Search (3 results, page 1 of 1)

0.014447878 = product of:
  0.028895756 = sum of:
    0.015314223 = weight(_text_:library in 4052) [ClassicSimilarity], result of:
      0.015314223 = score(doc=4052,freq=2.0), product of:
        0.1317883 = queryWeight, product of:
          2.6293786 = idf(docFreq=8668, maxDocs=44218)
          0.050121464 = queryNorm
        0.11620321 = fieldWeight in 4052, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          2.6293786 = idf(docFreq=8668, maxDocs=44218)
          0.03125 = fieldNorm(doc=4052)
    0.013581533 = product of:
      0.027163066 = sum of:
        0.027163066 = weight(_text_:22 in 4052) [ClassicSimilarity], result of:
          0.027163066 = score(doc=4052,freq=2.0), product of:
            0.17551683 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.050121464 = queryNorm
            0.15476047 = fieldWeight in 4052, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.03125 = fieldNorm(doc=4052)
      0.5 = coord(1/2)
  0.5 = coord(2/4)

Abstract

Purpose The purpose of this paper is to investigate the relationship between internet filtering, emotions and information-seeking behaviour. Design/methodology/approach In total, 15 postgraduate students at an Iranian university participated in the study which involved a questionnaire, search tasks with think aloud narratives, and interviews. Findings Internet content filtering results in some changes in the information-seeking behaviour of users. Users who face website blocking use a variety of methods to bypass filtering, mostly by using anti-filter software. Filtering encourages users to use channels such as social networking services to share resources and it increases the use of library material by some of the users. Users who face filtering during their search are more likely to visit more pages of results and click on more hits in the results, unlike users who do not experience filtering who rarely go past the first page. Blocking users' access to content stimulates their curiosity and they become more determined to access the content. In terms of the affective aspect, filtering causes several negative emotions (e.g. anger, disgust, sadness and anxiety) and the main reason for these emotions is not the inability to access information but the feeling of being controlled and not having freedom. Research limitations/implications The study was limited to a small number of postgraduate students in social sciences and not generalisable to all user groups. The implication is that in countries where filtering is used, libraries can play an important role in serving users and reducing users negative emotions, especially if libraries can take advantage of technologies such as social media for their services. Originality/value This is first study to address the effects of internet filtering on information-seeking behaviour and emotions. The study shows that internet filtering causes negative emotions and results in some changes in information-seeking behaviour.

Date

20. 1.2015 18:30:22

0.012924549 = product of:
  0.051698197 = sum of:
    0.051698197 = weight(_text_:digital in 3113) [ClassicSimilarity], result of:
      0.051698197 = score(doc=3113,freq=2.0), product of:
        0.19770671 = queryWeight, product of:
          3.944552 = idf(docFreq=2326, maxDocs=44218)
          0.050121464 = queryNorm
        0.26148933 = fieldWeight in 3113, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.944552 = idf(docFreq=2326, maxDocs=44218)
          0.046875 = fieldNorm(doc=3113)
  0.25 = coord(1/4)

0.010770457 = product of:
  0.043081827 = sum of:
    0.043081827 = weight(_text_:digital in 961) [ClassicSimilarity], result of:
      0.043081827 = score(doc=961,freq=2.0), product of:
        0.19770671 = queryWeight, product of:
          3.944552 = idf(docFreq=2326, maxDocs=44218)
          0.050121464 = queryNorm
        0.21790776 = fieldWeight in 961, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.944552 = idf(docFreq=2326, maxDocs=44218)
          0.0390625 = fieldNorm(doc=961)
  0.25 = coord(1/4)

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.