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  • × theme_ss:"Informetrie"
  1. Maier, S.: Wie Wissenschaftler berühmt werden : Anzahl der Veröffentlichungen zählt - "Google" ist das Maß aller Dinge (2004) 0.01 
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    Footnote
    Vgl.: http:/www.wissenschaft.de/wissen/news/240593.html
  2. Thelwall, M.; Thelwall, S.: ¬A thematic analysis of highly retweeted early COVID-19 tweets : consensus, information, dissent and lockdown life (2020) 0.01 
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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
  3. Petersen, A.; Münch, V.: STN® AnaVist(TM) holt verborgenes Wissen aus Recherche-Ergebnissen : Neue Software analysiert und visualisiert Marktaufteilung, Forschung und Patentaktivitäten (2005) 0.01 
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  4. Nicholls, P.T.: Empirical validation of Lotka's law (1986) 0.00 
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    Source
    Information processing and management. 22(1986), S.417-419
  5. Nicolaisen, J.: Citation analysis (2007) 0.00 
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    Date
    13. 7.2008 19:53:22
  6. Fiala, J.: Information flood : fiction and reality (1987) 0.00 
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    Source
    Thermochimica acta. 110(1987), S.11-22
  7. Hassler, M.: Web analytics : Metriken auswerten, Besucherverhalten verstehen, Website optimieren ; [Metriken analysieren und interpretieren ; Besucherverhalten verstehen und auswerten ; Website-Ziele definieren, Webauftritt optimieren und den Erfolg steigern] (2009) 0.00 
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    Abstract
    Web Analytics bezeichnet die Sammlung, Analyse und Auswertung von Daten der Website-Nutzung mit dem Ziel, diese Informationen zum besseren Verständnis des Besucherverhaltens sowie zur Optimierung der Website zu nutzen. Je nach Ziel der eigenen Website - z.B. die Vermittlung eines Markenwerts oder die Vermehrung von Kontaktanfragen, Bestellungen oder Newsletter-Abonnements - können Sie anhand von Web Analytics herausfinden, wo sich Schwachstellen Ihrer Website befinden und wie Sie Ihre eigenen Ziele durch entsprechende Optimierungen besser erreichen. Dabei ist Web Analytics nicht nur für Website-Betreiber und IT-Abteilungen interessant, sondern wird insbesondere auch mehr und mehr für Marketing und Management nutzbar. Mit diesem Buch lernen Sie, wie Sie die Nutzung Ihrer Website analysieren. Sie können z. B. untersuchen, welche Traffic-Quelle am meisten Umsatz bringt oder welche Bereiche der Website besonders häufig genutzt werden und vieles mehr. Auf diese Weise werden Sie Ihre Besucher, ihr Verhalten und ihre Motivation besser kennen lernen, Ihre Website darauf abstimmen und somit Ihren Erfolg steigern können. Um aus Web Analytics einen wirklichen Mehrwert ziehen zu können, benötigen Sie fundiertes Wissen. Marco Hassler gibt Ihnen in seinem Buch einen umfassenden Einblick in Web Analytics. Er zeigt Ihnen detailliert, wie das Verhalten der Besucher analysiert wird und welche Metriken Sie wann sinnvoll anwenden können. Im letzten Teil des Buches zeigt Ihnen der Autor, wie Sie Ihre Auswertungsergebnisse dafür nutzen, über Conversion-Messungen die Website auf ihre Ziele hin zu optimieren. Ziel dieses Buches ist es, konkrete Web-Analytics-Kenntnisse zu vermitteln und wertvolle praxisorientierte Tipps zu geben. Dazu schlägt das Buch die Brücke zu tangierenden Themenbereichen wie Usability, User-Centered-Design, Online Branding, Online-Marketing oder Suchmaschinenoptimierung. Marco Hassler gibt Ihnen klare Hinweise und Anleitungen, wie Sie Ihre Ziele erreichen.
  8. Su, Y.; Han, L.-F.: ¬A new literature growth model : variable exponential growth law of literature (1998) 0.00 
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    Date
    22. 5.1999 19:22:35
  9. Van der Veer Martens, B.: Do citation systems represent theories of truth? (2001) 0.00 
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    Date
    22. 7.2006 15:22:28
  10. Khurshid, A.; Sahai, H.: Bibliometric, scientometric and informetric distributions and laws : a selected bibliography (1991) 0.00 
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    Source
    International forum on information and documentation. 16(1991) no.2, S.18-29
  11. Diodato, V.: Dictionary of bibliometrics (1994) 0.00 
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    Footnote
    Rez. in: Journal of library and information science 22(1996) no.2, S.116-117 (L.C. Smith)
  12. Bookstein, A.: Informetric distributions : II. Resilience to ambiguity (1990) 0.00 
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    Date
    22. 7.2006 18:55:55
  13. Herb, U.: Überwachungskapitalismus und Wissenschaftssteuerung (2019) 0.00 
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    Date
    29. 6.2019 17:46:17
    4. 8.2019 19:52:29
    Issue
    [29. Juli 2019].
  14. Prathap, G.: Quantity, quality, and consistency as bibliometric indicators (2014) 0.00 
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    Date
    29. 1.2014 15:59:59
  15. Bornmann, L.: On the function of university rankings (2014) 0.00 
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    Date
    29. 1.2014 16:55:03
  16. Zornic, N.; Markovic, A.; Jeremic, V.: How the top 500 ARWU can provide a misleading rank (2014) 0.00 
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    Date
    16. 6.2014 19:29:15
  17. Lewison, G.: ¬The work of the Bibliometrics Research Group (City University) and associates (2005) 0.00 
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    Date
    20. 1.2007 17:02:22
  18. Marx, W.; Bornmann, L.: On the problems of dealing with bibliometric data (2014) 0.00 
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    Date
    18. 3.2014 19:13:22
  19. Ding, Y.: Scholarly communication and bibliometrics : Part 1: The scholarly communication model: literature review (1998) 0.00 
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    Source
    International forum on information and documentation. 23(1998) no.2, S.20-29
  20. Raan, A.F.J. van: Statistical properties of bibliometric indicators : research group indicator distributions and correlations (2006) 0.00 
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    Date
    22. 7.2006 16:20:22

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