Everything Is Obvious_ _Once You Know the Answer - Duncan J. Watts [141]
9. There are a number of subtleties to the issue of chain lengths in small-world experiments that have led to a certain amount of confusion regarding what can and cannot be concluded from the evidence. For details about the experiment itself, see Dodds, Muhamad, and Watts (2003), and for a clarifying discussion of the evidence, as well as a detailed analysis of chain lengths, see Goel, Muhamad, and Watts (2009).
10. See Watts and Strogatz (1998); Kleinberg (2000a; 2000b); Watts, Dodds, and Newman (2002); Watts (2003, ch. 5); Dodds, Muhamad, and Watts (2003); and Adamic and Adar (2005) for details on the searchability of social networks.
11. Influencers go by many names. Often they are called opinion leaders or influentials but they are also called e-fluentials, mavens, hubs, connectors, alpha mums, or even passionistas. Not all of these labels are intended to mean exactly the same thing, but they all refer to the same basic idea that a small number of special individuals have an important effect on the opinions, beliefs, and consumption habits of a large number of “ordinary” individuals (see Katz and Lazarsfeld 1955, Merton 1968b, Weimann 1994, Keller and Berry 2003, Rand 2004, Burson-Marsteller 2001, Rosen 2000, and Gladwell 2000 for a range of influentials-related labels). Ed Keller and Michael Berry claim that “One in ten Americans tells the other nine how to vote, where to eat, and what to buy.” They conclude, in fact, that “Few important trends reach the mainstream without passing through the Influentials in the early stages, and the Influentials can stop a would-be trend in its tracks” (Keller and Berry 2003, pp. 21–22); and the market-research firm Burson-Marsteller concurs, claiming that “The far-reaching effect of this powerful group of men and women can make or break a brand, marshal or dissolve support for business and consumer issues, and provide insight into events as they unfold.” All one needs to do, it seems, is to find these individuals and influence them. As a result, “Influencers have become the ‘holy grail’ for today’s marketers” (Rand 2004).
12. For the original quote, see Gladwell (2000, pp. 19–21).
13. See Keller and Berry (2003, p. 15).
14. See, for example, Christakis and Fowler (2009), Salganik et al. (2006), and Stephen (2009).
15. In fact, even then you can’t be sure. If A and B are friends, they are likely to have similar tastes, or watch similar shows on TV and so be exposed to similar information; thus what looks like influence may really just be homophily. So if every time a friend of A’s adopts something that A adopts, we attribute that to A’s influence, we are probably overestimating how influential A is. See Aral (2009), Anagostopoulos et al. (2008), Bakshy et al. (2009), Cohen-Cole and Fletcher (2008b, 2008a) Shuliti and Thomas (2010), and Lyons (2010) for more details on the issue of similarity versus influence.
16. See Katz and Lazarsfeld (1955) for a discussion of the difficulty of measuring influence, along with a more general introduction to personal influence and opinion leaders. See Weimann (1994) for a discussion of proxy measures of influence.
17. See Watts (2003) and Christakis and Fowler (2009) for discussions of contagion in social networks.
18. The connection between influentials and contagion is most explicit in Gladwell’s analogy of “social epidemics,” but a similar connection is implied throughout the literature on influentials. Everett Rogers (1995, p. 281) claims that “The behavior of opinion leaders is important in determining the rate of adoption of an innovation in a system. In fact, the S-shape of the diffusion curve occurs because once opinion leaders adopt and tell others about the innovation, the number of adopters per unit time takes off.” Keller and Berry make a similar point when they claim