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RwSM Reading Group, Frank Cornelissen and Martin Rehm, 17th June, 2016

Nubo Influo - Developing a Computational Approach to Understanding Online Influence

Dr Martin Rehm (University Duisburg-Essen) and Dr Frank Cornelissen (University of Cambridge)

12-1:30pm, Room S2, Alison Richard Building


The rise of social media has led to a panoply of online communication spaces wherein individuals can communicate with one another. Additionally, we argue that social media provide social opportunity spaces, wherein individuals can  scale-up their professional (informal) learning, by exchanging information and connecting with other people. Moreover, scholars have increasingly acknowledged that the concept of social capital can contribute to our understanding of how these spaces develop and evolve over time. Yet, while social media should – in theory – provide individuals with equal access to social capital formation, an increasing amount of evidence suggests that dominant individuals and groups can control communication, and impose limits on other individuals’ opportunity to gain social capital.

In this context, social network analysis has been widely used to assess social capital in social media. Furthermore, an increasing amount of studies has employed bibliometric techniques to assess the overall content of communication on social media. However, combining these two approaches is an underdeveloped area of research. Yet, such a combination would allow to make inferences on how and to what extent dominant individuals and groups can control communication on social media. Moreover, while a wide range of algorithms are available to measure and assess different facets of social media, their interpretation is not always straight forward. Furthermore, the most widely used social network metrics capturing an individual’s influence on a certain network structure (e.g. closeness and betweenness) originate from face-to-face environments. The question then arises about how these metrics translate into an online space, where (access to) information is largely open and free.

In order to address these issues, we employ a combination of social and bibliometric analyses and propose a new “influencer index” to assess the impact of individuals on social media. During our talk, we will elaborate on our methodological approach and provide first empirical evidence, from an exploratory study of 10 hashtag conversations on Twitter. The target audiences of these conversations are teachers and other actors from the domain of education from seven different countries (US, UK, Australia, New Zealand, Canada, The Netherlands and Germany).

Eventbrite - Developing a Computational Approach to Understanding Online Influence


Dr. Martin Rehm is a Postdoctoral Fellow at the Learning Lab (University Duisburg-Essen). He received his PhD from Maastricht University (The Netherlands), where he investigated the impact of hierarchical positions on Communities of Learning. His current research focus is on information diffusion and informal learning within social media. In his work, he departs from social capital theory and employs a muli-method approach, using social and semantic network, as well as bibliometric analyses.

Dr. Frank Cornelissen is a Senior Research Associate at the Faculty of Education (University of Cambridge). Until recently he worked as a Marie Curie Research Fellow at the University of California, San Diego and the University of Cambridge where he investigated the knowledge processes in school-university research networks. Currently his research focuses on examining the influence of social networks on educational practice and policy.

Key Reading

Bruns, A., & Stieglitz, S. (2013). Towards more systematic Twitter analysis: Metrics for tweeting activities. International Journal of Social Research Methodology, 16(2), 91-108.

Additional Readings

Hofer, M., & Aubert, V. (2013). Perceived bridging and bonding social capital on Twitter: Differentiating between followers and followees. Computers in Human Behavior, 29(6), 2134–2142.

Ruths, D., & Pfeffer, J. (2014). Social media for large studies of behavior. Science, 346(6213), 1063–1064.

Wasko, M. M., & Faraj, S. (2005). Why should I share? Examining social capital and knowledge contribution in electronic networks of practice. Mis Quarterly, 29(1), 35–57.

About this website

This is the website for Ella McPherson's work related to her 2014-17 ESRC-funded research project, Social Media, Human Rights NGOs, and the Potential for Governmental Accountability.