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.

Email: ning.wang@oii.ox.ac.uk
  • Profile
  • Research
  • Publications

Ning Wang (Ph.D) holds a joint position between the Oxford Internet Institute and the Mathematical Institute, University of Oxford. He works as Researcher at the Oxford Internet Institute and Senior Research Fellow in Data Science at the Oxford-NIE financial Big Data Lab. His research is driven by a deep interest in analysing a wide range of sociotechnical problems by exploiting big data approaches, with the hope that this work could contribute to the intersection of social behavior and computational systems.

He is also interested in the broad area of financial data analysis, machine learning , social computing, data mining, social networks analysis, Chinese Internet and social media, etc. He has been working on a range of projects including Forexmaster: mobile forex trading platform, Machine Learning in Time Series, “Big Vs” on Chinese microblog, Open Data and Civic Engagement, Big Data: Demonstrating the Value of the UK Web Domain Dataset, Leaders and Followers in Online Activism, Using Twitter to Map and Measure Online Cultural Diffusion, etc. His research has appeared in Elsevier Journal of Social Networks, Data Science, Entropy, etc.

Prior to Oxford, he was a postdoctoral researcher at the Computer Laboratory, University of Cambridge. He worked on the Social-based Forwarding Algorithm. He was involved in research to analyse a large number of real-world data on social networks in an effort to use centrality and community structure to optimise online communications.

He is also guest editor of a forthcoming Policy and Internet journal special issue of Chinese Web Data, program chair of the 14th IEEE Conference on Computer and Information Technology (CIT2014), Co-Chair of the 2014 IEEE Conference on Cyber, Physical and Social Computing (CPSCom2014), and TCP members of 2013 AAAI Conference on Weblogs and Social Media (ICWSM13) and reviewer for IEEE Communications Magazine.

Research interests

social networks, sentiment analysis, cloud computing, mobile / ubiquitous computing, mobile applications

Positions held at the OII

  • Research Associate, November 2014 –
  • Researcher, April 2012 –

Current projects

Past projects

  • Leaders and Followers in Online Activism

    Participants: Professor Helen Margetts, Dr Sandra Gonzalez-Bailon, Dr Ning Wang

    Where do political and policy-oriented mobilizations (such as e-petitions or organized protests) start and how are they sustained? What affects the propensity of people to join a mobilization, and hence, the mobilization's success?

  • Open Data and Civic Engagement: Mechanisms for the Promotion of Political Participation

    Participants: Dr Sandra Gonzalez-Bailon, Dr Ning Wang, Dr Jonathan Bright

    How effective are open data initiatives in encouraging civic engagement in policy-relevant domains?

  • Using Twitter to Map and Measure Online Cultural Diffusion

    Participants: Professor Mark Graham, Dr Scott A. Hale, Devin Gaffney, Dr Ning Wang

    This project is using Twitter data to comprehensively uncover where Internet content is being created; whether the amount of content created in different places is changing over time; and how content moves across time and space in the Social Web.

Conference papers

  • Wei, P. and Wang, N. (2016) "Wikipedia and stock return: Wikipedia usage pattern helps to predict the individual stock movement", Proceedings of the 25th International Conference Companion on World Wide Web. Proceedings of the 25th International Conference Companion on World Wide Web.
  • Wang, N., She, J. and Chen, J. (2014) "How "big vs" dominate chinese microblog", Proceedings of the 2014 ACM conference on Web science - WebSci '14. the 2014 ACM conference, 23 – 26 June 2014. ACM Press. 182-186.

Journal articles

Reports

  • Bright, J., Margetts, H.Z., Wang, N. and Hale, S.A. (2015) Explaining Usage Patterns in Open Government Data: The Case of Data.Gov.UK.
  • Wang, N. and González-Bailón, S. Assessing the Bias in Communication Networks Sampled from Twitter.