@techreport{kajic2018,
    title = {Evaluating the psychological plausibility of word2vec and GloVe
        distributional semantic models},
    year = {2018},
    month = {08},
    institution = {Centre for Theoretical Neuroscience},
    address = {Waterloo, ON},
    abstract = {
        The representation of semantic knowledge poses a central modelling
            decision in many models of cognitive phenomena. However, not all
            such representations reflect properties observed in human semantic
            networks. Here, we evaluate the psychological plausibility of two
            distributional semantic models widely used in natural language
            processing: word2vec and GloVe. We use these models to construct
            directed and undirected semantic networks and compare them to
            networks of human association norms using a set of graph-theoretic
            analyses. Our results show that all such networks display
            small-world characteristics, while only undirected networks show
            similar degree distributions to those in the human semantic
            network. Directed networks also exhibit a hierarchical organization
            that is reminiscent of the human semantic network.},
    issn = {CTN-TR-20180824-012},
    author = {Kaji\'c, Ivana and Eliasmith, Chris},
    doi = {10.13140/RG.2.2.25289.60004},
    url = {https://www.researchgate.net/publication/327209035_Evaluating_the_psychological_plausibility_of_word2vec_and_GloVe_distributional_semantic_models},
    pdf = {/files/publications/kajic.2018.pdf}
}