Search (133 results, page 1 of 7)

  • × language_ss:"e"
  • × theme_ss:"Internet"
  • × year_i:[2010 TO 2020}
  1. Kalman, Y.M.; Ravid, G.: Filing, piling, and everything in between : the dynamics of E-mail inbox management (2015) 0.03 
    0.03418126 = product of:
  0.06836252 = sum of:
    0.059307255 = weight(_text_:management in 2336) [ClassicSimilarity], result of:
      0.059307255 = score(doc=2336,freq=8.0), product of:
        0.15925534 = queryWeight, product of:
          3.3706124 = idf(docFreq=4130, maxDocs=44218)
          0.047248192 = queryNorm
        0.37240356 = fieldWeight in 2336, product of:
          2.828427 = tf(freq=8.0), with freq of:
            8.0 = termFreq=8.0
          3.3706124 = idf(docFreq=4130, maxDocs=44218)
          0.0390625 = fieldNorm(doc=2336)
    0.009055263 = product of:
      0.018110527 = sum of:
        0.018110527 = weight(_text_:science in 2336) [ClassicSimilarity], result of:
          0.018110527 = score(doc=2336,freq=2.0), product of:
            0.124457374 = queryWeight, product of:
              2.6341193 = idf(docFreq=8627, maxDocs=44218)
              0.047248192 = queryNorm
            0.1455159 = fieldWeight in 2336, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              2.6341193 = idf(docFreq=8627, maxDocs=44218)
              0.0390625 = fieldNorm(doc=2336)
      0.5 = coord(1/2)
  0.5 = coord(2/4)
    Abstract
    Managing the constant flow of incoming messages is a daily challenge faced by knowledge workers who use technologies such as e-mail and other digital communication tools. This study focuses on the most ubiquitous of these technologies, e-mail, and unobtrusively explores the ongoing inbox-management activities of thousands of users worldwide over a period of 8 months. The study describes the dynamics of these inboxes throughout the day and the week as users strive to handle incoming messages, read them, classify them, respond to them in a timely manner, and archive them for future reference, all while carrying out the daily tasks of knowledge workers. It then tests several hypotheses about the influence of specific inbox-management behaviors in mitigating the causes of e-mail overload, and proposes a continuous index that quantifies one of these inbox-management behaviors. This inbox clearing index (ICI) expands on the widely cited trichotomous classification of users into frequent filers, spring cleaners, and no filers, as suggested by Whittaker and Sidner (1996). We propose that the ICI allows shifting the focus, from classifying users to characterizing a diversity of user behaviors and measuring the relationships between these behaviors and desired outcomes.
    Source
    Journal of the Association for Information Science and Technology. 66(2015) no.12, S.2540-2552
  2. Tashiro, H.; Lau, A.; Mori, J.; Fujii, N.; Kajikawa, Y.: E-mail networks and leadership performance (2012) 0.03 
    0.030595098 = product of:
  0.061190195 = sum of:
    0.050323877 = weight(_text_:management in 77) [ClassicSimilarity], result of:
      0.050323877 = score(doc=77,freq=4.0), product of:
        0.15925534 = queryWeight, product of:
          3.3706124 = idf(docFreq=4130, maxDocs=44218)
          0.047248192 = queryNorm
        0.31599492 = fieldWeight in 77, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          3.3706124 = idf(docFreq=4130, maxDocs=44218)
          0.046875 = fieldNorm(doc=77)
    0.010866316 = product of:
      0.021732632 = sum of:
        0.021732632 = weight(_text_:science in 77) [ClassicSimilarity], result of:
          0.021732632 = score(doc=77,freq=2.0), product of:
            0.124457374 = queryWeight, product of:
              2.6341193 = idf(docFreq=8627, maxDocs=44218)
              0.047248192 = queryNorm
            0.17461908 = fieldWeight in 77, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              2.6341193 = idf(docFreq=8627, maxDocs=44218)
              0.046875 = fieldNorm(doc=77)
      0.5 = coord(1/2)
  0.5 = coord(2/4)
    Abstract
    Online communication is an indispensable tool for communication and management. The network structure of communication is considered to affect team and individual performances, but it has not been not empirically tested. In this article, we collected a set of 1-month e-mail logs of a company and conducted an e-mail network analysis. We calculated the network centralities of 72 managerial candidates, and investigated the relationship between positions in the network and leadership performance with partial least squares structural equation modeling. Betweenness and in-degree network centralities of those middle managers are correlated with their leadership performance; on the other hand, for this management group, out-degree has no correlation, and PageRank is a negative indicator of leadership. Leaders with high performance are trusted in their communities as a hub of the information channel of the communication network.
    Source
    Journal of the American Society for Information Science and Technology. 63(2012) no.3, S.600-606
  3. Sood, S.O.; Churchill, E.F.; Antin, J.: Automatic identification of personal insults on social news sites (2012) 0.03 
    0.030208427 = product of:
  0.060416855 = sum of:
    0.05136159 = weight(_text_:management in 4976) [ClassicSimilarity], result of:
      0.05136159 = score(doc=4976,freq=6.0), product of:
        0.15925534 = queryWeight, product of:
          3.3706124 = idf(docFreq=4130, maxDocs=44218)
          0.047248192 = queryNorm
        0.32251096 = fieldWeight in 4976, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          3.3706124 = idf(docFreq=4130, maxDocs=44218)
          0.0390625 = fieldNorm(doc=4976)
    0.009055263 = product of:
      0.018110527 = sum of:
        0.018110527 = weight(_text_:science in 4976) [ClassicSimilarity], result of:
          0.018110527 = score(doc=4976,freq=2.0), product of:
            0.124457374 = queryWeight, product of:
              2.6341193 = idf(docFreq=8627, maxDocs=44218)
              0.047248192 = queryNorm
            0.1455159 = fieldWeight in 4976, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              2.6341193 = idf(docFreq=8627, maxDocs=44218)
              0.0390625 = fieldNorm(doc=4976)
      0.5 = coord(1/2)
  0.5 = coord(2/4)
    Abstract
    As online communities grow and the volume of user-generated content increases, the need for community management also rises. Community management has three main purposes: to create a positive experience for existing participants, to promote appropriate, socionormative behaviors, and to encourage potential participants to make contributions. Research indicates that the quality of content a potential participant sees on a site is highly influential; off-topic, negative comments with malicious intent are a particularly strong boundary to participation or set the tone for encouraging similar contributions. A problem for community managers, therefore, is the detection and elimination of such undesirable content. As a community grows, this undertaking becomes more daunting. Can an automated system aid community managers in this task? In this paper, we address this question through a machine learning approach to automatic detection of inappropriate negative user contributions. Our training corpus is a set of comments from a news commenting site that we tasked Amazon Mechanical Turk workers with labeling. Each comment is labeled for the presence of profanity, insults, and the object of the insults. Support vector machines trained on these data are combined with relevance and valence analysis systems in a multistep approach to the detection of inappropriate negative user contributions. The system shows great potential for semiautomated community management.
    Source
    Journal of the American Society for Information Science and Technology. 63(2012) no.2, S.270-285
  4. Yang, S.; Han, R.; Ding, J.; Song, Y.: ¬The distribution of Web citations (2012) 0.03 
    0.027202684 = product of:
  0.05440537 = sum of:
    0.035584353 = weight(_text_:management in 2735) [ClassicSimilarity], result of:
      0.035584353 = score(doc=2735,freq=2.0), product of:
        0.15925534 = queryWeight, product of:
          3.3706124 = idf(docFreq=4130, maxDocs=44218)
          0.047248192 = queryNorm
        0.22344214 = fieldWeight in 2735, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.3706124 = idf(docFreq=4130, maxDocs=44218)
          0.046875 = fieldNorm(doc=2735)
    0.018821014 = product of:
      0.03764203 = sum of:
        0.03764203 = weight(_text_:science in 2735) [ClassicSimilarity], result of:
          0.03764203 = score(doc=2735,freq=6.0), product of:
            0.124457374 = queryWeight, product of:
              2.6341193 = idf(docFreq=8627, maxDocs=44218)
              0.047248192 = queryNorm
            0.30244917 = fieldWeight in 2735, product of:
              2.4494898 = tf(freq=6.0), with freq of:
                6.0 = termFreq=6.0
              2.6341193 = idf(docFreq=8627, maxDocs=44218)
              0.046875 = fieldNorm(doc=2735)
      0.5 = coord(1/2)
  0.5 = coord(2/4)
    Abstract
    A substantial amount of research has focused on the persistence or availability of Web citations. The present study analyzes Web citation distributions. Web citations are defined as the mentions of the URLs of Web pages (Web resources) as references in academic papers. The present paper primarily focuses on the analysis of the URLs of Web citations and uses three sets of data, namely, Set 1 from the Humanities and Social Science Index in China (CSSCI, 1998-2009), Set 2 from the publications of two international computer science societies, Communications of the ACM and IEEE Computer (1995-1999), and Set 3 from the medical science database, MEDLINE, of the National Library of Medicine (1994-2006). Web citation distributions are investigated based on Web site types, Web page types, URL frequencies, URL depths, URL lengths, and year of article publication. Results show significant differences in the Web citation distributions among the three data sets. However, when the URLs of Web citations with the same hostnames are aggregated, the distributions in the three data sets are consistent with the power law (the Lotka function).
    Source
    Information processing and management. 48(2012) no.4, S.779-790
  5. Capra, R.; Khanova, J.; Ramdeen, S.: Work and personal e-mail use by university employees : PIM practices across domain boundaries (2013) 0.03 
    0.025495915 = product of:
  0.05099183 = sum of:
    0.041936565 = weight(_text_:management in 749) [ClassicSimilarity], result of:
      0.041936565 = score(doc=749,freq=4.0), product of:
        0.15925534 = queryWeight, product of:
          3.3706124 = idf(docFreq=4130, maxDocs=44218)
          0.047248192 = queryNorm
        0.2633291 = fieldWeight in 749, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          3.3706124 = idf(docFreq=4130, maxDocs=44218)
          0.0390625 = fieldNorm(doc=749)
    0.009055263 = product of:
      0.018110527 = sum of:
        0.018110527 = weight(_text_:science in 749) [ClassicSimilarity], result of:
          0.018110527 = score(doc=749,freq=2.0), product of:
            0.124457374 = queryWeight, product of:
              2.6341193 = idf(docFreq=8627, maxDocs=44218)
              0.047248192 = queryNorm
            0.1455159 = fieldWeight in 749, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              2.6341193 = idf(docFreq=8627, maxDocs=44218)
              0.0390625 = fieldNorm(doc=749)
      0.5 = coord(1/2)
  0.5 = coord(2/4)
    Abstract
    In this article, we present findings from a survey of nearly 600 university employees' e-mail use. The study provides a detailed comparison of use patterns between work and personal e-mail accounts. Our results suggest that users engage in more "keeping" behaviors with work e-mail than with personal e-mail-respondents reported more frequent use of keeping actions and larger inbox sizes for their work accounts. However, we found correlations between individual respondents' e-mail behaviors in the two contexts, indicating that personal preferences can play a role. We also report results pointing to e-mail as an important boundary management artifact. We show evidence that the use of multiple e-mail accounts may be a work-personal boundary placement strategy, but also observe that a fair amount of boundary permeation occurs through e-mail. To our knowledge, this study is one of the first to compare e-mail use in both work and personal contexts across the same sample. Our findings extend prior research on personal information management regarding e-mail use, and help inform the role of e-mail in managing work-personal boundaries. The results have implications for the design of e-mail systems, organizational e-mail policies, user training, and understanding the impacts of technology on daily life.
    Source
    Journal of the American Society for Information Science and Technology. 64(2013) no.5, S.1029-1044
  6. Ghosh, J.; Kshitij, A.: ¬An integrated examination of collaboration coauthorship networks through structural cohesion, holes, hierarchy, and percolating clusters (2014) 0.03 
    0.025475822 = product of:
  0.050951645 = sum of:
    0.035584353 = weight(_text_:management in 1333) [ClassicSimilarity], result of:
      0.035584353 = score(doc=1333,freq=2.0), product of:
        0.15925534 = queryWeight, product of:
          3.3706124 = idf(docFreq=4130, maxDocs=44218)
          0.047248192 = queryNorm
        0.22344214 = fieldWeight in 1333, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.3706124 = idf(docFreq=4130, maxDocs=44218)
          0.046875 = fieldNorm(doc=1333)
    0.015367293 = product of:
      0.030734586 = sum of:
        0.030734586 = weight(_text_:science in 1333) [ClassicSimilarity], result of:
          0.030734586 = score(doc=1333,freq=4.0), product of:
            0.124457374 = queryWeight, product of:
              2.6341193 = idf(docFreq=8627, maxDocs=44218)
              0.047248192 = queryNorm
            0.24694869 = fieldWeight in 1333, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              2.6341193 = idf(docFreq=8627, maxDocs=44218)
              0.046875 = fieldNorm(doc=1333)
      0.5 = coord(1/2)
  0.5 = coord(2/4)
    Abstract
    Structural cohesion, hierarchy, holes, and percolating clusters share a complementary existence in many social networks. Although the individual influences of these attributes on the structure and function of a network have been analyzed in detail, a more accurate picture emerges in proper perspective and context only when research methods are employed to integrate their collective impacts on the network. In a major research project, we have undertaken this examination. This paper presents an extract from this project, using a global network assessment of these characteristics. We apply our methods to analyze the collaboration networks of a subset of researchers in India through their coauthored papers in peer-reviewed journals and conference proceedings in management science, including related areas of information technology and economics. We find the Indian networks to be currently suffering from a high degree of fragmentation, which severely restricts researchers' long-rage connectivities in the networks. Comparisons are made with networks of a similar sample of researchers working in the United States.
    Source
    Journal of the Association for Information Science and Technology. 65(2014) no.8, S.1639-1661
  7. Sanchiza, M.; Chinb, J.; Chevaliera, A.; Fuc, W.T.; Amadieua, F.; Hed, J.: Searching for information on the web : impact of cognitive aging, prior domain knowledge and complexity of the search problems (2017) 0.02 
    0.023225334 = product of:
  0.046450667 = sum of:
    0.035584353 = weight(_text_:management in 3294) [ClassicSimilarity], result of:
      0.035584353 = score(doc=3294,freq=2.0), product of:
        0.15925534 = queryWeight, product of:
          3.3706124 = idf(docFreq=4130, maxDocs=44218)
          0.047248192 = queryNorm
        0.22344214 = fieldWeight in 3294, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.3706124 = idf(docFreq=4130, maxDocs=44218)
          0.046875 = fieldNorm(doc=3294)
    0.010866316 = product of:
      0.021732632 = sum of:
        0.021732632 = weight(_text_:science in 3294) [ClassicSimilarity], result of:
          0.021732632 = score(doc=3294,freq=2.0), product of:
            0.124457374 = queryWeight, product of:
              2.6341193 = idf(docFreq=8627, maxDocs=44218)
              0.047248192 = queryNorm
            0.17461908 = fieldWeight in 3294, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              2.6341193 = idf(docFreq=8627, maxDocs=44218)
              0.046875 = fieldNorm(doc=3294)
      0.5 = coord(1/2)
  0.5 = coord(2/4)
    Content
    Vgl.: http://www.sciencedirect.com/science/article/pii/S0306457316301923 [http://dx.doi.org/10.1016/j.ipm.2016.09.003].
    Source
    Information processing and management. 53(2017) no.1, S.281-294
  8. Wu, P.F.: ¬The privacy paradox in the context of online social networking : a self-identity perspective (2019) 0.02 
    0.023225334 = product of:
  0.046450667 = sum of:
    0.035584353 = weight(_text_:management in 4984) [ClassicSimilarity], result of:
      0.035584353 = score(doc=4984,freq=2.0), product of:
        0.15925534 = queryWeight, product of:
          3.3706124 = idf(docFreq=4130, maxDocs=44218)
          0.047248192 = queryNorm
        0.22344214 = fieldWeight in 4984, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.3706124 = idf(docFreq=4130, maxDocs=44218)
          0.046875 = fieldNorm(doc=4984)
    0.010866316 = product of:
      0.021732632 = sum of:
        0.021732632 = weight(_text_:science in 4984) [ClassicSimilarity], result of:
          0.021732632 = score(doc=4984,freq=2.0), product of:
            0.124457374 = queryWeight, product of:
              2.6341193 = idf(docFreq=8627, maxDocs=44218)
              0.047248192 = queryNorm
            0.17461908 = fieldWeight in 4984, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              2.6341193 = idf(docFreq=8627, maxDocs=44218)
              0.046875 = fieldNorm(doc=4984)
      0.5 = coord(1/2)
  0.5 = coord(2/4)
    Abstract
    Drawing on identity theory and privacy research, this article argues that the need for self-identity is a key factor affecting people's privacy behavior in social networking sites. I first unpack the mainstream, autonomy-centric discourse of privacy, and then present a research model that illustrates a possible new theorization of the relationship between self-identity and information privacy. An empirical study with Facebook users confirms the main hypotheses. In particular, the data show that the need for self-identity is positively related to privacy management behaviors, which in turn result in increased self-disclosure in online social networks. I subsequently argue that the so-called "privacy paradox" is not a paradox per se in the context of online social networking; rather, privacy concerns reflect the ideology of an autonomous self, whereas social construction of self-identity explains voluntary self-disclosure.
    Source
    Journal of the Association for Information Science and Technology. 70(2019) no.3, S.207-217
  9. Zimmer, M.; Proferes, N.J.: ¬A topology of Twitter research : disciplines, methods, and ethics (2014) 0.02 
    0.02282866 = product of:
  0.04565732 = sum of:
    0.029653627 = weight(_text_:management in 1622) [ClassicSimilarity], result of:
      0.029653627 = score(doc=1622,freq=2.0), product of:
        0.15925534 = queryWeight, product of:
          3.3706124 = idf(docFreq=4130, maxDocs=44218)
          0.047248192 = queryNorm
        0.18620178 = fieldWeight in 1622, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.3706124 = idf(docFreq=4130, maxDocs=44218)
          0.0390625 = fieldNorm(doc=1622)
    0.016003694 = product of:
      0.03200739 = sum of:
        0.03200739 = weight(_text_:22 in 1622) [ClassicSimilarity], result of:
          0.03200739 = score(doc=1622,freq=2.0), product of:
            0.16545512 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.047248192 = queryNorm
            0.19345059 = fieldWeight in 1622, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.0390625 = fieldNorm(doc=1622)
      0.5 = coord(1/2)
  0.5 = coord(2/4)
    Date
    20. 1.2015 18:30:22
    Source
    Aslib journal of information management. 66(2014) no.3, S.134-155
  10. Min, J.: Personal information concerns and provision in social network sites : interplay between secure preservation and true presentation (2016) 0.02 
    0.019354446 = product of:
  0.03870889 = sum of:
    0.029653627 = weight(_text_:management in 2489) [ClassicSimilarity], result of:
      0.029653627 = score(doc=2489,freq=2.0), product of:
        0.15925534 = queryWeight, product of:
          3.3706124 = idf(docFreq=4130, maxDocs=44218)
          0.047248192 = queryNorm
        0.18620178 = fieldWeight in 2489, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.3706124 = idf(docFreq=4130, maxDocs=44218)
          0.0390625 = fieldNorm(doc=2489)
    0.009055263 = product of:
      0.018110527 = sum of:
        0.018110527 = weight(_text_:science in 2489) [ClassicSimilarity], result of:
          0.018110527 = score(doc=2489,freq=2.0), product of:
            0.124457374 = queryWeight, product of:
              2.6341193 = idf(docFreq=8627, maxDocs=44218)
              0.047248192 = queryNorm
            0.1455159 = fieldWeight in 2489, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              2.6341193 = idf(docFreq=8627, maxDocs=44218)
              0.0390625 = fieldNorm(doc=2489)
      0.5 = coord(1/2)
  0.5 = coord(2/4)
    Abstract
    Encouraging users of social network sites (SNS) to actively provide personal information is vital if SNS are to prosper, but privacy concerns have hindered users from giving such information. Previous research dealing with privacy concerns has studied mostly worries about information misuse, focusing on the protection aspects of privacy. By adopting an interpersonal conception of privacy and communication privacy management theory, this study offers a new way of understanding privacy concerns by examining the social and presentational aspects of privacy. It examines privacy concerns in terms not only of others' misuse but of others' misunderstanding and personal information in terms not only of identity but of self-presentational information. Furthermore, it investigates the ways in which information and social risks inherent in SNS influence privacy concerns. A structural equation modeling analysis of a cross-sectional survey of 396 Facebook users finds that longer usage does not alleviate the impact of information risk on either concern, that a greater proportion of offline friends among one's SNS friends aggravates the impact of social risk on both concerns, and that concerns about information misuse affect the provision only of identity information, whereas concerns about information misunderstanding affect the provision of both identity and self-presentational information.
    Source
    Journal of the Association for Information Science and Technology. 67(2016) no.1, S.26-42
  11. Vishwanath, A.; Xu, W.; Ngoh, Z.: How people protect their privacy on facebook : a cost-benefit view (2018) 0.02 
    0.019354446 = product of:
  0.03870889 = sum of:
    0.029653627 = weight(_text_:management in 4223) [ClassicSimilarity], result of:
      0.029653627 = score(doc=4223,freq=2.0), product of:
        0.15925534 = queryWeight, product of:
          3.3706124 = idf(docFreq=4130, maxDocs=44218)
          0.047248192 = queryNorm
        0.18620178 = fieldWeight in 4223, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.3706124 = idf(docFreq=4130, maxDocs=44218)
          0.0390625 = fieldNorm(doc=4223)
    0.009055263 = product of:
      0.018110527 = sum of:
        0.018110527 = weight(_text_:science in 4223) [ClassicSimilarity], result of:
          0.018110527 = score(doc=4223,freq=2.0), product of:
            0.124457374 = queryWeight, product of:
              2.6341193 = idf(docFreq=8627, maxDocs=44218)
              0.047248192 = queryNorm
            0.1455159 = fieldWeight in 4223, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              2.6341193 = idf(docFreq=8627, maxDocs=44218)
              0.0390625 = fieldNorm(doc=4223)
      0.5 = coord(1/2)
  0.5 = coord(2/4)
    Abstract
    Realizing the many benefits from Facebook require users to share information reciprocally, which has overtime created trillions of bytes of information online-a treasure trove for cybercriminals. The sole protection for any user are three sets of privacy protections afforded by Facebook: settings that control information privacy (i.e., security of social media accounts and identity information), accessibility privacy or anonymity (i.e., manage who can connect with a user), and those that control expressive privacy (i.e., control who can see a user's posts and tag you). Using these settings, however, involves a trade-off between making oneself accessible and thereby vulnerable to potential attacks, or enacting stringent protections that could potentially make someone inaccessible thereby reducing the benefits that are accruable through social media. Using two theoretical frameworks, Uses and Gratifications (U&G) and Protection Motivation Theory (PMT), the research examined how individuals congitvely juxtaposed the cost of maintaining privacy through the use of these settings against the benefits of openness. The application of the U&G framework revealed that social need fulfillment was the single most significant benefit driving privacy management. From the cost standpoint, the PMT framework pointed to perceived severity impacting expressive and information privacy, and perceived susceptability influencing accessibility privacy.
    Source
    Journal of the Association for Information Science and Technology. 69(2018) no.5, S.700-709
  12. Zielinski, K.; Nielek, R.; Wierzbicki, A.; Jatowt, A.: Computing controversy : formal model and algorithms for detecting controversy on Wikipedia and in search queries (2018) 0.02 
    0.019354446 = product of:
  0.03870889 = sum of:
    0.029653627 = weight(_text_:management in 5093) [ClassicSimilarity], result of:
      0.029653627 = score(doc=5093,freq=2.0), product of:
        0.15925534 = queryWeight, product of:
          3.3706124 = idf(docFreq=4130, maxDocs=44218)
          0.047248192 = queryNorm
        0.18620178 = fieldWeight in 5093, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.3706124 = idf(docFreq=4130, maxDocs=44218)
          0.0390625 = fieldNorm(doc=5093)
    0.009055263 = product of:
      0.018110527 = sum of:
        0.018110527 = weight(_text_:science in 5093) [ClassicSimilarity], result of:
          0.018110527 = score(doc=5093,freq=2.0), product of:
            0.124457374 = queryWeight, product of:
              2.6341193 = idf(docFreq=8627, maxDocs=44218)
              0.047248192 = queryNorm
            0.1455159 = fieldWeight in 5093, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              2.6341193 = idf(docFreq=8627, maxDocs=44218)
              0.0390625 = fieldNorm(doc=5093)
      0.5 = coord(1/2)
  0.5 = coord(2/4)
    Abstract
    Controversy is a complex concept that has been attracting attention of scholars from diverse fields. In the era of Internet and social media, detecting controversy and controversial concepts by the means of automatic methods is especially important. Web searchers could be alerted when the contents they consume are controversial or when they attempt to acquire information on disputed topics. Presenting users with the indications and explanations of the controversy should offer them chance to see the "wider picture" rather than letting them obtain one-sided views. In this work we first introduce a formal model of controversy as the basis of computational approaches to detecting controversial concepts. Then we propose a classification based method for automatic detection of controversial articles and categories in Wikipedia. Next, we demonstrate how to use the obtained results for the estimation of the controversy level of search queries. The proposed method can be incorporated into search engines as a component responsible for detection of queries related to controversial topics. The method is independent of the search engine's retrieval and search results recommendation algorithms, and is therefore unaffected by a possible filter bubble. Our approach can be also applied in Wikipedia or other knowledge bases for supporting the detection of controversy and content maintenance. Finally, we believe that our results could be useful for social science researchers for understanding the complex nature of controversy and in fostering their studies.
    Source
    Information processing and management. 54(2018) no.1, S.14-36
  13. Jamali, H.R.; Shahbaztabar, P.: ¬The effects of internet filtering on users' information-seeking behaviour and emotions (2017) 0.02 
    0.018262928 = product of:
  0.036525857 = sum of:
    0.023722902 = weight(_text_:management in 4052) [ClassicSimilarity], result of:
      0.023722902 = score(doc=4052,freq=2.0), product of:
        0.15925534 = queryWeight, product of:
          3.3706124 = idf(docFreq=4130, maxDocs=44218)
          0.047248192 = queryNorm
        0.14896142 = fieldWeight in 4052, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.3706124 = idf(docFreq=4130, maxDocs=44218)
          0.03125 = fieldNorm(doc=4052)
    0.012802956 = product of:
      0.025605911 = sum of:
        0.025605911 = weight(_text_:22 in 4052) [ClassicSimilarity], result of:
          0.025605911 = score(doc=4052,freq=2.0), product of:
            0.16545512 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.047248192 = 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)
    Date
    20. 1.2015 18:30:22
    Source
    Aslib journal of information management. 69(2017) no.4, S.408-425
  14. Griesbaum, J.; Mahrholz, N.; Kiedrowski, K. von Löwe; Rittberger, M.: Knowledge generation in online forums : a case study in the German educational domain (2015) 0.02 
    0.018262928 = product of:
  0.036525857 = sum of:
    0.023722902 = weight(_text_:management in 4440) [ClassicSimilarity], result of:
      0.023722902 = score(doc=4440,freq=2.0), product of:
        0.15925534 = queryWeight, product of:
          3.3706124 = idf(docFreq=4130, maxDocs=44218)
          0.047248192 = queryNorm
        0.14896142 = fieldWeight in 4440, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.3706124 = idf(docFreq=4130, maxDocs=44218)
          0.03125 = fieldNorm(doc=4440)
    0.012802956 = product of:
      0.025605911 = sum of:
        0.025605911 = weight(_text_:22 in 4440) [ClassicSimilarity], result of:
          0.025605911 = score(doc=4440,freq=2.0), product of:
            0.16545512 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.047248192 = queryNorm
            0.15476047 = fieldWeight in 4440, 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=4440)
      0.5 = coord(1/2)
  0.5 = coord(2/4)
    Date
    20. 1.2015 18:30:22
    Source
    Aslib journal of information management. 67(2015) no.1, S.2-26
  15. Oguz, F.; Koehler, W.: URL decay at year 20 : a research note (2016) 0.02 
    0.01754127 = product of:
  0.07016508 = sum of:
    0.07016508 = sum of:
      0.02535474 = weight(_text_:science in 2651) [ClassicSimilarity], result of:
        0.02535474 = score(doc=2651,freq=2.0), product of:
          0.124457374 = queryWeight, product of:
            2.6341193 = idf(docFreq=8627, maxDocs=44218)
            0.047248192 = queryNorm
          0.20372227 = fieldWeight in 2651, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            2.6341193 = idf(docFreq=8627, maxDocs=44218)
            0.0546875 = fieldNorm(doc=2651)
      0.044810344 = weight(_text_:22 in 2651) [ClassicSimilarity], result of:
        0.044810344 = score(doc=2651,freq=2.0), product of:
          0.16545512 = queryWeight, product of:
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.047248192 = queryNorm
          0.2708308 = fieldWeight in 2651, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.0546875 = fieldNorm(doc=2651)
  0.25 = coord(1/4)
    Date
    22. 1.2016 14:37:14
    Source
    Journal of the Association for Information Science and Technology. 67(2016) no.2, S.477-479
  16. Okoli, C.; Mehdi, M.; Mesgari, M.; Nielsen, F.A.; Lanamäki, A.: Wikipedia in the eyes of its beholders : a systematic review of scholarly research on Wikipedia readers and readership (2014) 0.02 
    0.017285863 = product of:
  0.06914345 = sum of:
    0.06914345 = sum of:
      0.030734586 = weight(_text_:science in 1540) [ClassicSimilarity], result of:
        0.030734586 = score(doc=1540,freq=4.0), product of:
          0.124457374 = queryWeight, product of:
            2.6341193 = idf(docFreq=8627, maxDocs=44218)
            0.047248192 = queryNorm
          0.24694869 = fieldWeight in 1540, product of:
            2.0 = tf(freq=4.0), with freq of:
              4.0 = termFreq=4.0
            2.6341193 = idf(docFreq=8627, maxDocs=44218)
            0.046875 = fieldNorm(doc=1540)
      0.038408864 = weight(_text_:22 in 1540) [ClassicSimilarity], result of:
        0.038408864 = score(doc=1540,freq=2.0), product of:
          0.16545512 = queryWeight, product of:
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.047248192 = queryNorm
          0.23214069 = fieldWeight in 1540, 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=1540)
  0.25 = coord(1/4)
    Date
    18.11.2014 13:22:03
    Series
    Advances in information science
    Source
    Journal of the Association for Information Science and Technology. 65(2014) no.12, S.2381-2403
  17. Barrio, P.; Gravano, L.: Sampling strategies for information extraction over the deep web (2017) 0.02 
    0.015483556 = product of:
  0.030967113 = sum of:
    0.023722902 = weight(_text_:management in 3412) [ClassicSimilarity], result of:
      0.023722902 = score(doc=3412,freq=2.0), product of:
        0.15925534 = queryWeight, product of:
          3.3706124 = idf(docFreq=4130, maxDocs=44218)
          0.047248192 = queryNorm
        0.14896142 = fieldWeight in 3412, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.3706124 = idf(docFreq=4130, maxDocs=44218)
          0.03125 = fieldNorm(doc=3412)
    0.0072442107 = product of:
      0.014488421 = sum of:
        0.014488421 = weight(_text_:science in 3412) [ClassicSimilarity], result of:
          0.014488421 = score(doc=3412,freq=2.0), product of:
            0.124457374 = queryWeight, product of:
              2.6341193 = idf(docFreq=8627, maxDocs=44218)
              0.047248192 = queryNorm
            0.11641272 = fieldWeight in 3412, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              2.6341193 = idf(docFreq=8627, maxDocs=44218)
              0.03125 = fieldNorm(doc=3412)
      0.5 = coord(1/2)
  0.5 = coord(2/4)
    Content
    Vgl.: http://www.sciencedirect.com/science/article/pii/S0306457316306318 [http://dx.doi.org/10.1016/j.ipm.2016.11.006].
    Source
    Information processing and management. 53(2017) no.2, S.309-331
  18. Villela Dantas, J.R.; Muniz Farias, P.F.: Conceptual navigation in knowledge management environments using NavCon (2010) 0.02 
    0.015408479 = product of:
  0.061633915 = sum of:
    0.061633915 = weight(_text_:management in 4230) [ClassicSimilarity], result of:
      0.061633915 = score(doc=4230,freq=6.0), product of:
        0.15925534 = queryWeight, product of:
          3.3706124 = idf(docFreq=4130, maxDocs=44218)
          0.047248192 = queryNorm
        0.38701317 = fieldWeight in 4230, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          3.3706124 = idf(docFreq=4130, maxDocs=44218)
          0.046875 = fieldNorm(doc=4230)
  0.25 = coord(1/4)
    Abstract
    This article presents conceptual navigation and NavCon, an architecture that implements this navigation in World Wide Web pages. NavCon architecture makes use of ontology as metadata to contextualize user search for information. Based on ontologies, NavCon automatically inserts conceptual links in Web pages. By using these links, the user may navigate in a graph representing ontology concepts and their relationships. By browsing this graph, it is possible to reach documents associated with the user desired ontology concept. This Web navigation supported by ontology concepts we call conceptual navigation. Conceptual navigation is a technique to browse Web sites within a context. The context filters relevant retrieved information. The context also drives user navigation through paths that meet his needs. A company may implement conceptual navigation to improve user search for information in a knowledge management environment. We suggest that the use of an ontology to conduct navigation in an Intranet may help the user to have a better understanding about the knowledge structure of the company.
    Source
    Information processing and management. 46(2010) no.4, S.413-425
  19. Thelwall, M.; Buckley, K.; Paltoglou, G.: Sentiment in Twitter events (2011) 0.02 
    0.015035374 = product of:
  0.060141496 = sum of:
    0.060141496 = sum of:
      0.021732632 = weight(_text_:science in 4345) [ClassicSimilarity], result of:
        0.021732632 = score(doc=4345,freq=2.0), product of:
          0.124457374 = queryWeight, product of:
            2.6341193 = idf(docFreq=8627, maxDocs=44218)
            0.047248192 = queryNorm
          0.17461908 = fieldWeight in 4345, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            2.6341193 = idf(docFreq=8627, maxDocs=44218)
            0.046875 = fieldNorm(doc=4345)
      0.038408864 = weight(_text_:22 in 4345) [ClassicSimilarity], result of:
        0.038408864 = score(doc=4345,freq=2.0), product of:
          0.16545512 = queryWeight, product of:
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.047248192 = queryNorm
          0.23214069 = fieldWeight in 4345, 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=4345)
  0.25 = coord(1/4)
    Date
    22. 1.2011 14:27:06
    Source
    Journal of the American Society for Information Science and Technology. 62(2011) no.2, S.406-418
  20. Egbert, J.; Biber, D.; Davies, M.: Developing a bottom-up, user-based method of web register classification (2015) 0.02 
    0.015035374 = product of:
  0.060141496 = sum of:
    0.060141496 = sum of:
      0.021732632 = weight(_text_:science in 2158) [ClassicSimilarity], result of:
        0.021732632 = score(doc=2158,freq=2.0), product of:
          0.124457374 = queryWeight, product of:
            2.6341193 = idf(docFreq=8627, maxDocs=44218)
            0.047248192 = queryNorm
          0.17461908 = fieldWeight in 2158, product of:
            1.4142135 = tf(freq=2.0), with freq of:
              2.0 = termFreq=2.0
            2.6341193 = idf(docFreq=8627, maxDocs=44218)
            0.046875 = fieldNorm(doc=2158)
      0.038408864 = weight(_text_:22 in 2158) [ClassicSimilarity], result of:
        0.038408864 = score(doc=2158,freq=2.0), product of:
          0.16545512 = queryWeight, product of:
            3.5018296 = idf(docFreq=3622, maxDocs=44218)
            0.047248192 = queryNorm
          0.23214069 = fieldWeight in 2158, 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=2158)
  0.25 = coord(1/4)
    Date
    4. 8.2015 19:22:04
    Source
    Journal of the Association for Information Science and Technology. 66(2015) no.9, S.1817-1831

Authors

Types

  • a 129
  • el 2
  • m 2
  • More… Less…

Themes

Subjects

Classifications