Quantifying gender preferences in human social interactions using a large cellphone dataset

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dc.contributor Aalto-yliopisto fi
dc.contributor Aalto University en
dc.contributor.author Ghosh, Asim
dc.contributor.author Monsivais, Daniel
dc.contributor.author Bhattacharya, Kunal
dc.contributor.author Dunbar, Robin I.M.
dc.contributor.author Kaski, Kimmo
dc.date.accessioned 2019-04-02T06:56:16Z
dc.date.available 2019-04-02T06:56:16Z
dc.date.issued 2019-03-12
dc.identifier.citation Ghosh , A , Monsivais , D , Bhattacharya , K , Dunbar , R I M & Kaski , K 2019 , ' Quantifying gender preferences in human social interactions using a large cellphone dataset ' EPJ Data Science , vol. 8 , no. 1 , 9 , pp. 1-15 . https://doi.org/10.1140/epjds/s13688-019-0185-9 en
dc.identifier.issn 2193-1127
dc.identifier.other PURE UUID: a2ff67df-e7ad-4763-a1ee-1b0c46e04f7e
dc.identifier.other PURE ITEMURL: https://research.aalto.fi/en/publications/quantifying-gender-preferences-in-human-social-interactions-using-a-large-cellphone-dataset(a2ff67df-e7ad-4763-a1ee-1b0c46e04f7e).html
dc.identifier.other PURE LINK: http://www.scopus.com/inward/record.url?scp=85062952031&partnerID=8YFLogxK
dc.identifier.other PURE FILEURL: https://research.aalto.fi/files/32803308/s13688_019_0185_9.pdf
dc.identifier.uri https://aaltodoc.aalto.fi/handle/123456789/37357
dc.description | openaire: EC/H2020/662725/EU//IBSEN
dc.description.abstract In human relations individuals’ gender and age play a key role in the structures and dynamics of their social arrangements. In order to analyze the gender preferences of individuals in interaction with others at different stages of their lives we study a large mobile phone dataset. To do this we consider four fundamental gender-related caller and callee combinations of human interactions, namely male to male, male to female, female to male, and female to female, which together with age, kinship, and different levels of friendship give rise to a wide scope of human sociality. Here we analyse the relative strength of these four types of interaction using call detail records. Our analysis suggests strong age dependence for an individual of one gender choosing to call an individual of either gender. We observe a strong bonding with the opposite gender across most of their reproductive age. However, older women show a strong tendency to connect to another female that is one generation younger in a way that is suggestive of the grandmothering effect. We also find that the relative strength among the four possible interactions depends on phone call duration. For calls of medium and long duration, opposite gender interactions are significantly more probable than same gender interactions during the reproductive years, suggesting potential emotional exchange between spouses. By measuring the fraction of calls to other generations we find that mothers tend to make calls more to their daughters than to their sons, whereas fathers make calls more to their sons than to their daughters. For younger callers, most of their calls go to the same generation contacts, while older people call the younger people more frequently, which supports the suggestion that affection flows downward. Our study primarily rests on resolving the nature of interactions by examining the durations of calls. In addition, we analyse the intensity of the observed effects using a score based on a null model. en
dc.format.extent 1-15
dc.format.mimetype application/pdf
dc.language.iso en en
dc.publisher Springer Science + Business Media
dc.relation info:eu-repo/grantAgreement/EC/H2020/662725/EU//IBSEN
dc.relation.ispartofseries EPJ Data Science en
dc.relation.ispartofseries Volume 8, issue 1 en
dc.rights openAccess en
dc.subject.other Modelling and Simulation en
dc.subject.other Computer Science Applications en
dc.subject.other Computational Mathematics en
dc.subject.other 113 Computer and information sciences en
dc.title Quantifying gender preferences in human social interactions using a large cellphone dataset en
dc.type A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä fi
dc.description.version Peer reviewed en
dc.contributor.department Department of Computer Science
dc.contributor.department Helsinki School of Economics
dc.contributor.department University of Oxford
dc.subject.keyword Egocentric networks
dc.subject.keyword Gender differences
dc.subject.keyword Life history
dc.subject.keyword Mobile phones
dc.subject.keyword Sex differences
dc.subject.keyword Social networks
dc.subject.keyword GROUP-SIZE
dc.subject.keyword Modelling and Simulation
dc.subject.keyword Computer Science Applications
dc.subject.keyword Computational Mathematics
dc.subject.keyword 113 Computer and information sciences
dc.identifier.urn URN:NBN:fi:aalto-201904022488
dc.identifier.doi 10.1140/epjds/s13688-019-0185-9
dc.type.version publishedVersion

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