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020 _a9783031022890
024 7 _a10.1007/978-3-031-02289-0
_2doi
040 _aES-MaUEC
_bspa
_cES-MaUEC
_dES-MaUEC
050 4 _aQA76.9.H85
_b2015 EB
100 1 _aLalmas, Mounia
_eautor
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_9686360
245 1 0 _aMeasuring User Engagement
_cby Mounia Lalmas, Heather O'Brien, Elad Yom-Tov
250 _a1st edition 2015
264 1 _aCham
_bSpringer International Publishing
_c2015
300 _a1 recurso en línea (XV, 116 páginas)
336 _atexto
_btxt
_2rdacontent
337 _aelectrónico
_bc
_2rdamedia
338 _arecurso electrónico
_bcr
_2rdacarrier
347 _aarchivo de texto
_bPDF
490 0 _aSynthesis Lectures on Information Concepts Retrieval and Services
_x1947-9468
505 0 _aPreface -- Acknowledgments -- Introduction and Scope -- Approaches Based on Self-Report Methods -- Approaches Based on Physiological Measurements -- Approaches Based on Web Analytics -- Beyond Desktop, Single Site, and Single Task -- Enhancing the Rigor of User Engagement Methods and Measures -- Conclusions and Future Research Directions -- Bibliography -- Authors' Biographies -- Index .
520 _aUser engagement refers to the quality of the user experience that emphasizes the positive aspects of interacting with an online application and, in particular, the desire to use that application longer and repeatedly. User engagement is a key concept in the design of online applications (whether for desktop, tablet or mobile), motivated by the observation that successful applications are not just used, but are engaged with. Users invest time, attention, and emotion in their use of technology, and seek to satisfy pragmatic and hedonic needs. Measurement is critical for evaluating whether online applications are able to successfully engage users, and may inform the design of and use of applications. User engagement is a multifaceted, complex phenomenon; this gives rise to a number of potential measurement approaches. Common ways to evaluate user engagement include using self-report measures, e.g., questionnaires; observational methods, e.g. facial expression analysis, speech analysis; neuro-physiological signal processing methods, e.g., respiratory and cardiovascular accelerations and decelerations, muscle spasms; and web analytics, e.g., number of site visits, click depth. These methods represent various trade-offs in terms of the setting (laboratory versus ``in the wild''), object of measurement (user behaviour, affect or cognition) and scale of data collected. For instance, small-scale user studies are deep and rich, but limited in terms of generalizability, whereas large-scale web analytic studies are powerful but negate users' motivation and context. The focus of this book is how user engagement is currently being measured and various considerations for its measurement. Our goal is to leave readers with an appreciation of the various ways in which to measure user engagement, and their associated strengths and weaknesses. We emphasize the multifaceted nature of user engagement and the unique contextual constraints that come to bear upon attempts to measure engagement in different settings, and across different user groups and web domains. At the same time, this book advocates for the development of ``good'' measures and good measurement practices that will advance the study of user engagement and improve our understanding of this construct, which has become so vital in our wired world.
988 _aSynthesis Collection of Technology_2015
650 7 _2embne
_9155848
_aInteracción hombre-ordenador
700 1 _aO'Brien, Heather
_d1977-
_eautor
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_998212
700 1 _aYom-Tov, Elad
_eautor
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_9686430
776 0 8 _iPrinted edition:
_z9783031011610
776 0 8 _iPrinted edition:
_z9783031034176
856 4 0 _uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-02289-0
_zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942 _2lcc
_cLE
998 _dz
_eb
_zSI
_b02/2023