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    Web Metrics for Library and Information Professionals

    AvDavid Stuart

    Häftad, Engelska, 2023

    966 kr

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    Beskrivning

    Library and information professionals increasingly need to create, manage, and monitor a wide range of online content, from a library’s social media account and web sites to the new and traditional research outputs that funders expect to be made available openly online. It is important that they understand the new opportunities that web metrics provide for measuring the impact of an individual or an organisation’s content. This book provides an up-to-date introduction to a wide range of web metrics, with practical examples of how they can be best put to use.The book will begin with a wider discussion on the role of metrics, and how web metrics overlap with associated concepts with a longer library and information science history such as scientometrics and bibliometrics. It will explore the latest tools that are available, many of which have changed since the publication of the first edition, as well as how we can expect the field to change in the future with machine intelligence and artificial intelligence becoming more widely available.This new edition has been extended and updated throughout to reflect the rapidly changing nature of the field. As well as updates to the user-friendly tools and resources, there is a greater emphasis on the programming libraries that are available, as library and information professionals are increasingly willing to start engaging with data that is available programmatically. After reading the book the information professional will not only be better placed to adopt web metrics in their workplace, but also be critical of the misuse of web metrics.

    Produktinformation

    • Utgivningsdatum:2023-10-26
    • Mått:156 x 234 x 12 mm
    • Vikt:352 g
    • Format:Häftad
    • Språk:Engelska
    • Antal sidor:224
    • Upplaga:2
    • Förlag:Facet Publishing
    • ISBN:9781783305667

    Utforska kategorier

    • Referensverk och tvärvetenskap inom Samhälle och politik

    Mer om författaren

    David Stuart is an independent information professional, Bibliometrics Officer at the University of St Andrews and an Honorary Research Fellow at the University of Wolverhampton. He has published widely in in peer-reviewed academic journals and professional journals on information science, metrics, and semantic web technologies and is author of a number of books, including Practical Ontologies for Information Professionals (2016), Facilitating Access to the Web of Data (2011) and Practical Data Science for Information Professionals (2020).

    Recensioner i media

    The book begins with an overview of the metrics landscape. It covers metrics, indicators, standards, definitions and terminology. It then goes on to explore bibliometrics, altmetrics and web bibliometrics, which are familiar to many library and information professionals. Much of the content can be technical but the author does break it down where appropriate.

    Innehållsförteckning

    • 1 IntroductionMetricsIndicatorsWeb metrics and Ranganathan’s laws of library scienceWeb metrics for the library and information professionalResponsible metricsThe aim of this bookThe structure of the rest of this book2 Bibliometrics, Altmetrics, Web metrics, and WebometricsIntroductionWeb metricsInformation science metricsWeb analyticsRelational and evaluative metricsValidating the resultsConclusion3 Data Collection ToolsIntroductionThe anatomy of a URL, web links and the structure of the webSearch engines 1.0Web crawlersSearch enginesPost Search Engine 2.0: fragmentationConclusion4 Evaluating Web ImpactIntroductionWebsitesBlogsWikisInternal v. External MetricsInternal metricsExternal metricsA systematic approach to content analysisConclusion5 Evaluating Social Media ImpactIntroductionAspects of social network sitesTypology of social network sitesThe most popular social media servicesSentiment analysisConclusion**6 Relational Web Metrics and Social Network **AnalysisIntroductionSocial network analysis methodsNode centralityCluster identificationStatistical properties of the graphTopic modellingSources for relational network analysisTwo R ExamplesConclusion7 Web BibliometricsIntroductionMore bibliographic itemsNew bibliographic sourcesFull text analysisGreater ContextConclusion8 Web Metrics for Data and CodeIntroductionThe web of dataFrom data documents……to a semantic web?The Importance of CodeGitHub StatisticsA Brief Exploration of Code-metrics with R Conclusion9 The Future of Web Metrics and the Library and Information ProfessionalIntroductionHow far we have comeThe future of web metricsThe future of the library and information professional and web metrics