<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Datasets | Yiyang "Diana" Wang</title><link>https://hello-diana.github.io/tags/datasets/</link><atom:link href="https://hello-diana.github.io/tags/datasets/index.xml" rel="self" type="application/rss+xml"/><description>Datasets</description><generator>Hugo Blox Builder (https://hugoblox.com)</generator><language>en-us</language><lastBuildDate>Sat, 12 Oct 2024 00:00:00 +0000</lastBuildDate><image><url>https://hello-diana.github.io/media/icon_hu_3520ea6f5cfedd63.png</url><title>Datasets</title><link>https://hello-diana.github.io/tags/datasets/</link></image><item><title>Scito2M: A 2 Million, 30-Year Cross-disciplinary Dataset for Temporal Scientometric Analysis</title><link>https://hello-diana.github.io/publication/jin-scito-2-m-2024/</link><pubDate>Sat, 12 Oct 2024 00:00:00 +0000</pubDate><guid>https://hello-diana.github.io/publication/jin-scito-2-m-2024/</guid><description>&lt;h2 id="abstract">Abstract&lt;/h2>
&lt;p>We introduce &lt;strong>Scito2M&lt;/strong> (also released as the &lt;strong>SciEvo&lt;/strong> dataset), a longitudinal scientometric dataset with over two million academic publications, with content information and citation graphs supporting cross-disciplinary analyses. A 30-year temporal study reveals disparities in epistemic cultures, knowledge production modes, and citation practices across fields. The work received the &lt;strong>Best Paper Award&lt;/strong> at the Good Data @ AAAI 2025 Workshop.&lt;/p></description></item></channel></rss>