication and open source/open data working experience, his focus has been on user-generated content and data, Web analytics (webometrics), Chinese Internet Research and integrated research designs (both qualitative and quantitative). He enjoys networking with professionals on the geographic and linguistic growth / dynamics / exchanges of the Internet. He holds an MSc in Computer Science and Information Engineering, an MA in Journalism, a BSc in Electrical Engineering and a BA in Foreign Languages and Literatures. At the Oxford Internet Institute, University of Oxford, his PhD project compares two Chinese user-contributed encyclopedias, Chinese Wikipedia and Baidu Baike.