EDBT 2026 Demo / reviewers in the wild / expert
Ying Huang 0002
dblp:62/2964-2
· DBLP profile ↗
4ranked-venue papers
0as first author
4since 2021 · last 2025
0000-0003-0115-4581ORCID · verified
Domains — the database's venue-derived domains; a paper can count in several
Databases, data management, data science and information retrieval · 4 · 4 since 2021
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | How does scientific research influence policymaking? A study of four types of citation pathways between research articles and AI policy documentsabstractAbstract The importance of evidence‐based policymaking is widely recognized, but how science influences policy remains insufficiently explored. This study aims to examine how policy documents cite research articles, thereby tracing the complex impact process of scientific research on policymaking. A conceptual model is proposed to classify four types of citation pathways by distinguishing between direct and indirect impacts and observing whether a reinforcement effect is present. To operationalize this model, we collected nearly 10 thousand policy documents related to artificial intelligence (AI) and over 1.6 million links between these policies and their referenced articles. A large‐scale data analysis and a case study were conducted. Results exhibit distinct citation pathways among specific types of institutions, geopolitical areas, and policy areas. Indirect influences emerge as an important mechanism. Research articles from EU countries primarily serve the policymaking of inter‐governmental organizations (IGOs) and the EU, while research articles from the USA significantly support both domestic and foreign policymaking. Notably, IGOs serve as key intermediaries, facilitating the indirect influence of research on policymaking. In addition, while the knowledge from the social sciences provides substantial support for policies in various areas, an increasing involvement of the natural sciences in the development of AI‐related policies is found. Lin Zhang 0004, Ying Huang 0002, Gunnar Sivertsen |
J. Assoc. Inf. Sci. Technol. | 3 |
| 2024 | How do life sciences cite social sciences? Characterizing the volume and trajectory of citationsabstractAbstract Social sciences are increasingly recognized as significant for building a sustainable world since the social perspective can assist researchers in other fields in navigating public controversy and designing more responsible interaction mechanisms between the natural and social systems. However, the question arises: to what extent do natural sciences rely on social science research in their studies? Examining life science publications from seven PLoS journals, this paper attempts to characterize the volume and trajectory of citations from life sciences to social sciences. We explore three core questions: To what extent do life sciences cite social sciences? What actors in the life sciences are citing social sciences? Which actors in the social sciences are being cited? Our analysis estimates social sciences influence 15%–19% of life science publications, contributing to 1.1%–1.5% of references in 2018. Social science citers are found across peripheral and central topics of life science disciplines. Cited social science publications exhibit various levels of interdisciplinarity and achieve the greatest citation impact among peers. Citations to social sciences are prevalent in both theoretically and methodologically oriented sections. We show empirically the increasing impact of social sciences on the development of the life sciences. Beibei Sun, Raf Guns, Tim C. E. Engels, Ying Huang 0002, Lin Zhang 0004 |
J. Assoc. Inf. Sci. Technol. | 5 |
| 2023 | Who tweets scientific publications? A large-scale study of tweeting audiences in all areas of researchabstractAbstract The purpose of this study is to investigate the validity of tweets about scientific publications as an indicator of societal impact by measuring the degree to which the publications are tweeted beyond academia. We introduce methods that allow for using a much larger and broader data set than in previous validation studies. It covers all areas of research and includes almost 40 million tweets by 2.5 million unique tweeters mentioning almost 4 million scientific publications. We find that, although half of the tweeters are external to academia, most of the tweets are from within academia, and most of the external tweets are responses to original tweets within academia. Only half of the tweeted publications are tweeted outside of academia. We conclude that, in general, the tweeting of scientific publications is not a valid indicator of the societal impact of research. However, publications that continue being tweeted after a few days represent recent scientific achievements that catch attention in society. These publications occur more often in the health sciences and in the social sciences and humanities. Lin Zhang 0004, Zhenyu Gou, Zhichao Fang, Gunnar Sivertsen, Ying Huang 0002 |
J. Assoc. Inf. Sci. Technol. | 5 |
| 2022 | Uses of the Journal Impact Factor in national journal rankings in China and EuropeabstractAbstract This paper investigates different uses of the Journal Impact Factor (JIF) in national journal rankings and discusses the merits of supplementing metrics with expert assessment. Our focus is national journal rankings used as evidence to support decisions about the distribution of institutional funding or career advancement. The seven countries under comparison are China, Denmark, Finland, Italy, Norway, Poland, and Turkey—and the region of Flanders in Belgium. With the exception of Italy, top‐tier journals used in national rankings include those classified at the highest level, or according to tier, or points implemented. A total of 3,565 (75.8%) out of 4,701 unique top‐tier journals were identified as having a JIF, with 55.7% belonging to the first Journal Impact Factor quartile. Journal rankings in China, Flanders, Poland, and Turkey classify journals with a JIF as being top‐tier, but only when they are in the first quartile of the Average Journal Impact Factor Percentile. Journal rankings that result from expert assessment in Denmark, Finland, and Norway regularly classify journals as top‐tier outside the first quartile, particularly in the social sciences and humanities. We conclude that experts, when tasked with metric‐informed journal rankings, take into account quality dimensions that are not covered by JIFs. Emanuel Kulczycki, Ying Huang 0002, Alesia A. Zuccala, Tim C. E. Engels, Antonio Ferrara 0002, Raf Guns, Janne Pölönen, Gunnar Sivertsen, Zehra Taskin, Lin Zhang 0004 |
J. Assoc. Inf. Sci. Technol. | 2 |