Long-Range Social Influence in Phone Communication Networks on Offline Adoption Decisions

We use high-resolution mobile phone data with geolocation information and propose a novel technical framework to study how social influence propagates within a phone communication network and affects the offline decision to attend a performance event. Our fine-grained data are based on the universe of phone calls made in a European country between January and July 2016. We isolate social influence from observed and latent homophily by taking advantage of the rich spatial-temporal information and the social interactions available from the longitudinal behavioral data. We find that influence stemming from phone communication is significant and persists up to four degrees of separation in the communication network. Building on this finding, we introduce a new “influence” centrality measure that captures the empirical pattern of influence decay over successive connections. A validation test shows that the average influence centrality of the adopters at the beginning of each observational period can strongly predict the number of eventual adopters and has a stronger predictive power than other prevailing centrality measures. Our centrality measure can be used to improve optimal seeding strategies in contexts with influence over phone calls, such as targeted or viral marketing campaigns.

• 저널Information Systems Research · 35(1) · 318–338
• 토픽Complex Network Analysis Techniques · Statistical and Nonlinear Physics
• DOI10.1287/isre.2023.1231
• 저자Yan Leng, Xiaowen Dong, Esteban Moro, Alex Pentland