Evidence map›Paper›PMID 40471962›Full record

ArticlePloS one2025

Homophilic organization of egocentric communities in ICT services.

Chandreyee Roy, Hang-Hyun Jo, János Kertész, Kimmo Kaski, János Török

Abstract read
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

5 authors.

Chandreyee RoyDepartment of Computer Science, Aalto University School of Science, Espoo, Finland.
Hang-Hyun JoDepartment of Physics, The Catholic University of Korea, Bucheon, Republic of Korea.ORCID https://orcid.org/0000-0002-4214-9204
János KertészDepartment of Network and Data Science, Central European University, Vienna, Austria.ORCID https://orcid.org/0000-0003-4957-5406
Kimmo KaskiDepartment of Computer Science, Aalto University School of Science, Espoo, Finland.
János TörökDepartment of Theoretical Physics, Institute of Physics, Budapest University of Technology and Economics, Budapest, Hungary.ORCID https://orcid.org/0000-0002-4275-2396

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Members of a society can be characterized by a large number of features, such as gender, age, ethnicity, religion, social status, and shared activities. One of the main tie-forming factors between individuals in human societies is homophily, the tendency of being attracted to similar others. Homophily has been studied mainly in the context of link formation and social dynamics. However, less is known about the role of the multidimensional homophily in forming egocentric communities on Information and Communications Technology (ICT) services. To close this gap, we analyze three ICT datasets, namely, two online social networks and one network deduced from mobile phone calls, in all of which data about individual features are available. We identify communities within egocentric networks and surprisingly find that the larger the community, the more overlap is found between features of its members and the ego. We interpret this finding in terms of the effort needed to manage the communities; the larger diversity requires more effort such that maintaining a large diverse group may exceed the capacity of the members. As the ego reaches out to their alters on an ICT service, we observe that the first alter in each community tends to have a higher feature overlap with the ego than the rest. Moreover, the feature overlap of the ego with all their alters displays a non-monotonic behavior as a function of the ego's degree. We propose a simple mechanism of how people add links in their egocentric networks of alters that reproduces the empirical observations and shows the reason behind non-monotonic tendency of the egocentric feature overlap as a function of the ego's degree.

Indexed as

EgoInformation TechnologySocial NetworkingCell PhoneFemaleHumansMale

Identifiers

PMID40471962
PMCPMC12140276

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.