Search (5 results, page 1 of 1)

0.013273074 = product of:
  0.026546149 = sum of:
    0.026546149 = product of:
      0.053092297 = sum of:
        0.053092297 = weight(_text_:web in 2017) [ClassicSimilarity], result of:
          0.053092297 = score(doc=2017,freq=6.0), product of:
            0.17002425 = queryWeight, product of:
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.052098576 = queryNorm
            0.3122631 = fieldWeight in 2017, product of:
              2.4494898 = tf(freq=6.0), with freq of:
                6.0 = termFreq=6.0
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.0390625 = fieldNorm(doc=2017)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

Purpose - This article is an edited version of a report commissioned by the British Library and JISC to identify how the specialist researchers of the future (those born after 1993) are likely to access and interact with digital resources in five to ten years' time. The purpose is to investigate the impact of digital transition on the information behaviour of the Google Generation and to guide library and information services to anticipate and react to any new or emerging behaviours in the most effective way. Design/methodology/approach - The study was virtually longitudinal and is based on a number of extensive reviews of related literature, survey data mining and a deep log analysis of a British Library and a JISC web site intended for younger people. Findings - The study shows that much of the impact of ICTs on the young has been overestimated. The study claims that although young people demonstrate an apparent ease and familiarity with computers, they rely heavily on search engines, view rather than read and do not possess the critical and analytical skills to assess the information that they find on the web. Originality/value - The paper reports on a study that overturns the common assumption that the "Google generation" is the most web-literate.

0.010587957 = product of:
  0.021175914 = sum of:
    0.021175914 = product of:
      0.042351827 = sum of:
        0.042351827 = weight(_text_:22 in 2680) [ClassicSimilarity], result of:
          0.042351827 = score(doc=2680,freq=2.0), product of:
            0.18244034 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.052098576 = queryNorm
            0.23214069 = fieldWeight in 2680, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.046875 = fieldNorm(doc=2680)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Date

23. 2.2009 17:22:41

0.007663213 = product of:
  0.015326426 = sum of:
    0.015326426 = product of:
      0.030652853 = sum of:
        0.030652853 = weight(_text_:web in 990) [ClassicSimilarity], result of:
          0.030652853 = score(doc=990,freq=2.0), product of:
            0.17002425 = queryWeight, product of:
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.052098576 = queryNorm
            0.18028519 = fieldWeight in 990, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.0390625 = fieldNorm(doc=990)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

The article employs deep log analysis (DLA) techniques, a more sophisticated form of transaction log analysis, to demonstrate what usage data can disclose about information seeking behaviour of virtual scholars - academics, and researchers. DLA works with the raw server log data, not the processed, pre-defined and selective data provided by journal publishers. It can generate types of analysis that are not generally available via proprietary web logging software because the software filters out relevant data and makes unhelpful assumptions about the meaning of the data. DLA also enables usage data to be associated with search/navigational and/or user demographic data, hence the name 'deep'. In this connection the usage of two digital journal libraries, those of EmeraldInsight, and Blackwell Synergy are investigated. The information seeking behaviour of nearly three million users is analyzed in respect to the extent to which they penetrate the site, the number of visits made, as well as the type of items and content they view. The users are broken down by occupation, place of work, type of subscriber ("Big Deal", non-subscriber, etc.), geographical location, type of university (old and new), referrer link used, and number of items viewed in a session.

0.007663213 = product of:
  0.015326426 = sum of:
    0.015326426 = product of:
      0.030652853 = sum of:
        0.030652853 = weight(_text_:web in 1911) [ClassicSimilarity], result of:
          0.030652853 = score(doc=1911,freq=2.0), product of:
            0.17002425 = queryWeight, product of:
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.052098576 = queryNorm
            0.18028519 = fieldWeight in 1911, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.0390625 = fieldNorm(doc=1911)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

Purpose - This article aims to focus on usage data in respect to full-text downloads of journal articles, which is considered an important usage (satisfaction) metric by librarians and publishers. The purpose is to evaluate the evidence regarding full-text viewing by pooling together data on the full-text viewing of tens of thousands of users studied as part of a number of investigations of e-journal databases conducted during the Virtual Scholar research programme. Design/methodology/approach - The paper reviews the web logs of a number of electronic journal libraries including OhioLINK and ScienceDirect using Deep Log Analysis, which is a more sophisticated form of transactional log analysis. The frequency, characteristics and diversity of full-text viewing are examined. The article also features an investigation into the time spent online viewing full-text articles in order to get a clearer understanding of the significance of full-text viewing, especially in regard to reading. Findings - The main findings are that there is a great deal of variety amongst scholars in their full-text viewing habits and that a large proportion of views are very cursory in nature, although there is survey evidence to suggest that reading goes on offline. Originality/value - This is the first time that full-text viewing evidence is studied on such a large scale.

0.007663213 = product of:
  0.015326426 = sum of:
    0.015326426 = product of:
      0.030652853 = sum of:
        0.030652853 = weight(_text_:web in 961) [ClassicSimilarity], result of:
          0.030652853 = score(doc=961,freq=2.0), product of:
            0.17002425 = queryWeight, product of:
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.052098576 = queryNorm
            0.18028519 = fieldWeight in 961, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.0390625 = fieldNorm(doc=961)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

According to estimates the mobile device will soon be the main platform for searching the web, and yet our knowledge of how mobile consumers use information, and how that differs from desktops/laptops users, is imperfect. The paper sets out to correct this through an analysis of the logs of a major cultural website, Europeana. The behavior of nearly 70,000 mobile users was examined over a period of more than a year and compared with that for PC users of the same site and for the same period. The analyses conducted include: size and growth of use, time patterns of use; geographical location of users, digital collections used; comparative information-seeking behavior using dashboard metrics, clustering of users according to their information seeking, and user satisfaction. The main findings were that mobile users were the fastest-growing group and will rise rapidly to a million by December 2012 and that their visits were very different in the aggregate from those arising from fixed platforms. Mobile visits could be described as being information "lite": typically shorter, less interactive, and less content viewed per visit. Use took a social rather than office pattern, with mobile use peaking at nights and weekends. The variation between different mobile devices was large, with information seeking on the iPad similar to that for PCs and laptops and that for smartphones very different indeed. The research further confirms that information-seeking behavior is platform-specific and the latest platforms are changing it all again. Websites will have to adapt.