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Model for Explaining Citations in Scholarly Publications: A Conceptual Overview of the Literature

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      Abstract

      Understanding the process of citing is a necessary condition for the use of citations in research evaluation. Citations can only be used wisely in these evaluations, if the user is informed about the basic elements of the process and knows the relevant underlying factors. In this study, we introduce a model for explaining citations in scholarly publications. The model is composed of three major elements, including the context of the cited document, pathways from selection to citation of documents, and the context of the citing document. The model is simply designed to include only a few major and minor elements in order to be clear and understandable, but the elements are explained in great detail in this study. With the model, which has its roots in available citation theories, recent studies in bibliometrics on factors influencing citations and citation context are reviewed and synthesized to gain insights into the process of citing. The model can be used to understand the process of citing and delivers basic information for the proper application of citations in research evaluation. The model also reveals gaps in empirical research on citations.

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      What do citation counts measure? A review of studies on citing behavior

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        Do Altmetrics Work? Twitter and Ten Other Social Web Services

        Altmetric measurements derived from the social web are increasingly advocated and used as early indicators of article impact and usefulness. Nevertheless, there is a lack of systematic scientific evidence that altmetrics are valid proxies of either impact or utility although a few case studies have reported medium correlations between specific altmetrics and citation rates for individual journals or fields. To fill this gap, this study compares 11 altmetrics with Web of Science citations for 76 to 208,739 PubMed articles with at least one altmetric mention in each case and up to 1,891 journals per metric. It also introduces a simple sign test to overcome biases caused by different citation and usage windows. Statistically significant associations were found between higher metric scores and higher citations for articles with positive altmetric scores in all cases with sufficient evidence (Twitter, Facebook wall posts, research highlights, blogs, mainstream media and forums) except perhaps for Google+ posts. Evidence was insufficient for LinkedIn, Pinterest, question and answer sites, and Reddit, and no conclusions should be drawn about articles with zero altmetric scores or the strength of any correlation between altmetrics and citations. Nevertheless, comparisons between citations and metric values for articles published at different times, even within the same year, can remove or reverse this association and so publishers and scientometricians should consider the effect of time when using altmetrics to rank articles. Finally, the coverage of all the altmetrics except for Twitter seems to be low and so it is not clear if they are prevalent enough to be useful in practice.
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          Why we buy what we buy: A theory of consumption values

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            Author and article information

            Journal
            2017-07-01
            1707.02283

            http://arxiv.org/licenses/nonexclusive-distrib/1.0/

            Custom metadata
            39 pages, 1 figure
            cs.DL

            Information & Library science

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