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首页> 外文会议>2014 IEEE/ACM Joint Conference on Digital Libraries >Do altmetrics follow the crowd or does the crowd follow altmetrics?
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Do altmetrics follow the crowd or does the crowd follow altmetrics?

机译：高度度量遵循人群吗？还是人群遵循高度度量？

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摘要

Changes are occurring in scholarly communication as scientific discourse and research activities spread across various social media platforms. In this paper, we study altmetrics on the article and journal levels, investigating whether the online attention received by research articles is related to scholarly impact or may be due to other factors. We define a new metric, Journal Social Impact (JSI), based on eleven data sources: CiteULike, Mendeley, F1000, blogs, Twitter, Facebook, mainstream news outlets, Google Plus, Pinterest, Reddit, and sites running Stack Exchange (Q&A). We compare JSI against diverse citation-based metrics, and find that JSI significantly correlates with a number of them. These findings indicate that online attention of scholarly articles is related to traditional journal rankings and favors journals with a longer history of scholarly impact. We also find that journal-level altmetrics have strong significant correlations among themselves, compared with the weak correlations among article-level altmetrics. Another finding is that Mendeley and Twitter have the highest usage and coverage of scholarly activities. Among individual altmetrics, we find that the readership of academic social networks have the highest correlations with citation-based metrics. Our findings deepen the overall understanding of altmetrics and can assist in validating them.
机译：随着科学演讲和研究活动遍布各种社交媒体平台，学术交流中正在发生变化。在本文中，我们研究了文章和期刊层面的高度度量，以调查研究文章在网上获得的关注是否与学术影响有关或可能是由其他因素引起的。我们基于11个数据源定义了一个新的指标，即Journal Social Impact（JSI）：CiteULike，Mendeley，F1000，博客，Twitter，Facebook，主流新闻媒体，Google Plus，Pinterest，Reddit和运行Stack Exchange（Q＆A）的网站。我们将JSI与基于引文的各种指标进行了比较，发现JSI与其中的许多显着相关。这些发现表明，对学术文章的在线关注与传统期刊排名有关，并倾向于具有较长学术影响力的期刊。我们还发现，与文章级别的高度度量之间的弱相关性相比，期刊级别的高度度量之间具有很强的相关性。另一个发现是Mendeley和Twitter具有最高的学术活动使用率和覆盖率。在单个测度中，我们发现学术社交网络的读者与基于引文的测度具有最高的相关性。我们的发现加深了对高度度量的整体理解，并可以帮助验证它们。

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