Blog and social network platforms

Social Networking

Based on the first reading, summarize the idea of "relational data." Give examples of questions that can be asked/answered using social network analysis methods.

Throughout his extensive analysis of social networks and their fundamentals, Cook (2001) defines their essential components, their interactions, dependencies, and behaviors as they relate to one another and the broader sociograms they comprise. Relational data is the most fundamental elements within the constructs and models that Cook describes throughout the article referenced. Nodes, ties, symmetrical, and asymmetrical networks and the resulting multiplexities and structures of interactionism that are exhibited by social networks as they evolve are all fueled by relational data. The transactions between nodes in a sociogram are comprised of relational data in its many forms, some very structured, some unstructured. The common thread across all components of the relational data however is the establishment of trust through the creation of frequent interactions between nodes. Cook (2001) stresses that these nodes can be institutions, ideas, people, organizations, or in short any entity. The frequency of contact between nodes within the context of multiple roles is critical for the maturation of trust within a sociogram, and a broader social context.

Social network analysis specifically focuses on the science of how the many components and dynamics of a sociogram interact with one another. When people, organizations, or a combination of the two is involved, the creation of trust through the reliance on many roles leads to the definition of communities. The questions specifically that can be asked of social networks can range from the highly sociological to the relational aspects of how social networks learn and adapt to changing factors both inside and outside their control. The questions that can be asked using social network analysis are most effective in looking at the complexities of interrelationships between nodes and their activities are sharing, earning and keeping trust with, and solidifying the ties across nodal boundaries of the network. Word of Mouth advertising, the rise of consumer-generated media including blogs, and the entire area of reputation systems as is highly visible throughout Amazon.com and their rankings of books are all examples of what social networking analysis could be used for. Specifically the questions these techniques could answer include the growth of both positive and negative feedback on product sales and the correlation of these reviews to the success or failure of a product, and mining of unstructured content that can yield insights into how social networks perceive the strengths and weaknesses of any given company's products or services, and an entirely new approach to segmenting markets for automobiles for example through common perceptions of environment factors, as is the case with Toyota Prius owners and their focus on being environmentally aware with the cars they purchase. In short, social network analysis has the potential to specifically define entirely new approaches to the way companies attract, sell, and serve customers.

Evaluate the application of SNA in Huang & DeSanctis article.

The work completed by Huang and DeSanctis (2005) take social network theory and applies it pragmatically to a series of online forums dedicated to enterprise software and business process areas of interest. The authors report that the theoretical aspects of how social network congeal and become a catalyst for change within organizations. The crux of this paper emerges a maturity model that defines how social networks eventually attain trusted status among their members, with the structure of the networks themselves being integral to the growth of explicit or tacit knowledge. A fascinating finding is that when social networks are in a star topology there is a pronounced lower level of transactive information sharing. Contrasting this limiting effect on information sharing based on a star topology, the core-periphery structure enables more egalitarian information sharing and transactive use of data.

One of the key findings of the work by Huang and DeSanctis (2005) underscores' Cooks' (2001) assessment of multiple roles within a social network creating more of a basis for trust and more effective transactive data being shared and published throughout a network. From these observations by Huang and DeSanctis (2005) and the resulting influences of asymmetrical and symmetrical flows between nodes in an evolving community, a maturity model of interactions, level of transactive data, quantification of trust, core-periphery and ultimately the creation of an information exchange all can be predicted by the maturity model that emerges from the forum-based research completed.