skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

Explore Research Products in the PAR
It may take a few hours for recently added research products to appear in PAR search results.


Title: The Affective Science Network: A Fieldwide Map of over 1 Million Citations
Abstract Research in affective science includes over one hundred thousand articles, the vast majority of which have been published in only the past two decades. The size and rapid growth of this field have led to unique challenges for the twenty-first-century scientist including how to develop both breadth and depth of scholarship, curb siloing and promote integrative and interdisciplinary framework, and represent and monitor the field in its entirety. Here, we help address these issues by compactly mapping out this enormous field using citation network analysis (CNA). We generated a citation matrix of over 100,000 publications and over 1 million citations since the seminal works on emotion by Charles Darwin (1872) and William James (1884). Using graph theory metric and content analysis of titles and abstracts, we identified and characterized the contents of 69 research communities, their most influential articles, and their interconnectedness with each other. We further identified potential “missed connections” between communities that share similar content but do not have strong citation-based connections. In doing so, we establish the first, low-dimensional representation, or field-wide map, of a substantial portion of the affective sciences literature. This panoramic view of the field provides affective and non-affective scientists alike with the means to rapidly survey dozens of major research communities and topics in the field, guide scholarship development, and identify gaps and connections for developing an integrative science.  more » « less
Award ID(s):
2241938
PAR ID:
10569536
Author(s) / Creator(s):
; ; ;
Publisher / Repository:
Springer Science + Business Media
Date Published:
Journal Name:
Affective Science
Volume:
6
Issue:
2
ISSN:
2662-2041
Format(s):
Medium: X Size: p. 321-339
Size(s):
p. 321-339
Sponsoring Org:
National Science Foundation
More Like this
  1. ; ; ; ; (, Australian Journal of Environmental Education)
    null (Ed.)
    Abstract Sense of place describes both affective and cognitive — emotional and intellectual — connections to place. Affective outcomes, tied to arts and humanities education, can facilitate these connections. But little research explores environmental science, arts and humanities (eSAH) curricula on place relationships. Additionally, most research on the sense of place focuses on repeated visits to a place over time, rather than short-term experiences like a field trip. Finally, digital technology is a growing trend across science education, but little research investigates its use in field-based contexts. Our research begins to address these gaps. This article describes an eSAH field trip for middle and high school learners. Using a conventional content analysis, we present pilot data from two high school field trips. Our findings illuminate a framework for understanding active and passive place relationships in the context of short-term interdisciplinary field learning experiences. 
    more » « less
  2. ; (, Harvard Data Science Review)
    What do we know about data science learning at the grades K–12 (precollegiate) level? This article answers this question by using the notion of agency to provide a framework to review the diverse research agendas and learning environments relevant to data science education. Examining research on data science education published in three recent special issues, we highlight key findings from scholars working in different communities using this lens. Then, we present the results of a co-citation coupling analysis for articles published in one of three recent data science education special issues with research spanning various levels and contexts. This co-citation analysis showed that while there are some common touchpoints, research on data science learning is taking place in a siloed manner. Based on our review of the literature through the lens of agency and our analysis, we discuss how the data science education community can synthesize research across disciplinary and grade-level divides. 
    more » « less
  3. ; (, American Sociological Review)
    null (Ed.)
    Communication of scientific findings is fundamental to scholarly discourse. In this article, we show that academic review articles, a quintessential form of interpretive scholarly output, perform curatorial work that substantially transforms the research communities they aim to summarize. Using a corpus of millions of journal articles, we analyze the consequences of review articles for the publications they cite, focusing on citation and co-citation as indicators of scholarly attention. Our analysis shows that, on the one hand, papers cited by formal review articles generally experience a dramatic loss in future citations. Typically, the review gets cited instead of the specific articles mentioned in the review. On the other hand, reviews curate, synthesize, and simplify the literature concerning a research topic. Most reviews identify distinct clusters of work and highlight exemplary bridges that integrate the topic as a whole. These bridging works, in addition to the review, become a shorthand characterization of the topic going forward and receive disproportionate attention. In this manner, formal reviews perform creative destruction so as to render increasingly expansive and redundant bodies of knowledge distinct and comprehensible. 
    more » « less
  4. ; ; ; ; ; ; ; ; (, Ecosphere)
    Abstract Ecologists—especially those new to the field—are tasked with finding relevant literature matching their research interests and deciding upon a suitable venue for the publication of their work. To provide a roadmap for early career researchers to identify journals aligned with their interests, we analyzed major research themes found across the top 30 ecology journals and three high‐impact multi‐disciplinary journals (Nature, PNAS,andScience), utilizing an automated content analysis (ACA) of 84,841 article abstracts, titles, and author keywords published over the last four decades. Journals clustered into 10 distinct groups based on 46 research themes identified byACA. We examined the frequency of ecological themes in each of these journal groups to identify the journals most associated with each theme. We found three themes (anthropogenic impacts, disease,andtraits) that occurred at a high frequency in the high‐impact multi‐disciplinary journal group containingNature, PNAS,andScience. Themes that increased in frequency over the last four decades, such asclimate change, traits, anthropogenic, andcellular biology, were found more often in journals with higher impact factors, indicating that emerging research themes in ecology will likely become of interest to a broader readership over time. Our study provides a thematic review as a potential roadmap for junior ecologists to browse and publish journal articles. 
    more » « less
  5. ; ; ; (, On the use of the arXiv as a dataset)
    The arXiv has collected 1.5 million pre-print articles over 28 years, hosting literature from scientific fields including Physics, Mathematics, and Computer Science. Each pre-print features text, figures, authors, citations, categories, and other metadata. These rich, multi-modal features, combined with the natural graph structure—created by citation, affiliation, and co-authorship—makes the arXiv an exciting candidate for benchmarking next-generation models. Here we take the first necessary steps toward this goal, by providing a pipeline which standardizes and simplifies access to the arXiv’s publicly available data. We use this pipeline to extract and analyze a 6.7 million edge citation graph, with an 11 billion word cor- pus of full-text research articles. We present some baseline classification results, and motivate application of more exciting generative graph models. 
    more » « less
  • Citation Formats
  • MLA
  • APA
  • Chicago
  • BibTeX
  • Save / Share this Record
  • Send to Email