University of Cambridge > > Researching (with) Social Media reading group > Nubo Influo - Developing a Computational Approach to Understanding Online Influence

Nubo Influo - Developing a Computational Approach to Understanding Online Influence

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  • UserDr Martin Rehm (University Duisburg-Essen) and Dr Frank Cornelissen (University of Cambridge)
  • ClockFriday 17 June 2016, 12:00-13:30
  • HouseSG2, Alison Richard Building.

If you have a question about this talk, please contact Ella McPherson.

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).

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This talk is part of the Researching (with) Social Media reading group series.

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