Abstract
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.
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This non-assortativity of Amazon book co-buying graphs is confirmed by the assortativity coefficients of other Amazon crawls public at http://networkrepository.com/.
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Bucur, D. (2018). On the Gender of Books: Author Gender Mixing in Book Communities. In: Cherifi, C., Cherifi, H., Karsai, M., Musolesi, M. (eds) Complex Networks & Their Applications VI. COMPLEX NETWORKS 2017. Studies in Computational Intelligence, vol 689. Springer, Cham. https://doi.org/10.1007/978-3-319-72150-7_64
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DOI: https://doi.org/10.1007/978-3-319-72150-7_64
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