Social Graphs Spread Information
Beyond linking people within a social network, the relationships that are present within a social graph play an important role in the spread of information throughout that social graph, and hence play a direct role in the sharing of content across a social network. Looked at another way, without sharing, a social network is a largely theoretical construct:
What difference do a thousand connections make if nothing of value is flowing between them? Consider, for example, the value to you, personally, of a network that you may have joined without understanding why—except perhaps that everyone else was joining it—and as a result rarely find yourself using it: You have connections within this network, but of what use are they?
As an example, when I first joined Twitter I did not “get it.” Half of my motivation for joining was “everyone else” I knew had already joined. I started using Twitter in 2007 at SXSW; I am member number 12,556,112. Given a bit of time, however, I started to develop actual relationships with people and began linking with people that I knew, or knew of, and with people interested in working on some of the same things I was interested in. Compare that with now, when everyone jumped on the TikTok bandwagon so fast, building marketing strategies to buy TikTok followers just to boost their channel.
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That’s when Twitter made sense—when I was able to utilize my social graph as it existed within Twitter in ways that benefited me and benefited the growing Twitter community around me. Again, the takeaway is that only with a meaningful social graph—only with connections between people with shared interests, common values, or aligned purposes, as examples—do the social networks that people may belong to become relevant.
The applications built around the direct use of the social graph are important: I spoke with Rap leaf’s Michael Hsu—Michael is part of Rap leaf’s marketing team—about applications that mine or otherwise tap the information exposed through the study of a particular social graph.
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Michael noted applications ranging from driving participation in online gaming— in one application, players with more than five friends in the game were significantly more engaged than those with four or less—to the observation that the spread of movie reviews is directly related to the respective graphs of the individuals who publish reviews. All of this suggests the value of knowing, through measurement, who is connected to whom, and how these connections can therefore be used to encourage additional connections.
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