Disentangling degree and tie strength heterogeneity in egocentric social networks

被引:0
|
作者
Heydari, Sara [1 ]
Iniguez, Gerardo [1 ,2 ,3 ,4 ]
Kertesz, Janos [3 ,5 ]
Saramaki, Jari [1 ]
机构
[1] Aalto Univ, Sch Sci, Dept Comp Sci, Aalto 00076, Finland
[2] Tampere Univ, Fac Informat Technol & Commun Sci, Tampere 33720, Finland
[3] Cent European Univ, Dept Network & Data Sci, A-1100 Vienna, Austria
[4] Univ Nacl Autonoma Mexico, Ctr Ciencias Complej, Mexico City 04510, Mexico
[5] Complex Sci Hub, A-1080 Vienna, Austria
基金
芬兰科学院;
关键词
Social network analysis; Personal networks; Egocentric networks; Tie strength heterogeneity; Social signatures; Persistence; DYNAMICS; AGE;
D O I
10.1140/epjds/s13688-024-00513-x
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
The structure of personal networks reflects how we organise and maintain social relationships. The distribution of tie strengths in personal networks is heterogeneous, with a few close, emotionally intense relationships and a larger number of weaker ties. Recent results indicate this feature is universal across communication channels. Within this general pattern, there is a substantial and persistent inter-individual variation that is also similarly distributed among channels. The reason for the observed universality is yet unclear-one possibility is that people's traits determine their personal network features on any channel. To address this hypothesis, we need to compare an individual's personal networks across channels, which is a non-trivial task: while we are interested in measuring the differences in tie strength heterogeneity, personal network size is also expected to vary a lot across channels. Therefore, for any measure that compares personal networks, one needs to understand the sensitivity with respect to network size. Here, we study different measures of personal network similarity and show that a recently introduced alter-preferentiality parameter and the Gini coefficient are equally suitable measures for tie strength heterogeneity, as they are fairly insensitive to differences in network size. With these measures, we show that the earlier observed individual-level persistence of personal network structure cannot be attributed to network size stability alone, but that the tie strength heterogeneity is persistent too. We also demonstrate the effectiveness of the two measures on multichannel data, where tie strength heterogeneity in personal networks is seen to moderately correlate for the same users across two communication channels (calls and text messages).
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收藏
页数:16
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