Reflections on Conceptualizing and Measuring Tie Strength

We welcome this opportunity to revisit “Measuring Tie Strength” (Marsden and Campbell 1984) in light of more recent social network studies. When we wrote our article, the field of social networks was in the process of emerging as a recognized area of study, though it had many precursors (Freeman 2004). Since then, interest in network phenomena has surged, engaging analysts from many disciplines. We began by observing that the concept of tie strength had been substantively fruitful, and interest in it remains high – indeed growing: Web of Science citations to Granovetter’s classic (1973) statement about tie strength accelerated rapidly in the 2000s, exceeding 500 per year from 2009 to 2011. The much lower level of attention accorded to our article on its measurement follows a similar time path. Studies invoking the concept cover a broad substantive range: they examine topics including innovation (Ruef 2002), job searches (Harvey 2008), knowledge transfer (Levin and Cross 2004), minority social integration (Vervoort 2011), political participation (Lim 2008) and volunteering (Paik and Navarre-Jackson 2011), among many others. Studies of tie strength also span locations as disparate as China (e.g., Bian 1997) and Sweden (e.g., Korpi 2001).

The most notable role of weak ties in social networks is their structural significance as connectivity-generating factors: they tend to be bridges that connect distant clusters within social structures. Weak ties are less subject to the closure-producing transitivity pressures that operate on stronger ones, and hence less likely to be confined within local social environments. Weak ties thereby facilitate the interpersonal dissemination of novel phenomena, be those useful information or harmful diseases. Strong ties too have their roles, of course, serving, for example, as dependable sources of social or emotional support (Granovetter 1982).

If the presence of bridges is the primary concern, one might argue that measuring tie strength itself has become less necessary. The increased availability of data on “whole” social networks and myriad advances in methods for analyzing them now allow the direct identification of bridging ties within a network. Relationships having high “edge betweenness” – those that are found within large numbers of indirect paths joining pairs of actors in a network – are prone to be bridges. A well-known algorithm for locating clusters or “communities” of actors within networks (Girvan and Newman 2002) relies on this principle, successively removing the highest-betweenness ties to reveal subsets of densely interconnected actors that are relatively isolated from one another. Relationships with high edge betweenness are likely to be weak ties according to Granovetter’s argument, but if the key structural feature of bridging can be tapped directly, perhaps assessing the strength of ties is less urgent.

Many analysts are centrally interested in strong ties rather than bridges, of course. Moreover, many substantive studies drawing on network concepts continue to rely on egocentric network data from surveys like those we studied in our article, rather than measuring whole networks. Egocentric network data describe the local social environments surrounding individual actors in a network – usually comprising one or more of each focal actor’s direct contacts (“alters”) and certain qualities of the dyadic relationships between that actor (“ego”) and the alters (e.g., Marsden 2011). Such data collection designs do not support extensive structural analysis parallel to that possible for whole networks, though some measures of local structure exist (e.g., Burt 1992). Analytic interest in egocentric data sometimes focuses on properties of individual ties, and sometimes on features of an actor’s portfolio of relationships – notably network range (Campbell, Marsden and Hurlbert 1986). In such situations, proxies for the likelihood that a tie is bridging are needed, and the question we engaged in our article – how to identify stronger and weaker ties on the basis of dyadic properties such as closeness or frequency of contact – remains important. It would, however, be of interest to assess the quality of such proxy measures by correlating them with structural measures of bridging from whole-network studies.

Reflecting on our article nearly 30 years after completing the research, we begin with some thoughts about the conceptualization of tie strength as...