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• W2967722518 abstract "We present a method for automatically organizing and evaluating the quality of different publishing venues in Computer Science. Since this method only requires paper publication data as its input, we can demonstrate our method on a large portion of the DBLP dataset, spanning 50 years, with millions of authors and thousands of publishing venues. By formulating venue authorship as a regression problem and targeting metrics of interest, we obtain venue scores for every conference and journal in our dataset. The obtained scores can also provide a per-year model of conference quality, showing how fields develop and change over time. Additionally, these venue scores can be used to evaluate individual academic authors and academic institutions. We show that using venue scores to evaluate both authors and institutions produces quantitative measures that are comparable to approaches using citations or peer assessment. In contrast to many other existing evaluation metrics, our use of large-scale, openly available data enables this approach to be repeatable and transparent." @default.
• W2967722518 created "2019-08-22" @default.
• W2967722518 creator A5090078593 @default.
• W2967722518 date "2019-06-01" @default.
• W2967722518 modified "2023-10-14" @default.
• W2967722518 title "Venue Analytics: A Simple Alternative to Citation-Based Metrics" @default.
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• W2967722518 doi "https://doi.org/10.1109/jcdl.2019.00052" @default.
• W2967722518 hasPublicationYear "2019" @default.
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