Investigating and Modeling the Dynamics of Long Ties

Long ties, the social ties that bridge different communities, are widely believed to play crucial roles in spreading novel information in social networks. However, some existing network theories and prediction models indicate that long ties might dissolve quickly or eventually become redundant, thus putting into question the long-term value of long ties. Our empirical analysis of real-world dynamic networks shows that contrary to such reasoning, long ties are more likely to persist than other social ties, and that many of them constantly function as social bridges without being embedded in local networks. Using a cost-benefit analysis model combined with machine learning, we show that long ties are highly beneficial, which instinctively motivates people to expend extra effort to maintain them. This partly explains why long ties are more persistent than what has been suggested by many existing theories and models. Overall, our study suggests the need for social interventions that can promote the formation of long ties, such as mixing people with diverse backgrounds.

Forward the behavior and social science community from nature portfolio.

An Experimental Study of Tie Transparency and Individual Perception in Social Networks

Tie transparency, which may provide more unbiased information to deepen mutual understanding, thus builds trust and prompts cooperation in social networks. Little is known, however, about social connections’ transparency. We introduce knowable degree (KD) to characterize the transparency of a social tie, defined as the number of other entities who perceive the tie. We design a two-phase experiment to collect KDs in a network of 155 students. We find that structural property and node attribute significantly predict tie transparency. Meanwhile, we also find there almost always exist a few covert ties due to non-reciprocity. Furthermore, we focus on exploring the boundary of scopes of perception and evaluating individuals’ perceptual capability. We describe the two degrees of perception phenomenon that people can generally catch the relationships between their 2-neighbours at most. We propose a generic quantitative model to recognize high-capability perceivers, who are found more sociable and enjoy exploring the social context as well.