The Impact of Recommenders on Scientific Article Discovery: The Case of Mendeley Suggest

Minh Le, Subhradeep Kayal, Andrew Douglas

    Research output: Contribution to conferencePaperpeer-review


    Mendeley Suggest is a popular academic paper recommender, serving over 1.5 M researchers in 2018. We attempt to assess the extent Mendeley Suggest helps its users in their research in two areas: helping researchers keep up with the most prominent development in the field and help researchers find relevant literature. Our findings indicate that the recommender significantly increases the chance that a user finds important research and decreases the amount of time she needs to spend on searching. We observe that the effect is much greater than the number of accepted recommendations and propose that it is due to an increase in reading activity that Mendeley Suggest recommendations spur. Time-series analyses are presented to back up this hypothesis. Our results highlight the potential of academic paper recommenders in furthering science.
    Original languageAmerican English
    StatePublished - 2019

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