ArticleScientific reports2018
Understanding tie strength in social networks using a local "bow tie" framework.
Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
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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.
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Who cites it
12 citing papers in PubMed, 40 citations in OpenAlex.
- Article
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- Bow-tie architectures in biological and artificial neural networks: Implications for network evolution and assay design.iScience · 2023Article
- Can participatory processes lead to changes in the configuration of local mental health networks? A social network analysis.Frontiers in public health · 2023Article
- STEM learning communities promote friendships but risk academic segmentation.Scientific reports · 2022Article
- Neuroinflammation Following Traumatic Brain Injury: Take It Seriously or Not.Frontiers in immunology · 2022Review
- Blocking and being blocked on gay dating apps among MSM attending a sexual health clinic: an observational study.BMC public health · 2021Observational
- Transmission networks and ectoparasite mite burdens inParasitology · 2021Article
- A weighted network analysis framework for the hourglass effect-And its application in the C. elegans connectome.PloS one · 2021Article
- Beyond Activity Space: Detecting Communities in Ecological Networks.Annals of the American Association of Geographers · 2020Article
- Association between social asymmetry and depression in older adults: A phone Call Detail Records analysis.Scientific reports · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 3 institutions in 3 countries.
Funding
Abstract
Understanding factors associated with tie strength in social networks is essential in a wide variety of settings. With the internet and cellular phones providing additional avenues of communication, measuring and inferring tie strength has become much more complex. We introduce the social bow tie framework, which consists of a focal tie and all actors connected to either or both of the two focal nodes on either side of the focal tie. We also define several intuitive and interpretable metrics that quantify properties of the bow tie which enable us to investigate associations between the strength of the "central" tie and properties of the bow tie. We combine the bow tie framework with machine learning to investigate what aspects of the bow tie are most predictive of tie strength in two very different types of social networks, a collection of medium-sized social networks from 75 rural villages in India and a nationwide call network of European mobile phone users. Our results show that tie strength depends not only on the properties of shared friends, but also on non-shared friends, those observable to only one person in the tie, hence introducing a fundamental asymmetry to social interaction.
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Registered trials
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.