Citation Analysis of Mathematics and Statistics Dissertations and Theses from the University at Albany

Flynn, Kathleen

doi:10.1080/0194262x.2020.1727396

Cited by 7 publications

(2 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For instance, Card and DellaVigna (2013) discovered that older papers (pre‐1990) in Econometrics and Theory are more cited than recent ones in top journals from Economics (opposite pattern in Development and International Economics ). Another study on dissertations and thesis in Mathematics and Statistics reported that their cited materials are on average 19.9 years old and therefore suggest librarians not be afraid to purchase older materials (Flynn, 2020). Disciplines' behavior in distant knowledge inheritance is deeply embedded in their research traditions and informs the characteristics of their disciplinarity.…”

Section: Resultsmentioning

confidence: 99%

Knowledge inheritance in disciplines: Quantifying the successive and distant reuse of references

Zhou,

Dong,

Xia

2023

Asso for Info Science & Tech

View full text Add to dashboard Cite

How the knowledge base of disciplines grows, renews, and decays informs their distinct characteristics and epistemology. Here we track the evolution of knowledge bases of 19 disciplines for over 45 years. We introduce the notation of knowledge inheritance as the overlap in the set of references between years. We discuss two modes of knowledge inheritance of disciplines—successive and distant. To quantify the status and propensity of knowledge inheritance for disciplines, we propose two indicators: one descriptively describes knowledge base evolution, and one estimates the propensity of knowledge inheritance. When observing the continuity in knowledge bases for disciplines, we show distinct patterns for STEM and SS&H disciplines: the former inherits knowledge bases more successively, yet the latter inherits significantly from distant knowledge bases. We further discover stagnation or revival in knowledge base evolution where older knowledge base ceases to decay after 10 years (e.g., Physics and Mathematics) and are increasingly reused (e.g., Philosophy). Regarding the propensity of inheriting prior knowledge bases, we observe unanimous rises in both successive and distant knowledge inheritance. We show that knowledge inheritance could reveal disciplinary characteristics regarding the trajectory of knowledge base evolution and interesting insights into the metabolism and maturity of scholarly communication.

show abstract

Section: Resultsmentioning

confidence: 99%

Knowledge inheritance in disciplines: Quantifying the successive and distant reuse of references

Zhou,

Dong,

Xia

2023

Asso for Info Science & Tech

View full text Add to dashboard Cite

show abstract

“…Academic libraries have adopted a wide array of approaches to evaluate collections (i.e., citation analysis, interlibrary loan analysis, content analysis of syllabi, surveys, focus groups and interviews [4]. Previous citation studies have been used to analyze articles and disciplines including but not limited to engineering, computer science, math, and many others [5][6][7][8]. The literature continuously indicates the application of citation analysis to various research topics, core journals and supports the research needs of researchers.…”

Section: Literature Reviewmentioning

confidence: 99%

The Ties that Bind: Library E-Resources and Faculty Research

Wiley

2022 ASEE Annual Conference &Amp; Exposition Proceedings

View full text Add to dashboard Cite

Increasingly, academic libraries are becoming more interested in visualizing collection usage statistics to demonstrate return-on-investment analyses. Data visualization provides a detailed view that connects subscription resources provided by the library to researchers, students, and faculty. Institution blinded supports its university's commitment to teaching and research by providing access to subscription based print and electronic information resources. This study used several data science techniques to create visualizations from survey data and a citation analysis to (a) assess faculty perspectives on finding information and using library resources affiliated with Montana State University (MSU); (b) examine the citation data from articles written by faculty to determine the degree to which their current collection is supporting their faculty. This article shares the results of faculty responses to this survey and how well the library supports the needs of faculty. This type of analysis informs collection development decisions and assesses the strength of the library's collection and its relationship to scholarly communication. This project is a part of the LIS Education and Data Science integrated network group It is sponsored in partnership with

show abstract

A study of citations to STEM databases: ACM Digital Library, Engineering Village, IEEE Xplore, and MathSciNet

Tomaszewski

2021

Scientometrics

View full text Add to dashboard Cite

Citation Analysis of Mathematics and Statistics Dissertations and Theses from the University at Albany

Cited by 7 publications

References 17 publications

Knowledge inheritance in disciplines: Quantifying the successive and distant reuse of references

Knowledge inheritance in disciplines: Quantifying the successive and distant reuse of references

The Ties that Bind: Library E-Resources and Faculty Research

A study of citations to STEM databases: ACM Digital Library, Engineering Village, IEEE Xplore, and MathSciNet

Contact Info

Product

Resources

About