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#scopus

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Serhii Nazarovets<p>New <a href="https://mstdn.science/tags/preprint" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>preprint</span></a> 📢 - Can <a href="https://mstdn.science/tags/OpenAlex" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>OpenAlex</span></a> compete with <a href="https://mstdn.science/tags/Scopus" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Scopus</span></a> in bibliometric analysis?</p><p>👉 <a href="https://arxiv.org/abs/2502.18427" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="">arxiv.org/abs/2502.18427</span><span class="invisible"></span></a></p><p><span class="h-card" translate="no"><a href="https://mastodon.social/@OpenAlex" class="u-url mention" rel="nofollow noopener noreferrer" target="_blank">@<span>OpenAlex</span></a></span> has broader coverage and shows higher correlation with certain expert assessments.</p><p>At the same time, it has issues with metadata completeness and document classification.</p><p>❗ Most intriguingly: it turns out that raw <a href="https://mstdn.science/tags/citation" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>citation</span></a> counts perform just as well, and in some cases even better, than normalized indicators, which have long been considered the standard in <a href="https://mstdn.science/tags/scientometrics" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>scientometrics</span></a>.</p>
Ludo Waltman<p>Earlier this week an opinion piece authored by me and a number of great colleagues was published on the <span class="h-card" translate="no"><a href="https://scicomm.xyz/@upstream" class="u-url mention" rel="nofollow noopener noreferrer" target="_blank">@<span>upstream</span></a></span> blog. Our piece introduces criteria for innovation-friendly bibliographic databases <a href="https://doi.org/10.54900/d3ck1-skq19" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="">doi.org/10.54900/d3ck1-skq19</span><span class="invisible"></span></a>.</p><p>We express our deep concerns about the treatment of <span class="h-card" translate="no"><a href="https://fediscience.org/@eLife" class="u-url mention" rel="nofollow noopener noreferrer" target="_blank">@<span>eLife</span></a></span> by the <a href="https://social.cwts.nl/tags/WebOfScience" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>WebOfScience</span></a> and <a href="https://social.cwts.nl/tags/Scopus" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Scopus</span></a> databases. We see this as an example of databases hindering rather than supporting innovation in scholarly communication and research assessment.</p><p><span class="h-card" translate="no"><a href="https://social.cwts.nl/@cwts" class="u-url mention" rel="nofollow noopener noreferrer" target="_blank">@<span>cwts</span></a></span></p>
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