Search (219 results, page 1 of 11)

  • × theme_ss:"Informetrie"
  1. Bookstein, A.: Informetric distributions : I. Unified overview (1990) 0.04
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    Date
    22. 7.2006 18:55:29
  2. Ohly, P.: Dimensions of globality : a bibliometric analysis (2016) 0.02
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    Date
    20. 1.2019 11:22:31
    Source
    Knowledge organization for a sustainable world: challenges and perspectives for cultural, scientific, and technological sharing in a connected society : proceedings of the Fourteenth International ISKO Conference 27-29 September 2016, Rio de Janeiro, Brazil / organized by International Society for Knowledge Organization (ISKO), ISKO-Brazil, São Paulo State University ; edited by José Augusto Chaves Guimarães, Suellen Oliveira Milani, Vera Dodebei
  3. Neth, M.: Citation analysis and the Web (1998) 0.02
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    Date
    10. 1.1999 16:22:37
    Source
    Art documentation. 17(1998) no.1, S.29-33
  4. Burrell, Q.L.: Predicting future citation behavior (2003) 0.02
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    Date
    29. 3.2003 19:22:48
  5. Haycock, L.A.: Citation analysis of education dissertations for collection development (2004) 0.02
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    Date
    10. 9.2000 17:38:22
    17.12.2006 19:44:29
  6. Huang, M.-H.; Huang, W.-T.; Chang, C.-C.; Chen, D. Z.; Lin, C.-P.: The greater scattering phenomenon beyond Bradford's law in patent citation (2014) 0.02
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    Date
    22. 8.2014 17:11:29
  7. 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
  8. Nicholls, P.T.: Empirical validation of Lotka's law (1986) 0.01
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    Source
    Information processing and management. 22(1986), S.417-419
  9. Nicolaisen, J.: Citation analysis (2007) 0.01
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    Date
    13. 7.2008 19:53:22
  10. Fiala, J.: Information flood : fiction and reality (1987) 0.01
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    Source
    Thermochimica acta. 110(1987), S.11-22
  11. Su, Y.; Han, L.-F.: ¬A new literature growth model : variable exponential growth law of literature (1998) 0.01
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    Date
    22. 5.1999 19:22:35
  12. Van der Veer Martens, B.: Do citation systems represent theories of truth? (2001) 0.01
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    Date
    22. 7.2006 15:22:28
  13. Khurshid, A.; Sahai, H.: Bibliometric, scientometric and informetric distributions and laws : a selected bibliography (1991) 0.01
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    Source
    International forum on information and documentation. 16(1991) no.2, S.18-29
  14. Diodato, V.: Dictionary of bibliometrics (1994) 0.01
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    Footnote
    Rez. in: Journal of library and information science 22(1996) no.2, S.116-117 (L.C. Smith)
  15. Bookstein, A.: Informetric distributions : II. Resilience to ambiguity (1990) 0.01
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    Date
    22. 7.2006 18:55:55
  16. Herb, U.: Überwachungskapitalismus und Wissenschaftssteuerung (2019) 0.01
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    Date
    29. 6.2019 17:46:17
    4. 8.2019 19:52:29
    Issue
    [29. Juli 2019].
  17. Prathap, G.: Quantity, quality, and consistency as bibliometric indicators (2014) 0.01
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    Date
    29. 1.2014 15:59:59
  18. Bornmann, L.: On the function of university rankings (2014) 0.01
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    Date
    29. 1.2014 16:55:03
  19. Zornic, N.; Markovic, A.; Jeremic, V.: How the top 500 ARWU can provide a misleading rank (2014) 0.01
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    Date
    16. 6.2014 19:29:15
  20. Lewison, G.: ¬The work of the Bibliometrics Research Group (City University) and associates (2005) 0.01
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    Date
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Years

Languages

  • e 198
  • d 19
  • ro 1
  • sp 1
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Types

  • a 214
  • el 3
  • m 3
  • r 2
  • b 1
  • s 1
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