I participated in a webinar hosted by the Prospect Research Institute. We discussed the ways that NodeXL can simplify the task of collecting social media and social network data. The tool generates easy to understand reports that highlight insights into connected structures.
The slides associated with the talk can be found here:
In this episode host Randy Farmer (@frandallfarmer) and I talk about how to think about social media influence in terms of a social network. Networks can be measured and a variety of patterns can be found in them that indicate the role or pattern of connections a person has.
We talk about why influence is not a single attribute, it is a more complex function of a person’s position within a web of relationships.
People play different roles in social media networks, we talk about three: hubs, bridges and islands. Each plays a different role in a social media network. Each has a different kind of influence.
Once these different roles are measured, people can be ranked in terms of their similarity to one or the other pattern. Highly ranked people can be influential” in terms of their different locations in a network.
In a related blog post, I suggest possible strategies for using network insights to drive a social media campaign: identify key people and their content to guide targeted relationship building. See:
This April 8 and 9, 2013 an NSF funded workshop called Kredible.Net to be held at Purdue University will bring together researchers studying reputation and social roles in social media.
The grant will help researchers investigate how social media, especially Wikipedia articles and editors, shape public knowledge. The project aims to build a research community and to propose a research agenda for the study of reputation and authority in informal knowledge markets, such as Wikipedia.