Search (42 results, page 1 of 3)

  • × theme_ss:"Informetrie"
  • × theme_ss:"Internet"
  • × year_i:[2000 TO 2010}
  1. Thelwall, M.; Ruschenburg, T.: Grundlagen und Forschungsfelder der Webometrie (2006) 0.02 
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    Date
    4.12.2006 12:12:22
    Source
    Information - Wissenschaft und Praxis. 57(2006) H.8, S.401-406
  2. Zhang, Y.; Jansen, B.J.; Spink, A.: Identification of factors predicting clickthrough in Web searching using neural network analysis (2009) 0.01 
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    Date
    22. 3.2009 17:49:11
    Source
    Journal of the American Society for Information Science and Technology. 60(2009) no.3, S.557-570
  3. Maharana, B.; Nayak, K.; Sahu, N.K.: Scholarly use of web resources in LIS research : a citation analysis (2006) 0.01 
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    Source
    Library review. 55(2006) no.9, S.598-607
  4. 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) 0.01 
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    Classification
    TVK (FH K)
    Footnote
    Rez. in Mitt. VÖB 63(2010) H.1/2, S.147-148 (M. Buzinkay): "Webseiten-Gestaltung und Webseiten-Analyse gehen Hand in Hand. Leider wird das Letztere selten wenn überhaupt berücksichtigt. Zu Unrecht, denn die Analyse der eigenen Maßnahmen ist zur Korrektur und Optimierung entscheidend. Auch wenn die Einsicht greift, dass die Analyse von Webseiten wichtig wäre, ist es oft ein weiter Weg zur Realisierung. Warum? Analyse heißt kontinuierlicher Aufwand, und viele sind nicht bereit beziehungsweise haben nicht die zeitlichen Ressourcen dazu. Ist man einmal zu der Überzeugung gelangt, dass man seine Web-Aktivitäten dennoch optimieren, wenn nicht schon mal gelegentlich hinterfragen sollte, dann lohnt es sich, Marco Hasslers "Web Analytics" in die Hand zu nehmen. Es ist definitiv kein Buch für einen einzigen Lese-Abend, sondern ein Band, mit welchem gearbeitet werden muss. D.h. auch hier: Web-Analyse bedeutet Arbeit und intensive Auseinandersetzung (ein Umstand, den viele nicht verstehen und akzeptieren wollen). Das Buch ist sehr dicht und bleibt trotzdem übersichtlich. Die Gliederung der Themen - von den Grundlagen der Datensammlung, über die Definition von Metriken, hin zur Optimierung von Seiten und schließlich bis zur Arbeit mit Web Analyse Werkzeugen - liefert einen roten Faden, der schön von einem Thema auf das nächste aufbaut. Dadurch fällt es auch leicht, ein eigenes Projekt begleitend zur Buchlektüre Schritt für Schritt aufzubauen. Zahlreiche Screenshots und Illustrationen erleichtern zudem das Verstehen der Zusammenhänge und Erklärungen im Text. Das Buch überzeugt aber auch durch seine Tiefe (bis auf das Kapitel, wo es um die Zusammenstellung von Personas geht) und den angenehm zu lesenden Schreibstil. Von mir kommt eine dringende Empfehlung an alle, die sich mit Online Marketing im Allgemeinen, mit Erfolgskontrolle von Websites und Web-Aktivitäten im Speziellen auseindersetzen."
    GHBS
    TVK (FH K)
    Pages
    426 S
  5. Cronin, B.: Bibliometrics and beyond : some thoughts on web-based citation analysis (2001) 0.00 
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    Source
    Journal of information science. 27(2001) no.1, S.1-7
  6. Brody, T.; Harnad, S.; Carr, L.: Earlier Web usage statistics as predictors of later citation impact (2006) 0.00 
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    Source
    Journal of the American Society for Information Science and Technology. 57(2006) no.8, S.1060-1072
  7. fwt: Webseiten liegen im Schnitt nur 19 Klicks auseinander (2001) 0.00 
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    Abstract
    "Dokumente im World Wide Web liegen durchschnittlich 19 Mausklicks voneinander entfernt - angesichts von schätzungsweise mehr als einer Milliarde Seiten erstaunlich nahe. Albert-Lazlo Barabai vom Institut für Physik der University von Notre Dame (US-Staat Indiana) stellt seine Studie in der britischen Fachzeitschrift Physics World (Juli 2001, S. 33) vor. Der Statistiker konstruierte im Rechner zunächst Modelle von großen Computernetzwerken. Grundlage für diese Abbilder war die Analyse eines kleinen Teils der Verbindungen im Web, die der Wissenschaftler automatisch von einem Programm hatte prüfen lassen. Um seine Ergebnisse zu erklären, vergleicht Barabai das World Wide Web mit den Verbindungen internationaler Fluglinien. Dort gebe es zahlreiche Flughäfen, die meist nur mit anderen Flugplätzen in ihrer näheren Umgebung in Verbindung stünden. Diese kleineren Verteiler stehen ihrerseits mit einigen wenigen großen Airports wie Frankfurt, New York oder Hongkong in Verbindung. Ähnlich sei es im Netz, wo wenige große Server die Verteilung großer Datenmengen übernähmen und weite Entfernungen überbrückten. Damit seien die Online-Wege vergleichsweise kurz. Die Untersuchung spiegelt allerdings die Situation des Jahres 1999 wider. Seinerzeit gab es vermutlich 800 Millionen Knoten."
    Source
    Frankfurter Rundschau. Nr.157 vom 10.7.2001, S.27
  8. Thelwall, M.; Vaughan, L.: Webometrics : an introduction to the special issue (2004) 0.00 
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    Source
    Journal of the American Society for Information Science and Technology. 55(2004) no.14, S.1213-1215
  9. Pernik, V.; Schlögl, C.: Möglichkeiten und Grenzen von Web Structure Mining am Beispiel von informationswissenschaftlichen Hochschulinstituten im deutschsprachigen Raum (2006) 0.00 
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    Source
    Information - Wissenschaft und Praxis. 57(2006) H.8, S.407-414
  10. Park, H.W.; Barnett, G.A.; Nam, I.-Y.: Hyperlink - affiliation network structure of top Web sites : examining affiliates with hyperlink in Korea (2002) 0.00 
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    Source
    Journal of the American Society for Information Science and technology. 53(2002) no.7, S.592-601
  11. Marchionini, G.: Co-evolution of user and organizational interfaces : a longitudinal case study of WWW dissemination of national statistics (2002) 0.00 
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    Journal of the American Society for Information Science and technology. 53(2002) no.14, S.1192-1209
  12. Bar-Ilan, J.; Peritz, B.C.: Evolution, continuity, and disappearance of documents on a specific topic an the Web : a longitudinal study of "informetrics" (2004) 0.00 
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    Journal of the American Society for Information Science and Technology. 55(2004) no.11, S.980-990
  13. Björneborn, L.; Ingwersen, P.: Toward a basic framework for Webometrics (2004) 0.00 
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    Journal of the American Society for Information Science and Technology. 55(2004) no.14, S.1216-1227
  14. Cothey, V.: Web-crawling reliability (2004) 0.00 
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    Journal of the American Society for Information Science and Technology. 55(2004) no.14, S.1228-1238
  15. Faba-Pérez, C.; Zapico-Alonso, F.; Guerrero-Bote, V.P.; Moya-Anegón, F. de: Comparative analysis of webometric measurements in thematic environments (2005) 0.00 
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    Journal of the American Society for Information Science and Technology. 56(2005) no.8, S.779-785
  16. Payne, N.; Thelwall, M.: Mathematical models for academic webs : linear relationship or non-linear power law? (2005) 0.00 
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    Source
    Information processing and management. 41(2005) no.6, S.1495-1510
  17. Bar-Ilan, J.: ¬The Web as an information source on informetrics? : A content analysis (2000) 0.00 
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    Source
    Journal of the American Society for Information Science. 51(2000) no.5, S.432-443
  18. Davis, P.M.; Cohen, S.A.: ¬The effect of the Web on undergraduate citation behavior 1996-1999 (2001) 0.00 
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  19. Koehler, W.: Web page change and persistence : a four-year longitudinal study (2002) 0.00 
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  20. Thelwall, M.; Wilkinson, D.: Finding similar academic Web sites with links, bibliometric couplings and colinks (2004) 0.00 
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