Weighted reciprocity in human communication networks

Abstract

In this paper we define a metric for reciprocity---the degree of balance in a social relationship---appropriate for weighted social networks in order to investigate the distribution of this dyadic feature in a large-scale system built from trace-logs of over a billion cell-phone communication events across millions of actors. We find that dyadic relations in this network are characterized by much larger degrees of imbalance than we would expect if persons kept only those relationships that exhibited close to full reciprocity. We point to two structural features of human communication behavior and relationship formation---the division of contacts into strong and weak ties and the tendency to form relationships with similar others---that either help or hinder the ability of persons to obtain communicative balance in their relationships. We examine the extent to which deviations from reciprocity in the observed network are partially traceable to these characteristics.

14 pages, 5 figures, 1 table

References in corpus (13)

• Assortative mixing in networks
• The architecture of complex weighted networks
• Mixing patterns in networks
• Specificity and stability in topology of protein networks
• Why social networks are different from other types of networks
• Extracting the multiscale backbone of complex weighted networks
• Patterns of link reciprocity in directed networks
• Weighted Evolving Networks
• Characterization and Modeling of weighted networks
• Pattern Detection in Complex Networks: Correlation Profile of the Internet
• The origin of degree correlations in the Internet and other networks
• Assortative model for social networks
• Reciprocity of Networks with Degree Correlations and Arbitrary Degree Sequences

Cited by in corpus (3)

• Quantifying Information Flow During Emergencies
• A survey of results on mobile phone datasets analysis
• Dynamics of Trust Reciprocation in Heterogenous MMOG Networks