Search (166 results, page 1 of 9)

0.407457 = product of:
  0.95073295 = sum of:
    0.05469865 = weight(_text_:media in 2188) [ClassicSimilarity], result of:
      0.05469865 = score(doc=2188,freq=2.0), product of:
        0.13212246 = queryWeight, product of:
          4.6838713 = idf(docFreq=1110, maxDocs=44218)
          0.02820796 = queryNorm
        0.41399965 = fieldWeight in 2188, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          4.6838713 = idf(docFreq=1110, maxDocs=44218)
          0.0625 = fieldNorm(doc=2188)
    0.17920688 = weight(_text_:2f in 2188) [ClassicSimilarity], result of:
      0.17920688 = score(doc=2188,freq=2.0), product of:
        0.2391474 = queryWeight, product of:
          8.478011 = idf(docFreq=24, maxDocs=44218)
          0.02820796 = queryNorm
        0.7493574 = fieldWeight in 2188, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          8.478011 = idf(docFreq=24, maxDocs=44218)
          0.0625 = fieldNorm(doc=2188)
    0.17920688 = weight(_text_:2f in 2188) [ClassicSimilarity], result of:
      0.17920688 = score(doc=2188,freq=2.0), product of:
        0.2391474 = queryWeight, product of:
          8.478011 = idf(docFreq=24, maxDocs=44218)
          0.02820796 = queryNorm
        0.7493574 = fieldWeight in 2188, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          8.478011 = idf(docFreq=24, maxDocs=44218)
          0.0625 = fieldNorm(doc=2188)
    0.17920688 = weight(_text_:2f in 2188) [ClassicSimilarity], result of:
      0.17920688 = score(doc=2188,freq=2.0), product of:
        0.2391474 = queryWeight, product of:
          8.478011 = idf(docFreq=24, maxDocs=44218)
          0.02820796 = queryNorm
        0.7493574 = fieldWeight in 2188, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          8.478011 = idf(docFreq=24, maxDocs=44218)
          0.0625 = fieldNorm(doc=2188)
    0.17920688 = weight(_text_:2f in 2188) [ClassicSimilarity], result of:
      0.17920688 = score(doc=2188,freq=2.0), product of:
        0.2391474 = queryWeight, product of:
          8.478011 = idf(docFreq=24, maxDocs=44218)
          0.02820796 = queryNorm
        0.7493574 = fieldWeight in 2188, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          8.478011 = idf(docFreq=24, maxDocs=44218)
          0.0625 = fieldNorm(doc=2188)
    0.17920688 = weight(_text_:2f in 2188) [ClassicSimilarity], result of:
      0.17920688 = score(doc=2188,freq=2.0), product of:
        0.2391474 = queryWeight, product of:
          8.478011 = idf(docFreq=24, maxDocs=44218)
          0.02820796 = queryNorm
        0.7493574 = fieldWeight in 2188, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          8.478011 = idf(docFreq=24, maxDocs=44218)
          0.0625 = fieldNorm(doc=2188)
  0.42857143 = coord(6/14)

Content

Vgl. unter: https://www.leibniz-science20.de%2Fforschung%2Fprojekte%2Faltmetrics-in-verschiedenen-wissenschaftsdisziplinen%2F&ei=2jTgVaaXGcK4Udj1qdgB&usg=AFQjCNFOPdONj4RKBDf9YDJOLuz3lkGYlg&sig2=5YI3KWIGxBmk5_kv0P_8iQ.

0.017562684 = product of:
  0.12293878 = sum of:
    0.11338431 = weight(_text_:media in 2598) [ClassicSimilarity], result of:
      0.11338431 = score(doc=2598,freq=22.0), product of:
        0.13212246 = queryWeight, product of:
          4.6838713 = idf(docFreq=1110, maxDocs=44218)
          0.02820796 = queryNorm
        0.8581759 = fieldWeight in 2598, product of:
          4.690416 = tf(freq=22.0), with freq of:
            22.0 = termFreq=22.0
          4.6838713 = idf(docFreq=1110, maxDocs=44218)
          0.0390625 = fieldNorm(doc=2598)
    0.009554473 = product of:
      0.019108946 = sum of:
        0.019108946 = weight(_text_:22 in 2598) [ClassicSimilarity], result of:
          0.019108946 = score(doc=2598,freq=2.0), product of:
            0.09877947 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.02820796 = queryNorm
            0.19345059 = fieldWeight in 2598, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.0390625 = fieldNorm(doc=2598)
      0.5 = coord(1/2)
  0.14285715 = coord(2/14)

Abstract

Purpose - The purpose of this paper is to analyze the disciplinary orientation of scientific publications that were mentioned on different social media platforms, focussing on their differences and similarities with citation counts. Design/methodology/approach - Social media metrics and readership counts, associated with 500,216 publications and their citation data from the Web of Science database, were collected from Altmetric.com and Mendeley. Results are presented through descriptive statistical analyses together with science maps generated with VOSviewer. Findings - The results confirm Mendeley as the most prevalent social media source with similar characteristics to citations in their distribution across fields and their density in average values per publication. The humanities, natural sciences, and engineering disciplines have a much lower presence of social media metrics. Twitter has a stronger focus on general medicine and social sciences. Other sources (blog, Facebook, Google+, and news media mentions) are more prominent in regards to multidisciplinary journals. Originality/value - This paper reinforces the relevance of Mendeley as a social media source for analytical purposes from a disciplinary perspective, being particularly relevant for the social sciences (together with Twitter). Key implications for the use of social media metrics on the evaluation of research performance (e.g. the concentration of some social media metrics, such as blogs, news items, etc., around multidisciplinary journals) are identified.

Date

20. 1.2015 18:30:22

Footnote

Teil eines Special Issue: Social Media Metrics in Scholarly Communication: exploring tweets, blogs, likes and other altmetrics.

0.014293614 = product of:
  0.20011058 = sum of:
    0.20011058 = weight(_text_:datenschutz in 7571) [ClassicSimilarity], result of:
      0.20011058 = score(doc=7571,freq=2.0), product of:
        0.2063373 = queryWeight, product of:
          7.314861 = idf(docFreq=79, maxDocs=44218)
          0.02820796 = queryNorm
        0.96982265 = fieldWeight in 7571, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          7.314861 = idf(docFreq=79, maxDocs=44218)
          0.09375 = fieldNorm(doc=7571)
  0.071428575 = coord(1/14)

Source

Deutscher Dokumentartag 1979, Willingen/Hochsauerland, 1.-5.10.1979. Das IuD-Programm heute - Online-Benutzergruppe - Bibliometrie, Scientometrie - Terminologiearbeit - Datenschutz - Tariffragen, Berufsbilder - Informationsmarkt - Gesprächskreise. Bearb.: M. von der Laake u. H. Strohl-Goebel

0.014293614 = product of:
  0.20011058 = sum of:
    0.20011058 = weight(_text_:datenschutz in 399) [ClassicSimilarity], result of:
      0.20011058 = score(doc=399,freq=2.0), product of:
        0.2063373 = queryWeight, product of:
          7.314861 = idf(docFreq=79, maxDocs=44218)
          0.02820796 = queryNorm
        0.96982265 = fieldWeight in 399, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          7.314861 = idf(docFreq=79, maxDocs=44218)
          0.09375 = fieldNorm(doc=399)
  0.071428575 = coord(1/14)

Source

Deutscher Dokumentartag 1979, Willingen/Hochsauerland, 1.-5.10.1979. Das IuD-Programm heute - Online-Benutzergruppe - Bibliometrie, Scientometrie - Terminologiearbeit - Datenschutz - Tariffragen, Berufsbilder - Informationsmarkt - Gesprächskreise. Bearb.: M. von der Laake u. H. Strohl-Goebel

0.014293614 = product of:
  0.20011058 = sum of:
    0.20011058 = weight(_text_:datenschutz in 400) [ClassicSimilarity], result of:
      0.20011058 = score(doc=400,freq=2.0), product of:
        0.2063373 = queryWeight, product of:
          7.314861 = idf(docFreq=79, maxDocs=44218)
          0.02820796 = queryNorm
        0.96982265 = fieldWeight in 400, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          7.314861 = idf(docFreq=79, maxDocs=44218)
          0.09375 = fieldNorm(doc=400)
  0.071428575 = coord(1/14)

Source

Deutscher Dokumentartag 1979, Willingen/Hochsauerland, 1.-5.10.1979. Das IuD-Programm heute - Online-Benutzergruppe - Bibliometrie, Scientometrie - Terminologiearbeit - Datenschutz - Tariffragen, Berufsbilder - Informationsmarkt - Gesprächskreise. Bearb.: M. von der Laake u. H. Strohl-Goebel

0.014293614 = product of:
  0.20011058 = sum of:
    0.20011058 = weight(_text_:datenschutz in 401) [ClassicSimilarity], result of:
      0.20011058 = score(doc=401,freq=2.0), product of:
        0.2063373 = queryWeight, product of:
          7.314861 = idf(docFreq=79, maxDocs=44218)
          0.02820796 = queryNorm
        0.96982265 = fieldWeight in 401, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          7.314861 = idf(docFreq=79, maxDocs=44218)
          0.09375 = fieldNorm(doc=401)
  0.071428575 = coord(1/14)

Source

Deutscher Dokumentartag 1979, Willingen/Hochsauerland, 1.-5.10.1979. Das IuD-Programm heute - Online-Benutzergruppe - Bibliometrie, Scientometrie - Terminologiearbeit - Datenschutz - Tariffragen, Berufsbilder - Informationsmarkt - Gesprächskreise. Bearb.: M. von der Laake u. H. Strohl-Goebel

0.014293614 = product of:
  0.20011058 = sum of:
    0.20011058 = weight(_text_:datenschutz in 403) [ClassicSimilarity], result of:
      0.20011058 = score(doc=403,freq=2.0), product of:
        0.2063373 = queryWeight, product of:
          7.314861 = idf(docFreq=79, maxDocs=44218)
          0.02820796 = queryNorm
        0.96982265 = fieldWeight in 403, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          7.314861 = idf(docFreq=79, maxDocs=44218)
          0.09375 = fieldNorm(doc=403)
  0.071428575 = coord(1/14)

Source

Deutscher Dokumentartag 1979, Willingen/Hochsauerland, 1.-5.10.1979. Das IuD-Programm heute - Online-Benutzergruppe - Bibliometrie, Scientometrie - Terminologiearbeit - Datenschutz - Tariffragen, Berufsbilder - Informationsmarkt - Gesprächskreise. Bearb.: M. von der Laake u. H. Strohl-Goebel

0.009612492 = product of:
  0.067287445 = sum of:
    0.027349325 = weight(_text_:media in 3801) [ClassicSimilarity], result of:
      0.027349325 = score(doc=3801,freq=2.0), product of:
        0.13212246 = queryWeight, product of:
          4.6838713 = idf(docFreq=1110, maxDocs=44218)
          0.02820796 = queryNorm
        0.20699982 = fieldWeight in 3801, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          4.6838713 = idf(docFreq=1110, maxDocs=44218)
          0.03125 = fieldNorm(doc=3801)
    0.039938122 = weight(_text_:daten in 3801) [ClassicSimilarity], result of:
      0.039938122 = score(doc=3801,freq=4.0), product of:
        0.13425784 = queryWeight, product of:
          4.759573 = idf(docFreq=1029, maxDocs=44218)
          0.02820796 = queryNorm
        0.2974733 = fieldWeight in 3801, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          4.759573 = idf(docFreq=1029, maxDocs=44218)
          0.03125 = fieldNorm(doc=3801)
  0.14285715 = coord(2/14)

Content

Frontmatter -- -- Foreword -- -- Prologue -- -- Contents -- -- Introduction -- -- Part I: Critical informetrics -- -- The Incessant Chattering of Texts -- -- Informetrics Needs a Foundation in the Theory of Science -- -- Part II: Citation theories -- -- Referencing as Cooperation or Competition -- -- Semiotics and Citations -- -- Data Citation as a Bibliometric Oxymoron -- -- Part III: Statistical theories -- -- TypeToken Theory and Bibliometrics -- -- From a Success Index to a Success Multiplier -- -- From Matthew to Hirsch: A Success-Breeds-Success Story -- -- Informations Magic Numbers: The Numerology of Information Science -- -- Part IV: Authorship theories -- -- Authors as Persons and Authors as Bundles of Words -- -- The Angle Sum Theory: Exploring the Literature on Acknowledgments in Scholarly Communication -- -- The Flesh of Science: Somatics and Semiotics -- -- Part V: Knowledge organization theories -- -- Informetric Analyses of Knowledge Organization Systems (KOSs) -- -- Information, Meaning, and Intellectual Organization in Networks of Inter-Human Communication -- -- Modeling the Structure and Dynamics of Science Using Books -- -- Part VI: Altmetric theories -- -- Webometrics and Altmetrics: Home Birth vs. Hospital Birth -- -- Scientific Revolution in Scientometrics: The Broadening of Impact from Citation to Societal -- -- Altmetrics as Traces of the Computerization of the Research Process -- -- Interpreting Altmetrics: Viewing Acts on Social Media through the Lens of Citation and Social Theories -- -- Biographical information for the editor and contributors -- -- Index

RSWK

Altmetrische Daten

Subject

Altmetrische Daten

0.007752805 = product of:
  0.10853927 = sum of:
    0.10853927 = weight(_text_:media in 239) [ClassicSimilarity], result of:
      0.10853927 = score(doc=239,freq=14.0), product of:
        0.13212246 = queryWeight, product of:
          4.6838713 = idf(docFreq=1110, maxDocs=44218)
          0.02820796 = queryNorm
        0.82150507 = fieldWeight in 239, product of:
          3.7416575 = tf(freq=14.0), with freq of:
            14.0 = termFreq=14.0
          4.6838713 = idf(docFreq=1110, maxDocs=44218)
          0.046875 = fieldNorm(doc=239)
  0.071428575 = coord(1/14)

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.

0.0073257117 = product of:
  0.10255996 = sum of:
    0.10255996 = weight(_text_:media in 215) [ClassicSimilarity], result of:
      0.10255996 = score(doc=215,freq=18.0), product of:
        0.13212246 = queryWeight, product of:
          4.6838713 = idf(docFreq=1110, maxDocs=44218)
          0.02820796 = queryNorm
        0.7762493 = fieldWeight in 215, product of:
          4.2426405 = tf(freq=18.0), with freq of:
            18.0 = termFreq=18.0
          4.6838713 = idf(docFreq=1110, maxDocs=44218)
          0.0390625 = fieldNorm(doc=215)
  0.071428575 = coord(1/14)

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.

0.0071777035 = product of:
  0.10048784 = sum of:
    0.10048784 = weight(_text_:media in 3781) [ClassicSimilarity], result of:
      0.10048784 = score(doc=3781,freq=12.0), product of:
        0.13212246 = queryWeight, product of:
          4.6838713 = idf(docFreq=1110, maxDocs=44218)
          0.02820796 = queryNorm
        0.76056594 = fieldWeight in 3781, product of:
          3.4641016 = tf(freq=12.0), with freq of:
            12.0 = termFreq=12.0
          4.6838713 = idf(docFreq=1110, maxDocs=44218)
          0.046875 = fieldNorm(doc=3781)
  0.071428575 = coord(1/14)

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.

0.0071318084 = product of:
  0.09984531 = sum of:
    0.09984531 = weight(_text_:daten in 4499) [ClassicSimilarity], result of:
      0.09984531 = score(doc=4499,freq=4.0), product of:
        0.13425784 = queryWeight, product of:
          4.759573 = idf(docFreq=1029, maxDocs=44218)
          0.02820796 = queryNorm
        0.7436833 = fieldWeight in 4499, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          4.759573 = idf(docFreq=1029, maxDocs=44218)
          0.078125 = fieldNorm(doc=4499)
  0.071428575 = coord(1/14)

Abstract

Das Ziel dieses Beitrages ist es, einige Daten zum Zitationsverhalten mathematischer Arbeiten vorzustellen und zu diskutieren.

Content

Vgl. auch den Beitrag auf S.204-205: Vier bibliometrische Kennzahlen auf Grundlage von zbMATH-Daten. Vgl.: https://doi.org/10.1515/dmvm-2017-0064.

0.0066795247 = product of:
  0.04675667 = sum of:
    0.04102399 = weight(_text_:media in 3809) [ClassicSimilarity], result of:
      0.04102399 = score(doc=3809,freq=8.0), product of:
        0.13212246 = queryWeight, product of:
          4.6838713 = idf(docFreq=1110, maxDocs=44218)
          0.02820796 = queryNorm
        0.31049973 = fieldWeight in 3809, product of:
          2.828427 = tf(freq=8.0), with freq of:
            8.0 = termFreq=8.0
          4.6838713 = idf(docFreq=1110, maxDocs=44218)
          0.0234375 = fieldNorm(doc=3809)
    0.0057326835 = product of:
      0.011465367 = sum of:
        0.011465367 = weight(_text_:22 in 3809) [ClassicSimilarity], result of:
          0.011465367 = score(doc=3809,freq=2.0), product of:
            0.09877947 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.02820796 = queryNorm
            0.116070345 = fieldWeight in 3809, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.0234375 = fieldNorm(doc=3809)
      0.5 = coord(1/2)
  0.14285715 = coord(2/14)

Abstract

There will soon be a critical mass of web-based digital objects and usage statistics on which to model scholars' communication behaviors - publishing, posting, blogging, scanning, reading, downloading, glossing, linking, citing, recommending, acknowledging - and with which to track their scholarly influence and impact, broadly conceived and broadly felt (Cronin, 2005, p. 196). A decade after Cronin's prediction and five years after the coining of altmetrics, the time seems ripe to reflect upon the role of social media in scholarly communication. This Special Issue does so by providing an overview of current research on the indicators and metrics grouped under the umbrella term of altmetrics, on their relationships with traditional indicators of scientific activity, and on the uses that are made of the various social media platforms - on which these indicators are based - by scientists of various disciplines.

Date

20. 1.2015 18:30:22

Footnote

Teil eines Special Issue: Social Media Metrics in Scholarly Communication: exploring tweets, blogs, likes and other altmetrics. Der Beitrag ist frei verfügbar.

0.006248733 = product of:
  0.04374113 = sum of:
    0.034186658 = weight(_text_:media in 178) [ClassicSimilarity], result of:
      0.034186658 = score(doc=178,freq=2.0), product of:
        0.13212246 = queryWeight, product of:
          4.6838713 = idf(docFreq=1110, maxDocs=44218)
          0.02820796 = queryNorm
        0.25874978 = fieldWeight in 178, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          4.6838713 = idf(docFreq=1110, maxDocs=44218)
          0.0390625 = fieldNorm(doc=178)
    0.009554473 = product of:
      0.019108946 = sum of:
        0.019108946 = weight(_text_:22 in 178) [ClassicSimilarity], result of:
          0.019108946 = score(doc=178,freq=2.0), product of:
            0.09877947 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.02820796 = queryNorm
            0.19345059 = fieldWeight in 178, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.0390625 = fieldNorm(doc=178)
      0.5 = coord(1/2)
  0.14285715 = coord(2/14)

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

0.0061142524 = product of:
  0.08559953 = sum of:
    0.08559953 = weight(_text_:daten in 5738) [ClassicSimilarity], result of:
      0.08559953 = score(doc=5738,freq=6.0), product of:
        0.13425784 = queryWeight, product of:
          4.759573 = idf(docFreq=1029, maxDocs=44218)
          0.02820796 = queryNorm
        0.6375756 = fieldWeight in 5738, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          4.759573 = idf(docFreq=1029, maxDocs=44218)
          0.0546875 = fieldNorm(doc=5738)
  0.071428575 = coord(1/14)

Abstract

Bibliometrische Daten werden heute zunehmend in der Evaluation von Forschungsergebnissen benutzt. Diese Anwendungen reichen von der (indirekten) Verwendung bei der Peer-Evaluation von Drittmittelanträgen über die Beurteilung von Bewerbungen in Berufungskommissionen oder Anträgen für Forschungszulagen bis hin zur systematischen Erhebung von forschungsorientierten Kennzahlen von Institutionen. Mit diesem Dokument will die DMV ihren Mitgliedern eine Diskussionsgrundlage zur Verwendung bibliometrischer Daten im Zusammenhang mit der Evaluation von Personen und Institutionen im Fachgebiet Mathematik zur Verfügung stellen, insbesondere auch im Vergleich zu anderen Fächern. Am Ende des Texts befindet sich ein Glossar, in dem die wichtigsten Begriffe kurz erläutert werden.

0.005921303 = product of:
  0.08289824 = sum of:
    0.08289824 = weight(_text_:media in 1111) [ClassicSimilarity], result of:
      0.08289824 = score(doc=1111,freq=6.0), product of:
        0.13212246 = queryWeight, product of:
          4.6838713 = idf(docFreq=1110, maxDocs=44218)
          0.02820796 = queryNorm
        0.62743485 = fieldWeight in 1111, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          4.6838713 = idf(docFreq=1110, maxDocs=44218)
          0.0546875 = fieldNorm(doc=1111)
  0.071428575 = coord(1/14)

Abstract

The h-index can be a useful metric for evaluating a person's output of Internet media. Here I advocate and demonstrate adaption of the h-index and the g-index to the top video content creators on YouTube. The h-index for Internet video media is based on videos and their view counts. The h-index is defined as the number of videos with >=h × 10**5 views. The g-index is defined as the number of videos with >=g × 10**5 views on average. When compared with a video creator's total view count, the h-index and g-index better capture both productivity and impact in a single metric.

0.00586057 = product of:
  0.08204798 = sum of:
    0.08204798 = weight(_text_:media in 5057) [ClassicSimilarity], result of:
      0.08204798 = score(doc=5057,freq=8.0), product of:
        0.13212246 = queryWeight, product of:
          4.6838713 = idf(docFreq=1110, maxDocs=44218)
          0.02820796 = queryNorm
        0.62099946 = fieldWeight in 5057, product of:
          2.828427 = tf(freq=8.0), with freq of:
            8.0 = termFreq=8.0
          4.6838713 = idf(docFreq=1110, maxDocs=44218)
          0.046875 = fieldNorm(doc=5057)
  0.071428575 = coord(1/14)

Abstract

Increasingly researchers and academic research institutions are being asked to demonstrate the quality and impact of their research. Traditionally researchers have used text-based outputs to achieve these objectives. This paper discusses the introduction and subsequent review of a new service at a major Australian university, designed to encourage researchers to use media, particularly visual formats, in promoting their research. Findings from the review have highlighted the importance of researchers working in partnership with in-house media professionals to produce short, relatable, digestible, and engaging visual products. As a result of these findings, the authors have presented a four-phase media development model to assist researchers to tell their research story. The paper concludes with a discussion of the implications for the institution as a whole and, more specifically, libraries.

0.005525398 = product of:
  0.07735557 = sum of:
    0.07735557 = weight(_text_:media in 2154) [ClassicSimilarity], result of:
      0.07735557 = score(doc=2154,freq=4.0), product of:
        0.13212246 = queryWeight, product of:
          4.6838713 = idf(docFreq=1110, maxDocs=44218)
          0.02820796 = queryNorm
        0.5854839 = fieldWeight in 2154, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          4.6838713 = idf(docFreq=1110, maxDocs=44218)
          0.0625 = fieldNorm(doc=2154)
  0.071428575 = coord(1/14)

Abstract

We use a social network approach to examine how work and friendship ties in a university research group were associated with the kinds of media used for different kind of information exchange. The use of e-mail, unscheduled face-to-face encounters, and scheduled face-to-face meetings predominated for the exchange of 6 kinds of information: receiving work, giving work, collaborative writing, computer programming, sociability and major emotional support. Few pairs used synchronous desktop videoconferencing or the telephone

0.0054602637 = product of:
  0.07644369 = sum of:
    0.07644369 = weight(_text_:media in 2892) [ClassicSimilarity], result of:
      0.07644369 = score(doc=2892,freq=10.0), product of:
        0.13212246 = queryWeight, product of:
          4.6838713 = idf(docFreq=1110, maxDocs=44218)
          0.02820796 = queryNorm
        0.5785821 = fieldWeight in 2892, product of:
          3.1622777 = tf(freq=10.0), with freq of:
            10.0 = termFreq=10.0
          4.6838713 = idf(docFreq=1110, maxDocs=44218)
          0.0390625 = fieldNorm(doc=2892)
  0.071428575 = coord(1/14)

Abstract

Analyzing hyperlink patterns has been a major research topic since the early days of the web. Numerous studies reported uncovering rich information and methodological advances. However, very few studies thus far examined hyperlinks in the rapidly developing sphere of social media. This paper reports a study that helps fill this gap. The study analyzed links originating from tweets to the websites of 3 types of organizations (government, education, and business). Data were collected over an 8-month period to observe the fluctuation and reliability of the individual data set. Hyperlink data from the general web (not social media sites) were also collected and compared with social media data. The study found that the 2 types of hyperlink data correlated significantly and that analyzing the 2 together can help organizations see their relative strength or weakness in the two platforms. The study also found that both types of inlink data correlated with offline measures of organizations' performance. Twitter data from a relatively short period were fairly reliable in estimating performance measures. The timelier nature of social media data as well as the date/time stamps on tweets make this type of data potentially more valuable than that from the general web.

0.004279085 = product of:
  0.059907187 = sum of:
    0.059907187 = weight(_text_:daten in 3979) [ClassicSimilarity], result of:
      0.059907187 = score(doc=3979,freq=4.0), product of:
        0.13425784 = queryWeight, product of:
          4.759573 = idf(docFreq=1029, maxDocs=44218)
          0.02820796 = queryNorm
        0.44620997 = fieldWeight in 3979, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          4.759573 = idf(docFreq=1029, maxDocs=44218)
          0.046875 = fieldNorm(doc=3979)
  0.071428575 = coord(1/14)

Abstract

Der Beitrag "Drei von Fünfundzwanzigtausend" des UniSpectrums 3/2012 berichtete, dass drei Veröffentlichungen, an denen Wissenschaftler der TU Kaiserslautern beteiligt waren, gemäß der Datenbank "Web of Knowledge" die "magische Schwelle von 1.000 Zitierungen erreicht und überschritten" haben. Dies ist ein beachtenswerter Erfolg der Autoren und eine gute Nachricht für die Universität, denn bibliometrische Daten werden immer stärker zur Beurteilung von Wissenschaftlern und für das Ranking von Fachbereichen und ganzen Hochschulen herangezogen. Auch die Zuteilung von Forschungsgeldern wird mittlerweile in einigen Ländern von bibliometrischen Daten abhängig gemacht (z.B. in Italien) und vermutlich wird dies auch bei uns demnächst in die Diskussion kommen. Spätestens dann aber wird es wichtig, über die Objektivität und Genauigkeit der Messungen sowie über deren Aussagekraft und Relevanz nachzudenken. Insbesondere wird es wichtig, auch die problematischen Aspekte dieser scheinbar einfachen Form der Leistungsbewertung zu thematisieren. Dazu möchten wir in diesem Beitrag Anstöße geben.