Search (59 results, page 1 of 3)

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Abstract

To what extent is the destiny of a scientific paper shaped by the cocitation network in which it is involved? What are the social contexts that can explain these structuring? Using bibliometric data, interviews with researchers, and social network analysis, this article proposes a typology based on egocentric cocitation networks that displays a quadruple structuring (before and after publication): polarization, clusterization, atomization, and attrition. It shows that the academic capital of the authors and the intellectual resources of their research are key factors of these destinies, as are the social relations between the authors concerned. The circumstances of the publishing are also correlated with the structuring of the egocentric cocitation networks, showing how socially embedded they are. Finally, the article discusses the contribution of these original networks to the analyze of scientific production and its dynamics.

Date

21. 3.2023 19:22:14

Source

Journal of the Association for Information Science and Technology. 74(2023) no.4, S.415-433

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Abstract

This is the first study that evaluated the coverage of journals from Africa in Web of Science, Scopus, and CrossRef. A list of active journals published in each of the 55 African countries was compiled from Ulrich's periodicals directory and African Journals Online (AJOL) website. Journal master lists for Web of Science, Scopus, and CrossRef were searched for the African journals. A total of 2,229 unique active African journals were identified from Ulrich (N = 2,117, 95.0%) and AJOL (N = 243, 10.9%) after removing duplicates. The volume of African journals in Web of Science and Scopus databases is 7.4% (N = 166) and 7.8% (N = 174), respectively, compared to the 45.6% (N = 1,017) covered in CrossRef. While making up only 17.% of all the African journals, South African journals had the best coverage in the two most authoritative databases, accounting for 73.5% and 62.1% of all the African journals in Web of Science and Scopus, respectively. In contrast, Nigeria published 44.5% of all the African journals. The distribution of the African journals is biased in favor of Medical, Life and Health Sciences and Humanities and the Arts in the three databases. The low representation of African journals in CrossRef, a free indexing infrastructure that could be harnessed for building an African-centric research indexing database, is concerning.

Date

22. 6.2023 14:09:06

Object

Web of Science

Source

Journal of the Association for Information Science and Technology. 74(2023) no.7, S.745-758

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Abstract

This article discusses how letters to the editor boost publishing metrics for journals and authors, and then examines letters published since 2015 in six elite journals, including the Journal of the Association for Information Science and Technology. The initial findings identify some potentially anomalous use of letters and unusual self-citation patterns. The article proposes that Clarivate Analytics consider slightly reconfiguring the Journal Impact Factor to more fairly account for letters and that journals transparently explain their letter submission policies.

Date

6. 4.2022 19:22:26

Source

Journal of the Association for Information Science and Technology. 73(2022) no.5, S.702-707

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Abstract

Purpose The purpose of the paper is to analyse the interactions of bridging users in Twitter discussions about vaccination. Design/methodology/approach Conversational threads were collected through filtering the Twitter stream using keywords and the most active participants in the conversations. Following data collection and anonymisation of tweets and user profiles, a retweet network was created to find users bridging the main clusters. Four conversations were selected, ranging from 456 to 1,983 tweets long, and then analysed through content analysis. Findings Although different opinions met in the discussions, a consensus was rarely built. Many sub-threads involved insults and criticism, and participants seemed not interested in shifting their positions. However, examples of reasoned discussions were also found. Originality/value The study analyses conversations on Twitter, which is rarely studied. The focus on the interactions of bridging users adds to the uniqueness of the paper.

Date

20. 1.2015 18:30:22

Source

Aslib journal of information management. 73(2021) no.1, S.129-143

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Abstract

The paper reports a longitudinal analysis of the topical and methodological development of Library and Information Science (LIS). Its focus is on the effects of researchers' disciplines on these developments. The study extends an earlier cross-sectional study (Vakkari et al., Journal of the Association for Information Science and Technology, 2022a, 73, 1706-1722) by a coordinated dataset representing a content analysis of articles published in 31 scholarly LIS journals in 1995, 2005, and 2015. It is novel in its coverage of authors' disciplines, topical and methodological aspects in a coordinated dataset spanning two decades thus allowing trend analysis. The findings include a shrinking trend in the share of LIS from 67 to 36% while Computer Science, and Business and Economics increase their share from 9 and 6% to 21 and 16%, respectively. The earlier cross-sectional study (Vakkari et al., Journal of the Association for Information Science and Technology, 2022a, 73, 1706-1722) for the year 2015 identified three topical clusters of LIS research, focusing on topical subfields, methodologies, and contributing disciplines. Correspondence analysis confirms their existence already in 1995 and traces their development through the decades. The contributing disciplines infuse their concepts, research questions, and approaches to LIS and may also subsume vital parts of LIS in their own structures of knowledge production.

Date

22. 6.2023 18:15:06

Source

Journal of the Association for Information Science and Technology. 74(2023) no.7, S.811-827

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Abstract

Compared to previous studies that generally detect scientific breakthroughs based on citation patterns, this article proposes a knowledge entity-based disruption indicator by quantifying the change of knowledge directly created and inspired by scientific breakthroughs to their evolutionary trajectories. Two groups of analytic units, including MeSH terms and their co-occurrences, are employed independently by the indicator to measure the change of knowledge. The effectiveness of the proposed indicators was evaluated against the four datasets of scientific breakthroughs derived from four recognition trials. In terms of identifying scientific breakthroughs, the proposed disruption indicator based on MeSH co-occurrences outperforms that based on MeSH terms and three earlier citation-based disruption indicators. It is also shown that in our indicator, measuring the change of knowledge inspired by the focal paper in its evolutionary trajectory is a larger contributor than measuring the change created by the focal paper. Our study not only offers empirical insights into conceptual understanding of scientific breakthroughs but also provides practical disruption indicator for scientists and science management agencies searching for valuable research.

Date

22. 1.2023 18:37:33

Source

Journal of the Association for Information Science and Technology. 74(2023) no.2, S.150-167

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Abstract

Predicting a researcher's knowledge trajectories beyond their current foci can leverage potential inter-/cross-/multi-disciplinary interactions to achieve exploratory innovation. In this study, we present a method of diffusion-based network analytics for knowledge trajectory recommendation. The method begins by constructing a heterogeneous bibliometric network consisting of a co-topic layer and a co-authorship layer. A novel link prediction approach with a diffusion strategy is then used to capture the interactions between social elements (e.g., collaboration) and knowledge elements (e.g., technological similarity) in the process of exploratory innovation. This diffusion strategy differentiates the interactions occurring among homogeneous and heterogeneous nodes in the heterogeneous bibliometric network and weights the strengths of these interactions. Two sets of experiments-one with a local dataset and the other with a global dataset-demonstrate that the proposed method is prior to 10 selected baselines in link prediction, recommender systems, and upstream graph representation learning. A case study recommending knowledge trajectories of information scientists with topical hierarchy and explainable mediators reveals the proposed method's reliability and potential practical uses in broad scenarios.

Date

22. 6.2023 18:07:12

Source

Journal of the Association for Information Science and Technology. 74(2023) no.7, S.775-790

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Abstract

Purpose Public attitudes towards COVID-19 and social distancing are critical in reducing its spread. It is therefore important to understand public reactions and information dissemination in all major forms, including on social media. This article investigates important issues reflected on Twitter in the early stages of the public reaction to COVID-19. Design/methodology/approach A thematic analysis of the most retweeted English-language tweets mentioning COVID-19 during March 10-29, 2020. Findings The main themes identified for the 87 qualifying tweets accounting for 14 million retweets were: lockdown life; attitude towards social restrictions; politics; safety messages; people with COVID-19; support for key workers; work; and COVID-19 facts/news. Research limitations/implications Twitter played many positive roles, mainly through unofficial tweets. Users shared social distancing information, helped build support for social distancing, criticised government responses, expressed support for key workers and helped each other cope with social isolation. A few popular tweets not supporting social distancing show that government messages sometimes failed. Practical implications Public health campaigns in future may consider encouraging grass roots social web activity to support campaign goals. At a methodological level, analysing retweet counts emphasised politics and ignored practical implementation issues. Originality/value This is the first qualitative analysis of general COVID-19-related retweeting.

Date

20. 1.2015 18:30:22

Source

Aslib journal of information management. 72(2020) no.6, S.945-962

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Abstract

During the coronavirus pandemic, changes in the way science is done and shared occurred, which motivates meta-research to help understand science communication in crises and improve its effectiveness. The objective is to study how many Spanish scientific papers on COVID-19 published during 2020 share their research data. Qualitative and descriptive study applying nine attributes: (a) availability, (b) accessibility, (c) format, (d) licensing, (e) linkage, (f) funding, (g) editorial policy, (h) content, and (i) statistics. We analyzed 1,340 papers, 1,173 (87.5%) did not have research data. A total of 12.5% share their research data of which 2.1% share their data in repositories, 5% share their data through a simple request, 0.2% do not have permission to share their data, and 5.2% share their data as supplementary material. There is a small percentage that shares their research data; however, it demonstrates the researchers' poor knowledge on how to properly share their research data and their lack of knowledge on what is research data.

Date

21. 3.2023 19:22:02

Source

Journal of the Association for Information Science and Technology. 74(2023) no.4, S.402-414

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Abstract

Collaboration is encouraged because it is believed to improve academic research, supported by indirect evidence in the form of more coauthored articles being more cited. Nevertheless, this might not reflect quality but increased self-citations or the "audience effect": citations from increased awareness through multiple author networks. We address this with the first science wide investigation into whether author numbers associate with journal article quality, using expert peer quality judgments for 122,331 articles from the 2014-20 UK national assessment. Spearman correlations between author numbers and quality scores show moderately strong positive associations (0.2-0.4) in the health, life, and physical sciences, but weak or no positive associations in engineering and social sciences, with weak negative/positive or no associations in various arts and humanities, and a possible negative association for decision sciences. This gives the first systematic evidence that greater numbers of authors associates with higher quality journal articles in the majority of academia outside the arts and humanities, at least for the UK. Positive associations between team size and citation counts in areas with little association between team size and quality also show that audience effects or other nonquality factors account for the higher citation rates of coauthored articles in some fields.

Date

22. 6.2023 18:11:50

Source

Journal of the Association for Information Science and Technology. 74(2023) no.7, S.791-810

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Abstract

In the context of the increasing global connectivity in science, this article investigates the internal heterogeneity of international research collaborations (IRCs). We focus on the prevalence of shared heritage collaborations and the rise of multiple institutional affiliations as a collaboration mechanism. An analytical typology of IRCs based on the characteristics of collaborating researchers' location and heritage is developed and empirically tested on the dataset of Russia's publications in 2015. We found that shared heritage IRC and IRC via multiple affiliations are the cornerstones of internationalization. Significant structural differences are revealed between conventional IRC and these nonconventional IRCs across fields of science, locations, visibility of international partners, and the sources of funding. These results contribute towards a better understanding of IRC as a complex, heterogeneous phenomenon, which encompasses a variety of arrangements for knowledge creation across borders. A more nuanced understanding of IRC is needed for smarter university strategy, metric development, and policymaking.

Source

Journal of the Association for Information Science and Technology. 75(2023) no.2, S.97-114

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Abstract

To ascertain the diffusion and influence of Savolainen's ELIS model and its use as a theoretical and/or methodological basis for research. Design/methodology/approach A context citation analysis was made of the work where this researcher published his model. Analysis covered the year of publication, the type of work and the subject matter of the citing documents concerned. In-context citations were analysed for their frequency in each citing text, style, location and content cited. Findings The ELIS model received 18.5 cites/year. 20.2 per cent of them corresponded to papers published in journals in other areas, mainly computer science. The average of cites per paper was 1.8; 64.5 percent of the citing works cited them only once. 60 per cent of the cites were considered essential. Only 13.7 per cent of these cites appear in theory or methods. 37 per cent of the citing documents contained no concept relating to the model. Research limitations/implications The method used focuses on the most direct context of a cite (sentence or paragraph), but isolates it from the general context (full document, other documents by the author or their social capital). It has, however, allowed this research issue to be dealt with under laboratory conditions and revealed nuances hidden by the absolute number of cites. Originality/value It has become evident that the dissemination and influence of the ELIS model are less than what the total number of cites indicates and that it has scarcely been incorporated into research design. Despite its popularity, it is not being validated and/or refuted by way of empirical data.

Source

Journal of documentation. 76(2020) no.5, S.1069-1089

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Abstract

Theory is a kind of condensed human knowledge. This paper is to examine the mechanism of interdisciplinary diffusion of theoretical knowledge by tracing the diffusion of a representative theory, the Technology Acceptance Model (TAM). Design/methodology/approach Based on the full-scale dataset of Web of Science (WoS), the citations of Davis's original work about TAM were analysed and the interdisciplinary diffusion paths of TAM were delineated, a supervised machine learning method was used to extract theory incidents, and a content analysis was used to categorize the patterns of theory evolution. Findings It is found that the diffusion of a theory is intertwined with its evolution. In the process, the role that a participating discipline play is related to its knowledge distance from the original disciplines of TAM. With the distance increases, the capacity to support theory development and innovation weakens, while that to assume analytical tools for practical problems increases. During the diffusion, a theory evolves into new extensions in four theoretical construction patterns, elaboration, proliferation, competition and integration. Research limitations/implications The study does not only deepen the understanding of the trajectory of a theory but also enriches the research of knowledge diffusion and innovation. Originality/value The study elaborates the relationship between theory diffusion and theory development, reveals the roles of the participating disciplines played in theory diffusion and vice versa, interprets four patterns of theory evolution and uses text mining technique to extract theory incidents, which makes up for the shortcomings of citation analysis and content analysis used in previous studies.

Source

Journal of documentation. 76(2020) no.6, S.1109-1134

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Abstract

Purpose This paper aims to understand the nature of citations and metrics in the larger system of knowledge production involving universities, funding agencies, publishers, and indexing and data analytic services. Design/methodology/approach First, the normative and social constructivist views of citations are reviewed to be understood as co-existing conditions. Second, metrics are examined through the processes of commensuration by tracing the meanings of metrics embedded in various kinds of documents and contexts. Third, the steering effects of citations and metrics on knowledge production are discussed. Finally, the conclusion addresses questions pertaining to the validity and legitimacy of citations as data and their implications for knowledge production and the conception of information. Findings The normative view of citations is understood as an ideal speech situation; the social constructivist view of citation is recognised in the system of knowledge production where citing motivations are influenced by epistemic, social and political factors. When organisational performances are prioritised and generate system imperatives, motives of competition become dominant in shaping citing behaviour, which can deviate from the norms and values in the academic lifeworld. As a result, citations and metrics become a non-linguistic steering medium rather than evidence of research quality and impact. Originality/value This paper contributes to the understanding of the nature of citations and metrics and their implications for the conception of information and knowledge production.

Source

Journal of documentation. 77(2021) no.2, S.420-431

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Abstract

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.

Content

Beitrag in: JASIST special issue on 'Who tweets scientific publications? A large-scale study of tweeting audiences in all areas of research'. Vgl.: https://asistdl.onlinelibrary.wiley.com/doi/10.1002/asi.24830.

Source

Journal of the Association for Information Science and Technology. 74(2023) no.13, S.1485-1497

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Abstract

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.

Content

Beitrag in: JASIST special issue on 'Who tweets scientific publications? A large-scale study of tweeting audiences in all areas of research'. Vgl.: https://asistdl.onlinelibrary.wiley.com/doi/10.1002/asi.24833.

Source

Journal of the Association for Information Science and Technology. 74(2023) no.13, S.1515-1531

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Abstract

The phenomenon of co-corresponding authorship is becoming more and more common. To understand the practice of authorship credit sharing among multiple corresponding authors, we comprehensively analyzed the characteristics of the phenomenon of co-corresponding authorships from the perspectives of countries, disciplines, journals, and articles. This researcher was based on a dataset of nearly 8 million articles indexed in the Web of Science, which provides systematic, cross-disciplinary, and large-scale evidence for understanding the phenomenon of co-corresponding authorship for the first time. Our findings reveal that higher proportions of co-corresponding authorship exist in Asian countries, especially in China. From the perspective of disciplines, there is a relatively higher proportion of co-corresponding authorship in the fields of engineering and medicine, while a lower proportion exists in the humanities, social sciences, and computer science fields. From the perspective of journals, high-quality journals usually have higher proportions of co-corresponding authorship. At the level of the article, our findings proved that, compared to articles with a single corresponding author, articles with multiple corresponding authors have a significant citation advantage.

Source

Journal of the Association for Information Science and Technology. 75(2023) no.1, S.3-23

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Abstract

This study examines the relationship between team's gender composition and outputs of funded projects using a large data set of National Institutes of Health (NIH) R01 grants and their associated publications between 1990 and 2017. This study finds that while the women investigators' presence in NIH grants is generally low, higher women investigator presence is on average related to slightly lower number of publications. This study finds empirically that women investigators elect to work in fields in which fewer publications per million-dollar funding is the norm. For fields where women investigators are relatively well represented, they are as productive as men. The overall lower productivity of women investigators may be attributed to the low representation of women in high productivity fields dominated by men investigators. The findings shed light on possible reasons for gender disparity in grant productivity.

Source

Journal of the Association for Information Science and Technology. 72(2021) no.11, S.1386-1399

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Abstract

The data re-collection for tweets from data snapshots is a common methodological step in Twitter-based research. Understanding better the volatility of tweets over time is important for validating the reliability of metrics based on Twitter data. We tracked a set of 37,918 original scholarly tweets mentioning COVID-19-related research daily for 56 days and captured the reasons for the changes in their availability over time. Results show that the proportion of unavailable tweets increased from 1.6 to 2.6% in the time window observed. Of the 1,323 tweets that became unavailable at some point in the period observed, 30.5% became available again afterwards. "Revived" tweets resulted mainly from the unprotecting, reactivating, or unsuspending of users' accounts. Our findings highlight the importance of noting this dynamic nature of Twitter data in altmetric research and testify to the challenges that this poses for the retrieval, processing, and interpretation of Twitter data about scientific papers.

Source

Journal of the Association for Information Science and Technology. 73(2022) no.8, S.1192-1195

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Abstract

Social media data provide increasing opportunities for the automated analysis of large sets of textual documents. So far, automated tools have been developed either to account for the social networks among participants in the debates, or to analyze the content of these debates. Less attention has been paid to mapping co-occurrences of actors (participants) and topics (content) in online debates that can be considered as socio-semantic networks. We propose a new, automated approach that uses the whole matrix of co-addressed topics and actors for understanding and visualizing online debates. We show the advantages of the new approach with the analysis of two data sets: first, a large set of English-language Twitter messages at the Rio?+?20 meeting, in June 2012 (72,077 tweets), and second, a smaller data set of Dutch-language Twitter messages on bird flu related to poultry farming in 2015-2017 (2,139 tweets). We discuss the theoretical, methodological, and substantive implications of our approach, also for the analysis of other social media data.

Source

Journal of the Association for Information Science and Technology. 71(2020) no.1, S.3-15