Uncovering the Importance of Relationship Characteristics in Social Networks: Implications for Seeding Strategies

Xi Chen, Ralf van der Lans, and Tuan Q. Phan
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Key Takeaways
  • ​To understand diffusion processes on social networks, it is not sufficient to simply view relationships between people as uniform.

  • The fact that relationships between people are heterogeneous has significant consequences for understanding diffusion processes.

  • The differential importance of relationships can be inferred from diffusion patterns.

  • The recovered importance enables practitioners to more effectively spread information in social networks by seeding more influential people.

​Article Snapshot: Executive Summaries from the Journal of Marketing Research

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Scholars have identified a new method to recover the importance of relationships in social networks (i.e., Facebook, Twitter, LinkedIn etc.), helping to understand the spread of information in diffusion processes and viral marketing.

Despite the evidence that strengths of connections between individuals vary systematically, previous research mostly treated the social network as given and a priori determined the strength of connections between individuals.

The proposed multi-network approach demonstrated that the importance of relationship characteristics substantially varied. In both applications, recognizing these differences not only resulted in a better statistical fit, but also led to better seeding strategies.

Research Question

As discussed in the seminal work of Granovetter (1973), “The strength of weak ties”, the connections between individuals in social networks vary in strength. Therefore, it is important to identify the strengths so that we can attain a rightful understanding of how social network structure drives the diffusion of information.

Previous research, however, ignored the strengths or specified the strengths a priori when there is ample evidence that the strengths of connections vary with different relationship characteristics as well as information and products exchanged.

We hypothesize that the strengths of connections leave a "trace" on diffusion patterns, which can be statistically inferred from secondary data.


We developed a framework, called "multi-network approach", to recover strengths of connections in social networks from actual diffusion patterns. The strengths of connections depend on relationship characteristics, such as friendships vs. colleagues, duration of the relationship and intensity of contact. We applied the proposed framework to two empirical settings of microfinance diffusion in Indian villages and information dissemination in an online social networking site. For both applications, we recovered the importance of different relationship characteristics and demonstrated how to use the recovered importance to formulate better seeding strategies.


For both empirical applications, we found that different relationship characteristics indeed drive the diffusion process differently. In first application, we found that social relationship were more important for the diffusion of a microfinance program in Indian villages than economic, religious and familial relationships. In the second application, we found that recent friendships and friendships that exchange more information   had a stronger social influence in information dissemination. For both application, the framework recommended seeding strategies that improved diffusion by up to 10 percent (first application) and up to 92 percent (second application), compared with the state-of-art strategies. In addition, we found that seeding strategies based on weighted degree centrality generally performed better.


It is an intuitive finding that one's susceptibility to another's influence depends on the characteristics of the relationship between them. Specifically, in the first empirical application, social interaction is actually found to be more influential on an ecomonic activity than economic interaction. In the second application, online users are found to be more influenced by users they interact more recently and frequently.

Online marketers and social network platforms such as Facebook, LinkedIn, Twitter, MySpace, YouTube should be interested to better understand how information spreads online. In particular, these platforms should not only take into account how many friends someone has, but also how strong these relationships are.

Questions for the Classroom:

  • What are the characteristics of relationships in social networks and how do they drive diffusion processes differently?

  • Is it possible to recover the importance of different relationship characteristics? If yes, how?

  • How to formulate a seeding strategy with the recovered importance of relationship characteristics

Article Citation:

Xi Chen, Ralf van der Lans, and Tuan Q. Phan (2017) Uncovering the Importance of Relationship Characteristics in Social Networks: Implications for Seeding Strategies. Journal of Marketing Research: April 2017, Vol. 54, No. 2, pp. 187-201.

doi: http://dx.doi.org/10.1509/jmr.12.0511
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Author Bio:

Xi Chen, Ralf van der Lans, and Tuan Q. Phan
Xi Chen is Assistant Professor of Marketing, Erasmus University (e-mail: chen@rsm.nl). Ralf van der Lans is Associate Professor of Marketing, Hong Kong University of Science and Technology (e-mail: rlans@ust.hk). Tuan Q. Phan is Assistant Professor of Information Systems, National University of Singapore (e-mail: tphan@comp.nus.edu.sg).
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