In class on Monday, we learned about the effects that societal factors can play on impacting social network graphs, as illustrated by the derived projected graphs that link people not only due to personal contact but also by societal hotspots, such as a club, company board, or workplace. Digging deeper into the impacts of such affiliation networks, one can easily come across a recent paper by an employee at Google and his colleague that not only do affiliation networks help connect people through non-interpersonal means, they do so at an optimal rate that creates an increasingly dense social network. In this paper, the authors prove that should a social network conform to a bipartite graph form, that is, having actors in one set and societal hotspots – foci – as another set, with edges only forming between sets, that this social network conforms to a power-law distribution, as seen below.
The obvious follow through of this theory is that such affiliation networks also create highly interconnected social networks, due to the power of foci to generate edges between people belonging to different environments – as shown in our homework problem on the affiliation network of company board members.
The importance of this theoretical underpinning of affiliation networks is that closed networks can use this insight to create powerful apps designed to quickly saturate large populations with edges in order to create what we have referred to as a “giant component” of the network. In fact, Palaround has drawn on the incredibly successful interface of Tinder in order to create a software that allows any organization to generate their own affiliation network based through a personalized mobile application, thus allowing the organization to quickly interconnect its members at a theoretically maximal rate . Palaround’s app allows an organization to become a foci within the broader social network of Palaround’s members that users can “belong to”, in addition to the already commonly-used foci of geographic location, age or interests . Then, Palaround’s members are able to use the Tinder-Originated feature of “swiping” to start a chat with another individual they share a foci with in order to more fully saturate some subset of the population with edges. This is in response to what Palaround has noted as many larger groups’ concerns that,” For some reason, their people aren’t connecting or they’re not connecting efficiently, and that building a community is absolutely critical for them.” Palaround plans to use their application as a cost-effective alternative to proprietary company friend-finders that also try and achieve the same sort of affiliation networks albeit at a much higher cost.
The aim of the application is to increase the average degree (connections) of a random node (person) within a subset of a given closed social network, in order to promote a stronger sense of collaboration and teamwork, such as in alumni networks or private clubs. This is further achieved by the unique ability of the application, unlike Tinder, to create group messages that link everyone that has “swiped” on one another – in effect using the very action of swiping as another foci around which edges can be created. The result of these aspects of the application is an even-more powerful medium through which to generate highly interconnected projected graphs based off of affiliation networks, thus resulting in stronger teamwork across industry and within companies.
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