Online communities are connecting hordes of individuals and generating rich social network data. The social capital that resides within these networks is largely unknown. We have developed a general framework for measuring and leveraging social capital based upon explicit social networks, implicit affinities, and social resources. The resulting quantitative models are used to characterize social capital in several online communities.
We find it useful to distinguish between types of connections among individuals, as follows.
We call explicit social networks (ESNs), social networks built from explicit connections and implicit affinity networks (IANs), social networks built from implicit connections, and focus on their complementary natures.
Additionally, social resources are an important component of measuring social capital.
ESNs can be created using a variety of techniques. Some online communities (e.g., Facebook, Twitter, LinkedIn) have incorporated functionality that allows you to specify who you are explicitly connected to (e.g., who your friends are). Other techniques have been used to derive ESNs by using social interaction data. For example, ESNs have been generated by observing the frequency of email correspondence among individuals within a corporation (See Diesner et al 2005). Others, have derived ESNs using links among blogs, assuming that blogs that are "friends" link often to one another (e.g., Kumar et al 2003, Adamic et al 2005). Figure 1a shows possible explicit connections that make up an ESN for a sample set of individuals.
IANs are built from individuals represented as collections of attributes and associated value sets, where links are created whenever two individuals share an attribute whose value sets overlap. For example, in the network pictures the IAN is represented by dotted orange lines. Whenever an individual X adds a value, say v, to one of its attributes, say A, some amount of affinity is automatically added between X's node and all existing nodes whose individuals have value v for A. IANs tend to be highly dynamic and are subject to a chosen similarity metric.
As theorized by Lin, personal and social resources can be characterized for Individual actors. These resources are defined as either material goods (e.g. land, houses, car, and money) or symbolic goods (e.g., education, memberships in clubs, reputation, or fame). Personal resources (i.e., human capital) are in the possession of the individual, while social resources (i.e., social capital) are accessible through social connections (see Lin 2001). Resources gained through bridging interactions are perceived to be of greater worth as they are more likely to be dissimilar than the resources already available.
Lin characterizes access and mobilization as theoretical approaches that describe how social capital is expected to produce returns (see Lin 2008). Access estimates the amount of social capital (known to be) available to an individual. This approach is based on the assumption that the amount of accessible social capital largely determines the returns, without regard to the particular actions taken to use the social capital. Alternatively, the theoretical approach of mobilization reflects "a selection of one or more specific ties and their resources from the pool for a particular action at hand" (see Lin 2008). For example, using a specific contact having certain resources (e.g., a highly trafficked blog, or domain-knowledge) to boost sales on an e-commerce site could be indicative of mobilized social capital.
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