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  • × theme_ss:"Informetrie"
  1. Herb, U.; Beucke, D.: ¬Die Zukunft der Impact-Messung : Social Media, Nutzung und Zitate im World Wide Web (2013) 0.32
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    Content
    Vgl. unter: https://www.leibniz-science20.de%2Fforschung%2Fprojekte%2Faltmetrics-in-verschiedenen-wissenschaftsdisziplinen%2F&ei=2jTgVaaXGcK4Udj1qdgB&usg=AFQjCNFOPdONj4RKBDf9YDJOLuz3lkGYlg&sig2=5YI3KWIGxBmk5_kv0P_8iQ.
  2. Zhang, Y.; Wu, M.; Zhang, G.; Lu, J.: Stepping beyond your comfort zone : diffusion-based network analytics for knowledge trajectory recommendation (2023) 0.08
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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
  3. Song, M.; Kang, K.; An, J.Y.: Investigating drug-disease interactions in drug-symptom-disease triples via citation relations (2018) 0.07
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    Abstract
    With the growth in biomedical literature, the necessity of extracting useful information from the literature has increased. One approach to extracting biomedical knowledge involves using citation relations to discover entity relations. The assumption is that citation relations between any two articles connect knowledge entities across the articles, enabling the detection of implicit relationships among biomedical entities. The goal of this article is to examine the characteristics of biomedical entities connected via intermediate entities using citation relations aided by text mining. Based on the importance of symptoms as biomedical entities, we created triples connected via citation relations to identify drug-disease pairs with shared symptoms as intermediate entities. Drug-disease interactions built via citation relations were compared with co-occurrence-based interactions. Several types of analyses were adopted to examine the properties of the extracted entity pairs by comparing them with drug-disease interaction databases. We attempted to identify the characteristics of drug-disease pairs through citation relations in association with biomedical entities. The results showed that the citation relation-based approach resulted in diverse types of biomedical entities and preserved topical consistency. In addition, drug-disease pairs identified only via citation relations are interesting for clinical trials when they are examined using BITOLA.
    Date
    1.11.2018 18:19:22
  4. Lorentzen, D.G.: Bridging polarised Twitter discussions : the interactions of the users in the middle (2021) 0.05
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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
  5. Hassan, E.: Simultaneous mapping of interactions between scientific and technological knowledge bases : the case of space communications (2003) 0.04
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    Abstract
    This article examines the knowledge structure of the field of space communications using bibliometric mapping techniques based an textual analysis. A new approach with the aim of visualizing simultaneously the configuration of its scientific and technological knowledge bases is presented. This approach enabled us to overcome various limits of existing bibliometric methods dealing with science and technology relationships. The bibliometric map revealed weck cognitive interactions between science and technology at the worldwide level, although it brought out the systemic nature of the process of knowledge production at either side. We extended the mapping approach to the R&D activities of the Triad countries in order to characterize their specialization profiles and cognitive links an both sides in comparison with the structure of the field at the worldwide level. Results showed different patterns in the way the Triad countries organized their scientific and technological activities within the field.
  6. Rohman, A.: ¬The emergence, peak, and abeyance of an online information ground : the lifecycle of a Facebook group for verifying information during violence (2021) 0.04
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    Abstract
    Information grounds emerge as people share information with others in a common place. Many studies have investigated the emergence of information grounds in public places. This study pays attention to the emergence, peak, and abeyance of an online information ground. It investigates a Facebook group used by youth for sharing information when misinformation spread wildly during the 2011 violence in Ambon, Indonesia. The findings demonstrate change and continuity in an online information ground; it became an information hub when reaching a peak cycle, and an information repository when entering into abeyance. Despite this period of nonactivity, the friendships and collective memories resulting from information ground interactions last over time and can be used for reactivating the online information ground when new needs emerge. Illuminating the lifecycles of an online information ground, the findings have potential to explain the dynamic of users' interactions with others and with information in quotidian spaces.
  7. Voveriene, O.; Trumpiene, A.: Bibliometrics, scientometrics and informetrics : their relationship and interactions (1994) 0.04
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    Abstract
    Considers aspects of scientific methodology by which a new subject field attains the status of a branch of a science. Discusses recent developments of metrics in the science of science and library and information science. Presents definitions of librametrics, bibliometrics, scientometrics and informetrics and examines the relationships of the last 3 with each other and with science of science, library science and information science
  8. Mena-Chalco, J.P.; Digiampietri, L.A.; Fabrício Martins Lopes, F.; Marcondes Cesar Junior, R.: Brazilian bibliometric coauthorship networks (2014) 0.04
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    Abstract
    The Brazilian Lattes Platform is an important academic/résumé data set that registers all academic activities of researchers associated with different major knowledge areas. The academic information collected in this data set is used to evaluate, analyze, and document the scientific production of research groups. Information about the interactions between Brazilian researchers in the form of coauthorships, however, has not been analyzed. In this article, we identified and characterized Brazilian academic coauthorship networks of researchers registered in the Lattes Platform using topological properties of graphs. For this purpose, we explored (a) strategies to develop a large Lattes curricula vitae data set, (b) an algorithm for identifying automatic coauthorships based on bibliographic information, and (c) topological metrics to investigate interactions among researchers. This study characterized coauthorship networks to gain an in-depth understanding of the network structures and dynamics (social behavior) among researchers in all available major Brazilian knowledge areas. In this study, we evaluated information from a total of 1,131,912 researchers associated with the eight major Brazilian knowledge areas: agricultural sciences; biological sciences; exact and earth sciences; humanities; applied social sciences; health sciences; engineering; and linguistics, letters, and arts.
  9. Perry, C.A.: Network influences on scholarly communication in developmental dyslexia : a longitudinal follow-up (2003) 0.04
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    Abstract
    Perry collects co-citation data for the years 1994 to 1998 on 74 Developmental Dyslexia researchers whose co-citation patterns and personally reported interactions she originally studied form 1976 to 1993. The original study indicated discrepancies between sociometric and bibliometric networks of interaction, delays in the emergence of new perspectives and the possibility of the convergence of perspectives facilitated by central researchers. Mapping for the present study was done by multi-dimensional scaling rather than the principle components factor analysis in the earlier study, but both clustering techniques and factor analysis were applied to the new data. Researchers with phonological and with neuroscience perspectives area associated with different co-citation patterns. Research groups grow more distinct over time with the neuroscience-vision subgroup increasing in density, but other sub-groups showing some tendency toward integration. The personal networks differences with the co-citation network persist and the assumption that one reflects the other is not supported.
  10. Leydesdorff, L.: Theories of citation? (1999) 0.03
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    Abstract
    Citations support the communication of specialist knowledge by allowing authors and readers to make specific selections in several contexts at the same time. In the interactions between the social network of authors and the network of their reflexive communications, a sub textual code of communication with a distributed character has emerged. Citation analysis reflects on citation practices. Reference lists are aggregated in scientometric analysis using one of the available contexts to reduce the complexity: geometrical representations of dynamic operations are reflected in corresponding theories of citation. The specific contexts represented in the modern citation can be deconstructed from the perspective of the cultural evolution of scientific communication
  11. Leydesdorff, L.: How are new citation-based journal indicators adding to the bibliometric toolbox? (2009) 0.03
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    Abstract
    The launching of Scopus and Google Scholar, and methodological developments in social-network analysis have made many more indicators for evaluating journals available than the traditional impact factor, cited half-life, and immediacy index of the ISI. In this study, these new indicators are compared with one another and with the older ones. Do the various indicators measure new dimensions of the citation networks, or are they highly correlated among themselves? Are they robust and relatively stable over time? Two main dimensions are distinguished - size and impact - which together shape influence. The h-index combines the two dimensions and can also be considered as an indicator of reach (like Indegree). PageRank is mainly an indicator of size, but has important interactions with centrality measures. The Scimago Journal Ranking (SJR) indicator provides an alternative to the journal impact factor, but the computation is less easy.
  12. Yan, E.; Sugimoto, C.R.: Institutional interactions : exploring social, cognitive, and geographic relationships between institutions as demonstrated through citation networks (2011) 0.03
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    Abstract
    The objective of this research is to examine the interaction of institutions, based on their citation and collaboration networks. The domain of library and information science is examined, using data from 1965-2010. A linear model is formulated to explore the factors that are associated with institutional citation behaviors, using the number of citations as the dependent variable, and the number of collaborations, physical distance, and topical distance as independent variables. It is found that institutional citation behaviors are associated with social, topical, and geographical factors. Dynamically, the number of citations is becoming more associated with collaboration intensity and less dependent on the country boundary and/or physical distance. This research is informative for scientometricians and policy makers.
  13. Romero-Frías, E.; Vaughan, L.: Exploring the relationships between media and political parties through web hyperlink analysis : the case of Spain (2012) 0.03
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    Abstract
    The study focuses on the web presence of the main Spanish media and seeks to determine whether hyperlink analysis of media and political parties can provide insight into their political orientation. The research included all major national media and political parties in Spain. Inlink and co-link data about these organizations were collected and analyzed using multidimensional scaling (MDS) and other statistical methods. In the MDS map, media are clustered based on their political orientation. There are significantly more co-links between media and parties with the same political orientation than there are between those with different political orientations. Findings from the study suggest the potential of using link analysis to gain new insights into the interactions among media and political parties.
  14. Rousseau, S.; Rousseau, R.: Interactions between journal attributes and authors' willingness to wait for editorial decisions (2012) 0.03
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    Abstract
    In this article, we report on a discrete choice experiment to determine the willingness-to-wait (WTW) in the context of journal submissions. Respondents to our survey are mostly active in the information sciences, including librarians. Besides WTW, other attributes included in the study are the quality of the editorial board, the quality of referee reports, the probability of being accepted, the ISI impact factor, and the standing of the journal among peers. Interaction effects originating from scientists' personal characteristics (age, region of origin, motivations to publish) with the WTW are highlighted. A difference was made between submitting a high quality article and a standard article. Among the interesting results obtained from our analysis we mention that for a high-quality article, researchers are willing to wait some 18 months longer for a journal with an ISI impact factor above 2 than for a journal without an impact factor, keeping all other factors constant. For a standard article, the WTW decreases to some 8 months. Gender had no effect on our conclusions.
  15. Sugimoto, C.R.; Work, S.; Larivière, V.; Haustein, S.: Scholarly use of social media and altmetrics : A review of the literature (2017) 0.03
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    Abstract
    Social media has become integrated into the fabric of the scholarly communication system in fundamental ways, principally through scholarly use of social media platforms and the promotion of new indicators on the basis of interactions with these platforms. Research and scholarship in this area has accelerated since the coining and subsequent advocacy for altmetrics-that is, research indicators based on social media activity. This review provides an extensive account of the state-of-the art in both scholarly use of social media and altmetrics. The review consists of 2 main parts: the first examines the use of social media in academia, reviewing the various functions these platforms have in the scholarly communication process and the factors that affect this use. The second part reviews empirical studies of altmetrics, discussing the various interpretations of altmetrics, data collection and methodological limitations, and differences according to platform. The review ends with a critical discussion of the implications of this transformation in the scholarly communication system.
  16. Larivière, V.; Sugimoto, C.R.; Cronin, B.: ¬A bibliometric chronicling of library and information science's first hundred years (2012) 0.02
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    Abstract
    This paper presents a condensed history of Library and Information Science (LIS) over the course of more than a century using a variety of bibliometric measures. It examines in detail the variable rate of knowledge production in the field, shifts in subject coverage, the dominance of particular publication genres at different times, prevailing modes of production, interactions with other disciplines, and, more generally, observes how the field has evolved. It shows that, despite a striking growth in the number of journals, papers, and contributing authors, a decrease was observed in the field's market-share of all social science and humanities research. Collaborative authorship is now the norm, a pattern seen across the social sciences. The idea of boundary crossing was also examined: in 2010, nearly 60% of authors who published in LIS also published in another discipline. This high degree of permeability in LIS was also demonstrated through reference and citation practices: LIS scholars now cite and receive citations from other fields more than from LIS itself. Two major structural shifts are revealed in the data: in 1960, LIS changed from a professional field focused on librarianship to an academic field focused on information and use; and in 1990, LIS began to receive a growing number of citations from outside the field, notably from Computer Science and Management, and saw a dramatic increase in the number of authors contributing to the literature of the field.
  17. Ibáñez, A.; Armañanzas, R.; Bielza, C.; Larrañaga, P.: Genetic algorithms and Gaussian Bayesian networks to uncover the predictive core set of bibliometric indices (2016) 0.02
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    Abstract
    The diversity of bibliometric indices today poses the challenge of exploiting the relationships among them. Our research uncovers the best core set of relevant indices for predicting other bibliometric indices. An added difficulty is to select the role of each variable, that is, which bibliometric indices are predictive variables and which are response variables. This results in a novel multioutput regression problem where the role of each variable (predictor or response) is unknown beforehand. We use Gaussian Bayesian networks to solve the this problem and discover multivariate relationships among bibliometric indices. These networks are learnt by a genetic algorithm that looks for the optimal models that best predict bibliometric data. Results show that the optimal induced Gaussian Bayesian networks corroborate previous relationships between several indices, but also suggest new, previously unreported interactions. An extended analysis of the best model illustrates that a set of 12 bibliometric indices can be accurately predicted using only a smaller predictive core subset composed of citations, g-index, q2-index, and hr-index. This research is performed using bibliometric data on Spanish full professors associated with the computer science area.
  18. Zhang, Y.; Zhang, G.; Zhu, D.; Lu, J.: Scientific evolutionary pathways : identifying and visualizing relationships for scientific topics (2017) 0.02
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    Abstract
    Whereas traditional science maps emphasize citation statistics and static relationships, this paper presents a term-based method to identify and visualize the evolutionary pathways of scientific topics in a series of time slices. First, we create a data preprocessing model for accurate term cleaning, consolidating, and clustering. Then we construct a simulated data streaming function and introduce a learning process to train a relationship identification function to adapt to changing environments in real time, where relationships of topic evolution, fusion, death, and novelty are identified. The main result of the method is a map of scientific evolutionary pathways. The visual routines provide a way to indicate the interactions among scientific subjects and a version in a series of time slices helps further illustrate such evolutionary pathways in detail. The detailed outline offers sufficient statistical information to delve into scientific topics and routines and then helps address meaningful insights with the assistance of expert knowledge. This empirical study focuses on scientific proposals granted by the United States National Science Foundation, and demonstrates the feasibility and reliability. Our method could be widely applied to a range of science, technology, and innovation policy research, and offer insight into the evolutionary pathways of scientific activities.
  19. Costas, R.; Rijcke, S. de; Marres, N.: "Heterogeneous couplings" : operationalizing network perspectives to study science-society interactions through social media metrics (2021) 0.02
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    Abstract
    Social media metrics have a genuine networked nature, reflecting the networking characteristics of the social media platform from where they are derived. This networked nature has been relatively less explored in the literature on altmetrics, although new network-level approaches are starting to appear. A general conceptualization of the role of social media networks in science communication, and particularly of social media as a specific type of interface between science and society, is still missing. The aim of this paper is to provide a conceptual framework for appraising interactions between science and society in multiple directions, in what we call heterogeneous couplings. Heterogeneous couplings are conceptualized as the co-occurrence of science and non-science objects, actors, and interactions in online media environments. This conceptualization provides a common framework to study the interactions between science and non-science actors as captured via online and social media platforms. The conceptualization of heterogeneous couplings opens wider opportunities for the development of network applications and analyses of the interactions between societal and scholarly entities in social media environments, paving the way toward more advanced forms of altmetrics, social (media) studies of science, and the conceptualization and operationalization of more advanced science-society studies.
  20. Haustein, S.: Scientific interactions and research evaluation : from bibliometrics to Altmetrics (2015) 0.02
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