On the Gender of Books: Author Gender Mixing in Book Communities

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    2 Citations (Scopus)
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    Using a book co-buying network from amazon.com of over 1 million books, we find empirically that readers who have purchased male first authors before are substantially less likely than expected to buy books by female first authors, when aggregated across the entire book market. Conversely, past buyers of female authors are slightly more likely than expected to buy other female authors. This same-gender assortativity is found to be local: certain writing genres are ``coloured'' preferentially by one gender. This can be attributed both to writer availability (i.e., a gender's preferential attachment to writing for one genre), and to the buyers' preferential attachment to the output of writers of one gender. We obtain these insights by classifying the gender of the first author for most of the books, then running statistical tests which compare the gender makeup of books co-bought with either male or female books. Structural book communities, as generated from readers' co-buying choices, are computed, visualised in terms of gender makeup, and their writing genres are summarised to match the genre with a gender makeup.
    Original languageEnglish
    Title of host publicationComplex Networks and Their Applications VI
    Subtitle of host publicationProceedings of Complex Networks 2017 (The Sixth International Conference on Complex Networks and Their Applications)
    EditorsChantal Cherifi, Hocine Cherifi, Márton Karsai, Mirco Musolesi
    Place of PublicationCham
    Number of pages12
    ISBN (Electronic)978-3-319-72150-7
    ISBN (Print)978-3-319-72149-1
    Publication statusPublished - 2018
    Event6th International Conference on Complex Networks and Their Applications - Lyon, France
    Duration: 29 Nov 20171 Dec 2017
    Conference number: 6

    Publication series

    NameStudies in Computational Intelligence
    ISSN (Print)1860-949X


    Conference6th International Conference on Complex Networks and Their Applications
    Abbreviated titleComplex Networks 2017


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