Co-loan analysis of finnish public library loan data

This paper analyses public library loan data of the two most popular book genres, novels and crime fiction, to illustrate the cultural and social literacy prevailing in Finland. Using a social network analysis method we are able to identify and visualize distinct book clusters - rather than simply groups of books - providing a considerably more nuanced insight. Firstly, we generated book networks based on library customers' loan transactions where books were associated with each other when they were co-loaned. We then applied a modularity maximization method to identify book clusters. The most influential books and authors were identified by examining their involvement in the network. The results show that the reading culture is no longer uniform but is fragmented into multiple smaller clusters. Additionally, the position of national classics, popular among Finnish readership some decades ago, has radically weakened. The results also show that the library users typically borrow multiple books in the same series. Through this study, we found that a social network analysis leads to a better interpretation of the library collection usage and overview of the reading culture. The presented approach benefits library users, librarians, and literary scholars.