Journal of the Association for Information Science and Technology最新文献

{"title":"How do authors perceive the way their work is cited? Findings from a large-scale survey on quotation accuracy","authors":"Simon Wakeling,&nbsp;Monica Lestari Paramita,&nbsp;Stephen Pinfield","doi":"10.1002/asi.70000","DOIUrl":"10.1002/asi.70000","url":null,"abstract":"<p>It has long been recognized that there are issues with the appropriateness of citations in the academic literature. Citations of sources that do not support the statement they are cited against are known as quotation errors, and there have been many previous studies of their prevalence. The vast majority of these studies rely on researchers evaluating the accuracy of citations in a small sample of the literature, and show large variation in quotation error rates. In this article we report a novel approach to assessing quotation accuracy via an online survey in which 2648 corresponding authors of articles evaluated a real-world citation of their work. Respondents were also asked to categorize the perceived purpose of the citation, and what action, if any, they take when encountering inaccurate citations of their work. We found a quotation error rate of 16.6%, with no significant difference across academic disciplines, suggesting that variation in previous studies may be a result of methodological differences. Only 11.3% of respondents indicated they had taken action after encountering an inaccurate citation of their work. This work reveals reasons contributing to inaccurate quotations and issues with citation practices, and offers suggestions of areas for future research.</p>","PeriodicalId":48810,"journal":{"name":"Journal of the Association for Information Science and Technology","volume":"76 10","pages":"1396-1410"},"PeriodicalIF":4.3,"publicationDate":"2025-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://asistdl.onlinelibrary.wiley.com/doi/epdf/10.1002/asi.70000","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145062682","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The visual, the textual, and the one-dimensional: An exploration of the visual elements of bibliographic classification schemes","authors":"Deborah Lee","doi":"10.1002/asi.70001","DOIUrl":"10.1002/asi.70001","url":null,"abstract":"<p>Classification schemes are a key way of organizing bibliographic knowledge, yet the way that classification schemes communicate their information to classifiers receives little attention. This article takes a novel approach by exploring the visual aspects contained within classification schemes. The research uses a classification scheme analysis methodology. Three different classification scheme phenomena are discussed in terms of their visualization: hierarchy, notation, and notes. Indentation is found to be a significant—and implicit—method of communicating hierarchy to classifiers and offers intriguing solutions to the issues of transmuting from two dimensions into one. The visual elements of notation reveal a strong separation between notation and class, while the visual elements of notes illuminate a varying narrative around the position of notes in <i>the classification scheme</i>. A categorization system for visual elements in classification schemes is presented. Model 1 proffers visual elements as a fourth plane of classification, which extends and remodels Ranganathan's <i>Three Planes of Work</i>. Model 2 shows how visual elements could fit into classification scheme versioning. Ultimately, looking at visual aspects of classification schemes is a novel way of thinking about knowledge organization and can help us to better understand—and ultimately, to better use—classification schemes.</p>","PeriodicalId":48810,"journal":{"name":"Journal of the Association for Information Science and Technology","volume":"76 10","pages":"1411-1427"},"PeriodicalIF":4.3,"publicationDate":"2025-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://asistdl.onlinelibrary.wiley.com/doi/epdf/10.1002/asi.70001","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145062742","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Knowledge integration and diffusion structures of interdisciplinary research: A large-scale analysis based on propensity score matching","authors":"Jiawei Xu,&nbsp;Zhihan Zheng,&nbsp;Chao Min,&nbsp;Win-bin Huang,&nbsp;Yi Bu","doi":"10.1002/asi.25014","DOIUrl":"10.1002/asi.25014","url":null,"abstract":"<p>While facilitating science, interdisciplinary research (IDR) has a heavier cognitive burden for researchers compared to unidisciplinary research (UDR). Yet, little has been known about patterns of knowledge integration and diffusion structures of IDR. Here we adopt a causal inference strategy, namely propensity score matching, with all journal publications in 2005 in Microsoft Academic Graph to better understand the IDR effect in various research fields. We use the diversity of reference fields of one paper as the proxy of the paper's interdisciplinarity and estimate the effect of a research article being IDR on its knowledge integration and diffusion measured by its high-order citation/reference cascade. We find that, in disciplines where IDR articles are less popular, such as mathematics, physics, and chemistry, IDR needs a more extensive knowledge base than UDR to gain a similar number of citations. In disciplines where IDR articles are more popular, for example, psychology, geology, biology, and economics, a small knowledge base is enough for a high-impact IDR article. As to knowledge diffusion, no matter whether IDR or UDR, a more extensive knowledge base leads to stronger knowledge diffusion ability. Findings imply potential drawbacks of pure interdisciplinarity-oriented research policy; rather, the establishment of policies may vary across disciplines.</p>","PeriodicalId":48810,"journal":{"name":"Journal of the Association for Information Science and Technology","volume":"76 9","pages":"1210-1226"},"PeriodicalIF":4.3,"publicationDate":"2025-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144923610","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Semantic organization for historical maps: Classification, representation, association","authors":"Qi Xiaoying,&nbsp;Alton Y. K. Chua,&nbsp;Yang Haiping","doi":"10.1002/asi.25023","DOIUrl":"10.1002/asi.25023","url":null,"abstract":"<p>Given that historical maps (HM) are represented by a complex network of symbols, their semantics cannot be easily and directly understood. To extract the embedded knowledge, scholars have developed semantic organization for different types of HM. However, the construction of semantic organization for HM is challenging due to problems of semantic clutter, semantic loss, and semantic ambiguity. To resolve these problems, this paper proposes a semantic organization system which includes classification, representation, and association mechanisms for HM. The intent is to achieve semantic ordering, semantic enhancement, and semantic association. As a means to verify the proposed semantic organization system, this paper develops an HM knowledge question and answer (Q&amp;A) system. Experimental results show that the Q&amp;A system outperformed Baidu (Wenxinyiyan) and GPT-4o in terms of precision and recall.</p>","PeriodicalId":48810,"journal":{"name":"Journal of the Association for Information Science and Technology","volume":"76 10","pages":"1374-1395"},"PeriodicalIF":4.3,"publicationDate":"2025-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145062563","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The landscape of data reuse in interactive information retrieval: Motivations, sources, and evaluation of reusability","authors":"Tianji Jiang,&nbsp;Wenqi Li,&nbsp;Jiqun Liu","doi":"10.1002/asi.25020","DOIUrl":"10.1002/asi.25020","url":null,"abstract":"<p>Reusing research data can effectively reduce efforts in data collection and enhance the replicability of evaluation experiments, especially for small laboratories and research teams studying human-centered systems. Building a sustainable data reuse process and culture relies on frameworks that encompass policies, standards, roles, and responsibilities, all of which must address the diverse needs of data providers, curators, and reusers. This study investigated data reuse practices of experienced researchers in Interactive Information Retrieval (IIR), a field where data reuse has been strongly advocated but still remains a challenge. We conducted 21 semi-structured in-depth interviews with IIR researchers from varying demographic backgrounds, institutions, and career stages about their motivations, experiences, and concerns regarding data reuse. We uncovered the rationales, criteria, and strategies they used in reusability assessments, as well as the challenges they faced when attempting to reuse research data in their studies. These empirical findings enrich ongoing discussions about the reusability of user-generated data and research resources and help promote community-level data reuse culture and standards in both traditional and emerging IIR research fields.</p>","PeriodicalId":48810,"journal":{"name":"Journal of the Association for Information Science and Technology","volume":"76 9","pages":"1258-1276"},"PeriodicalIF":4.3,"publicationDate":"2025-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144923781","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The spatiotemporal relationship between usage data and topic popularity in scientific literature","authors":"Xianwen Wang,&nbsp;Wencan Tian,&nbsp;Ruonan Cai,&nbsp;Zhichao Fang","doi":"10.1002/asi.25019","DOIUrl":"10.1002/asi.25019","url":null,"abstract":"<p>This study explored the spatiotemporal relationship between usage data (measured by PDF downloads and HTML views) and topic popularity (measured by the number of publications) in scientific literature. Using a panel dataset of over 2.3 million papers and 130 million usage records from IEEE Xplore, we develop a theoretical framework grounded in attention economy theory and the competitive exclusion principle. By using fixed effects model, the instrumental variable method, and the spatial Durbin model, we discover that how often a topic is used greatly increases its future popularity, while usage data from related topics have a negative impact. This study provides solid preliminary evidence for using usage data in detecting research hotspots. Additionally, this study innovatively proposes two methods for constructing spatial weight matrices based on topic semantic vectors, offering a concrete pathway for integrating spatial econometrics with spatial scientometrics.</p>","PeriodicalId":48810,"journal":{"name":"Journal of the Association for Information Science and Technology","volume":"76 9","pages":"1241-1257"},"PeriodicalIF":4.3,"publicationDate":"2025-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144923780","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correction to “The enhanced research impact of self-archiving platforms: Evidence from bioRxiv”","authors":"","doi":"10.1002/asi.25022","DOIUrl":"10.1002/asi.25022","url":null,"abstract":"<p>Liu, H., Hu, G., &amp; Li, Y. (2024). The enhanced research impact of self-archiving platforms: Evidence from bioRxiv. <i>Journal of the Association for Information Science and Technology</i>, <i>75</i>(8), 883–897. https://doi.org/10.1002/asi.24932</p><p>This correction has been published following concerns raised by a third party regarding limitations of the data set and analyses presented in the article and the undisclosed modification of the authors’ supporting online dataset following publication.</p><p><i>“The statistical similarity between the treatment and control groups was assessed by a t-test. In our analysis, t-tests were an integral part of the matching procedures, with the null hypothesis being that ‘the variables in the treatment and control groups have equal means’. The results of the t-tests for our treatment and control samples were as follows</i>:</p><p><b><i>TABLE 1</i></b> <i>Results of the t-test for the treatment and control groups</i>.\u0000 </p><p><i>“The decision to include non-research articles in the control group was based on the fact that bioRxiv deposits include all four types of articles. Since we are examining the overall impact of bioRxiv, it was appropriate to include these article types. Nevertheless, when we excluded non-research articles and reran the regression analysis, the main effect remained significant (0.222***)</i>.</p><p><i>“The data acquisition date for Altmetrics differs from that for citation data due to the nature of our study. We measured online exposure between deposition dates and publication dates to estimate its impact. All papers in the treatment group were published before October 2020, and Altmetrics data were collected soon after to avoid potential contamination from web data that could occur over time. In contrast, citation data were collected later, in 2022, with complete citation records up to the end of 2021.”</i></p><p>After being informed about the concerns, the authors made post-publication changes to their original dataset without appropriately stating this in a correction. After acknowledging their mistake, the original, unmodified data set (“Detailed version”) and the consolidated dataset prepared for regression analysis (“Integrated version”) were both made available with an additional explanation regarding the files listed as Supplementary Data. Additionally, the authors have provided the STATA codes used in the analyses, along with article identifiers in the integrated panel dataset to facilitate replication of the study. The authors apologize for this oversight.</p><p>Please find the link to the updated supporting dataset, here: https://yunpan.tongji.edu.cn/link/AA5DD75818FCD24946BBCEBEF0C2BAB9CA.</p>","PeriodicalId":48810,"journal":{"name":"Journal of the Association for Information Science and Technology","volume":"76 8","pages":"1141-1142"},"PeriodicalIF":4.3,"publicationDate":"2025-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/asi.25022","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144767973","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Data sources used in bibliometrics 1978–2022: From proprietary databases to the great wide open","authors":"Camilla Hertil Lindelöw,&nbsp;Björn Hammarfelt,&nbsp;Alysson Mazoni","doi":"10.1002/asi.25018","DOIUrl":"10.1002/asi.25018","url":null,"abstract":"<p>Traditionally, the bibliometric community has relied heavily on secondary data sources, most prominently the Science Citation Index. By analyzing three key journals, we detected trends in the data sources used over a 45-year period (1978–2022). The historical analysis of data sources reveals a consistency in the materials used as well as bursts of new materials and approaches. On a larger scale, the pattern is stable with Web of Science and Scopus dominating, but this might be about to change. The complexity of the research performed in bibliometrics does not seem to increase as a vast majority of studies use one or two types of data sources despite the increasing availability of data. A more detailed analysis detects trends in the use of data, as represented by patent analyses in the 1980s, webometrics in the late 1990s, and altmetrics in the 2010s. Overall, the paper provides an analytical overview of current and historical data sources used in bibliometrics, which may guide and inspire further research. The question remaining, however, is how the current emphasis on open sources will transform the field in the future: are we entering the great wide open, or will established proprietary databases remain a dominating source?</p>","PeriodicalId":48810,"journal":{"name":"Journal of the Association for Information Science and Technology","volume":"76 9","pages":"1227-1240"},"PeriodicalIF":4.3,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://asistdl.onlinelibrary.wiley.com/doi/epdf/10.1002/asi.25018","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144923639","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessing the societal influence of academic research with ChatGPT: Impact case study evaluations","authors":"Kayvan Kousha,&nbsp;Mike Thelwall","doi":"10.1002/asi.25021","DOIUrl":"10.1002/asi.25021","url":null,"abstract":"<p>Academics and departments are sometimes judged by how their research has benefited society. For example, the UK's Research Excellence Framework (REF) assesses Impact Case Studies (ICSs), which are five-page evidence-based claims of societal impacts. This article investigates whether ChatGPT can evaluate societal impact claims and therefore potentially support expert human assessors. For this, various parts of 6220 public ICSs from REF2021 were fed to ChatGPT 4o-mini along with the REF2021 evaluation guidelines, comparing ChatGPT's predictions with published departmental average ICS scores. The results suggest that the optimal strategy for high correlations with expert scores is to input the title and summary of an ICS but not the remaining text and to modify the original REF guidelines to encourage a stricter evaluation. The scores generated by this approach correlated positively with departmental average scores in all 34 Units of Assessment (UoAs), with values between 0.18 (Economics and Econometrics) and 0.56 (Psychology, Psychiatry and Neuroscience). At the departmental level, the corresponding correlations were higher, reaching 0.71 for Sport and Exercise Sciences, Leisure and Tourism. Thus, ChatGPT-based ICS evaluations are simple and viable to support or cross-check expert judgments, although their value varies substantially between fields.</p>","PeriodicalId":48810,"journal":{"name":"Journal of the Association for Information Science and Technology","volume":"76 10","pages":"1357-1373"},"PeriodicalIF":4.3,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://asistdl.onlinelibrary.wiley.com/doi/epdf/10.1002/asi.25021","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145062662","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The woman researcher's tale: A review of bibliometric methods and results for studying gender in science","authors":"Elvira González-Salmón,&nbsp;Zaida Chinchilla-Rodríguez,&nbsp;Nicolas Robinson-Garcia","doi":"10.1002/asi.25012","DOIUrl":"10.1002/asi.25012","url":null,"abstract":"<p>There has been a notable increase in bibliometric research studying gender in academia. This narrative review aims to organize and synthesize this extensive body of work to uncover new insights into gender disparities in science. We begin by analyzing key methodological elements, including gender assignment techniques, units of analysis, and causality issues. Next, we identify and categorize the main findings of the literature into three groups: differences in academia, causes behind these differences, and their primary consequences. Finally, we point out gaps in the literature and propose new lines of inquiry to address these gaps. These proposals include more rigorous gender assignment algorithms, fostering comparability of studies, exploring a broader range of topics, and improving the interpretability and context of results when studying gender.</p>","PeriodicalId":48810,"journal":{"name":"Journal of the Association for Information Science and Technology","volume":"76 9","pages":"1188-1209"},"PeriodicalIF":4.3,"publicationDate":"2025-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://asistdl.onlinelibrary.wiley.com/doi/epdf/10.1002/asi.25012","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144923438","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}