• Asaf Shapira

SNA Classics: The Strengh of Weak Ties (Granovetter)

עודכן ב: ינו 11

This paper, published 1973, is an SNA classic with more than 59,000 citations. It's author, M.S. Granovetter, is known for his research about how people find out about vacant jobs and the importance of weak social ties in this process. These groundbreaking findings were counter-intuitive because research intuition till then emphasized the importance of the individual's strong ties to his social surrounding, which sounds pretty logical. Intuitively, I guess most of us think about our strong ties as more important and influential than our weak ties.

I guess many SNA analysts will content themselves with the gist of his research, but the article contains additional insights relevant to this day, even after 46 years:

  1. Granovetter shows how a perturbation languishes beyond the first and second circle of ties in an Ego Network - a thing to keep in mind when performing a snowball sampling on a dataset. Interestingly, this issue came up in the NSA's hearing in congress 2013. The NSA denied conducting surveillance of American citizens but noted that the "agency can perform 'three-hop queries' through Americans' data and records". All this relates closely to Robin Dunbar's famous research which will be added as a post in the "Classics" section.

  2. The Micro/Macro Paradox of strong ties: An interesting theory (which Granovetter mentions as yet-to-be-proven) is that strong ties in micro scale create cohesion while paradoxically create fragmentation on a macro scale, In the early 2000's, network scientists were able to demonstrate this theory on communities (clusters) in networks.

  3. The article raises methodological points to consider while assessing a theory, especially when the theory rests upon the author's intuition or common sense, but lacks empirical proof. If anything, SNA taught me to throw my intuition/life experience/common sense out of the nearest window when it comes to analyzing complex systems. But, hey, isn't life itself a complex system? Well, I guess that's what makes it interesting :)


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