A new study of social networks presents a model of how new relationships develop and how knowledge of the expanded network can aid marketing efforts.
Researchers from Columbia University and Zurich University observed that multiple, distinct types of relationships often occur among users of the same network. According to the experts, these variations are not explained by existing models.
For example, when people connect with each other through networks, they connect via multiple relationships.
One connection is when two Facebook users are online “friends” but may not regularly communicate with each other directly. Another connection occurs when a user comments on another’s profile, a different type of relationship in the network.
Offline, multiple relationships also exist, as when employees in different departments in an organization perform different types of work (for instance, marketing and operations), but still interact with each other.
Given this set of observations, the researchers wanted to know whether the formation of one type of relationship in a network could predict connections via other types of relationships.
The study authors developed an integrated statistical framework for simultaneously modeling the connectivity structure of multiple relationships of different types on a common set of actors.
Two scenarios were studied. The first involved a sequential network of communications among managers during new product development activities, and the second was an online collaborative social network of musicians.
The researchers modeled both direct (a relationship with a clear sender and receiver) and undirected relationships (such as a collaboration relationship), to prove how different relationships can be encased within a common framework.
In terms of multiple relationships, the statistical framework created by the researchers can also captured weighted and un-weighted relationships.
In terms of social networking online, the researchers focused on a Swiss social networking site for musicians, where three types of relationships were studied: individual friendships between musicians; relationships based on communication or the exchange of information, such as direct messages or comments about upcoming concerts; and musicians’ downloads of others’ music.
They found that common factors determined the likelihood that each of these relationships would form, including geographical proximity of users; the online, as opposed to offline, popularity of musicians; and whether the users shared an identity as an individual musicians or as part of a band.
These factors were related with the existence of a relationship and its strength — for instance, the more messages two users sent each other, the stronger the connection between them.
In terms of networking in the workplace, the researchers measured the impact of interventions in a network by focusing on an organization’s small network of different groups of managers — such as research and development, marketing, and operations — involved in the development of a new product.
These managers were moved into one shared facility, with researchers examining the types and strength of relationships between managers from different departments before and after the intervention.
The model accurately predicted what relationships would form based on common characteristics and predicted the effects of intervention on relationships in the network.
Investigators believe these findings can assist marketing managers, customers relationship managers, and direct marketers. For example, this research can help identify and target influential users in a network, predict network relationships, and improve understanding of the network structure.
This knowledge can help to better leverage word-of-mouth marketing or the information transfer potential of a particular network.
In addition, operations managers can use this model to better understand the social and communication structure of their organizational network, which can lead to solutions for increased efficiency and productivity among employees.
The research was recently featured in the Journal of Marketing Research.
Source: Columbia Business School