Search (381 results, page 1 of 20)

0.11119729 = product of:
  0.27799323 = sum of:
    0.24901254 = weight(_text_:3a in 862) [ClassicSimilarity], result of:
      0.24901254 = score(doc=862,freq=2.0), product of:
        0.4430686 = queryWeight, product of:
          8.478011 = idf(docFreq=24, maxDocs=44218)
          0.052260913 = queryNorm
        0.56201804 = fieldWeight in 862, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          8.478011 = idf(docFreq=24, maxDocs=44218)
          0.046875 = fieldNorm(doc=862)
    0.028980678 = weight(_text_:it in 862) [ClassicSimilarity], result of:
      0.028980678 = score(doc=862,freq=2.0), product of:
        0.15115225 = queryWeight, product of:
          2.892262 = idf(docFreq=6664, maxDocs=44218)
          0.052260913 = queryNorm
        0.19173169 = fieldWeight in 862, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          2.892262 = idf(docFreq=6664, maxDocs=44218)
          0.046875 = fieldNorm(doc=862)
  0.4 = coord(2/5)

Abstract

This research revisits the classic Turing test and compares recent large language models such as ChatGPT for their abilities to reproduce human-level comprehension and compelling text generation. Two task challenges- summary and question answering- prompt ChatGPT to produce original content (98-99%) from a single text entry and sequential questions initially posed by Turing in 1950. We score the original and generated content against the OpenAI GPT-2 Output Detector from 2019, and establish multiple cases where the generated content proves original and undetectable (98%). The question of a machine fooling a human judge recedes in this work relative to the question of "how would one prove it?" The original contribution of the work presents a metric and simple grammatical set for understanding the writing mechanics of chatbots in evaluating their readability and statistical clarity, engagement, delivery, overall quality, and plagiarism risks. While Turing's original prose scores at least 14% below the machine-generated output, whether an algorithm displays hints of Turing's true initial thoughts (the "Lovelace 2.0" test) remains unanswerable.

Source

https%3A%2F%2Farxiv.org%2Fabs%2F2212.06721&usg=AOvVaw3i_9pZm9y_dQWoHi6uv0EN

0.04538867 = product of:
  0.11347167 = sum of:
    0.07098787 = weight(_text_:it in 915) [ClassicSimilarity], result of:
      0.07098787 = score(doc=915,freq=12.0), product of:
        0.15115225 = queryWeight, product of:
          2.892262 = idf(docFreq=6664, maxDocs=44218)
          0.052260913 = queryNorm
        0.46964484 = fieldWeight in 915, product of:
          3.4641016 = tf(freq=12.0), with freq of:
            12.0 = termFreq=12.0
          2.892262 = idf(docFreq=6664, maxDocs=44218)
          0.046875 = fieldNorm(doc=915)
    0.042483795 = weight(_text_:22 in 915) [ClassicSimilarity], result of:
      0.042483795 = score(doc=915,freq=2.0), product of:
        0.18300882 = queryWeight, product of:
          3.5018296 = idf(docFreq=3622, maxDocs=44218)
          0.052260913 = queryNorm
        0.23214069 = fieldWeight in 915, 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=915)
  0.4 = coord(2/5)

Abstract

Experimentation is the process of trying something out to discover what happens. It is a widespread information practice, yet often bypassed in information-behavior research. This article argues that experimentation complements prior knowledge, documents, and people as an important fourth class of information sources. Relative to the other classes, the distinguishing characteristics of experimentation are that it is a personal-as opposed to interpersonal-source and that it provides "backtalk." When the information seeker tries something out and then attends to the resulting situation, it is as though the materials of the situation talk back: They provide the information seeker with a situated and direct experience of the consequences of the tried-out options. In this way, experimentation involves obtaining information by creating it. It also involves turning material and behavioral processes into information interactions. Thereby, information seeking by experimentation is important to practical information literacy and extends information-behavior research with new insights on the interrelations between creating and seeking information.

Date

21. 3.2023 19:22:29

0.041502092 = product of:
  0.20751046 = sum of:
    0.20751046 = weight(_text_:3a in 5669) [ClassicSimilarity], result of:
      0.20751046 = score(doc=5669,freq=2.0), product of:
        0.4430686 = queryWeight, product of:
          8.478011 = idf(docFreq=24, maxDocs=44218)
          0.052260913 = queryNorm
        0.46834838 = fieldWeight in 5669, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          8.478011 = idf(docFreq=24, maxDocs=44218)
          0.0390625 = fieldNorm(doc=5669)
  0.2 = coord(1/5)

Content

"Die Englischsprachige Wikipedia verfügt jetzt über mehr als 6 Millionen Artikel. An zweiter Stelle kommt die deutschsprachige Wikipedia mit 2.3 Millionen Artikeln, an dritter Stelle steht die französischsprachige Wikipedia mit 2.1 Millionen Artikeln (via Researchbuzz: Firehose <https://rbfirehose.com/2020/01/24/techcrunch-wikipedia-now-has-more-than-6-million-articles-in-english/> und Techcrunch <https://techcrunch.com/2020/01/23/wikipedia-english-six-million-articles/?utm_source=feedburner&utm_medium=feed&utm_campaign=Feed%3A+Techcrunch+%28TechCrunch%29&guccounter=1&guce_referrer=aHR0cHM6Ly9yYmZpcmVob3NlLmNvbS8yMDIwLzAxLzI0L3RlY2hjcnVuY2gtd2lraXBlZGlhLW5vdy1oYXMtbW9yZS10aGFuLTYtbWlsbGlvbi1hcnRpY2xlcy1pbi1lbmdsaXNoLw&guce_referrer_sig=AQAAAK0zHfjdDZ_spFZBF_z-zDjtL5iWvuKDumFTzm4HvQzkUfE2pLXQzGS6FGB_y-VISdMEsUSvkNsg2U_NWQ4lwWSvOo3jvXo1I3GtgHpP8exukVxYAnn5mJspqX50VHIWFADHhs5AerkRn3hMRtf_R3F1qmEbo8EROZXp328HMC-o>). 250120 via digithek ch = #fineBlog s.a.: Angesichts der Veröffentlichung des 6-millionsten Artikels vergangene Woche in der englischsprachigen Wikipedia hat die Community-Zeitungsseite "Wikipedia Signpost" ein Moratorium bei der Veröffentlichung von Unternehmensartikeln gefordert. Das sei kein Vorwurf gegen die Wikimedia Foundation, aber die derzeitigen Maßnahmen, um die Enzyklopädie gegen missbräuchliches undeklariertes Paid Editing zu schützen, funktionierten ganz klar nicht. *"Da die ehrenamtlichen Autoren derzeit von Werbung in Gestalt von Wikipedia-Artikeln überwältigt werden, und da die WMF nicht in der Lage zu sein scheint, dem irgendetwas entgegenzusetzen, wäre der einzige gangbare Weg für die Autoren, fürs erste die Neuanlage von Artikeln über Unternehmen zu untersagen"*, schreibt der Benutzer Smallbones in seinem Editorial <https://en.wikipedia.org/wiki/Wikipedia:Wikipedia_Signpost/2020-01-27/From_the_editor> zur heutigen Ausgabe."

0.041502092 = product of:
  0.20751046 = sum of:
    0.20751046 = weight(_text_:3a in 1000) [ClassicSimilarity], result of:
      0.20751046 = score(doc=1000,freq=2.0), product of:
        0.4430686 = queryWeight, product of:
          8.478011 = idf(docFreq=24, maxDocs=44218)
          0.052260913 = queryNorm
        0.46834838 = fieldWeight in 1000, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          8.478011 = idf(docFreq=24, maxDocs=44218)
          0.0390625 = fieldNorm(doc=1000)
  0.2 = coord(1/5)

Content

Master thesis Master of Science (Library and Information Studies) (MSc), Universität Wien. Advisor: Christoph Steiner. Vgl.: https://www.researchgate.net/publication/371680244_Vergabe_von_DDC-Sachgruppen_mittels_eines_Schlagwort-Thesaurus. DOI: 10.25365/thesis.70030. Vgl. dazu die Präsentation unter: https://www.google.com/url?sa=i&rct=j&q=&esrc=s&source=web&cd=&ved=0CAIQw7AJahcKEwjwoZzzytz_AhUAAAAAHQAAAAAQAg&url=https%3A%2F%2Fwiki.dnb.de%2Fdownload%2Fattachments%2F252121510%2FDA3%2520Workshop-Gabler.pdf%3Fversion%3D1%26modificationDate%3D1671093170000%26api%3Dv2&psig=AOvVaw0szwENK1or3HevgvIDOfjx&ust=1687719410889597&opi=89978449.

0.038114388 = product of:
  0.09528597 = sum of:
    0.038640905 = weight(_text_:it in 486) [ClassicSimilarity], result of:
      0.038640905 = score(doc=486,freq=2.0), product of:
        0.15115225 = queryWeight, product of:
          2.892262 = idf(docFreq=6664, maxDocs=44218)
          0.052260913 = queryNorm
        0.25564227 = fieldWeight in 486, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          2.892262 = idf(docFreq=6664, maxDocs=44218)
          0.0625 = fieldNorm(doc=486)
    0.05664506 = weight(_text_:22 in 486) [ClassicSimilarity], result of:
      0.05664506 = score(doc=486,freq=2.0), product of:
        0.18300882 = queryWeight, product of:
          3.5018296 = idf(docFreq=3622, maxDocs=44218)
          0.052260913 = queryNorm
        0.30952093 = fieldWeight in 486, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.5018296 = idf(docFreq=3622, maxDocs=44218)
          0.0625 = fieldNorm(doc=486)
  0.4 = coord(2/5)

Abstract

Während der Messenger-Dienst Signal von Größen wie Edward Snowden empfohlen wird, steht der Telegram-Messenger immer häufiger in Kritik. Die IT-Sicherheitsexperten der PSW GROUP www.psw-group.de haben beide Messenger-Dienste auf Usability, die AGBs und die Sicherheit geprüft.

Date

22. 1.2022 14:01:14

0.03707192 = product of:
  0.0926798 = sum of:
    0.050196007 = weight(_text_:it in 887) [ClassicSimilarity], result of:
      0.050196007 = score(doc=887,freq=6.0), product of:
        0.15115225 = queryWeight, product of:
          2.892262 = idf(docFreq=6664, maxDocs=44218)
          0.052260913 = queryNorm
        0.33208904 = fieldWeight in 887, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          2.892262 = idf(docFreq=6664, maxDocs=44218)
          0.046875 = fieldNorm(doc=887)
    0.042483795 = weight(_text_:22 in 887) [ClassicSimilarity], result of:
      0.042483795 = score(doc=887,freq=2.0), product of:
        0.18300882 = queryWeight, product of:
          3.5018296 = idf(docFreq=3622, maxDocs=44218)
          0.052260913 = queryNorm
        0.23214069 = fieldWeight in 887, 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=887)
  0.4 = coord(2/5)

Abstract

This study investigates how privacy as an ethical concept exists in two languages: Mandarin Chinese and American English. The exploration relies on two genres of corpora from 10 years: social media posts and news articles, 2010-2019. A mixed-methods approach combining structural topic modeling (STM) and human interpretation were used to work with the data. Findings show various privacy-related topics across the two languages. Moreover, some of these different topics revealed fundamental incompatibilities for understanding privacy across these two languages. In other words, some of the variations of topics do not just reflect contextual differences; they reveal how the two languages value privacy in different ways that can relate back to the society's ethical tradition. This study is one of the first empirically grounded intercultural explorations of the concept of privacy. It has shown that natural language is promising to operationalize intercultural and comparative privacy research, and it provides an examination of the concept as it is understood in these two languages.

Date

22. 1.2023 18:59:40

0.033387464 = product of:
  0.08346866 = sum of:
    0.04098487 = weight(_text_:it in 918) [ClassicSimilarity], result of:
      0.04098487 = score(doc=918,freq=4.0), product of:
        0.15115225 = queryWeight, product of:
          2.892262 = idf(docFreq=6664, maxDocs=44218)
          0.052260913 = queryNorm
        0.27114958 = fieldWeight in 918, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          2.892262 = idf(docFreq=6664, maxDocs=44218)
          0.046875 = fieldNorm(doc=918)
    0.042483795 = weight(_text_:22 in 918) [ClassicSimilarity], result of:
      0.042483795 = score(doc=918,freq=2.0), product of:
        0.18300882 = queryWeight, product of:
          3.5018296 = idf(docFreq=3622, maxDocs=44218)
          0.052260913 = queryNorm
        0.23214069 = fieldWeight in 918, 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=918)
  0.4 = coord(2/5)

Abstract

To what extent is the destiny of a scientific paper shaped by the cocitation network in which it is involved? What are the social contexts that can explain these structuring? Using bibliometric data, interviews with researchers, and social network analysis, this article proposes a typology based on egocentric cocitation networks that displays a quadruple structuring (before and after publication): polarization, clusterization, atomization, and attrition. It shows that the academic capital of the authors and the intellectual resources of their research are key factors of these destinies, as are the social relations between the authors concerned. The circumstances of the publishing are also correlated with the structuring of the egocentric cocitation networks, showing how socially embedded they are. Finally, the article discusses the contribution of these original networks to the analyze of scientific production and its dynamics.

Date

21. 3.2023 19:22:14

0.033350088 = product of:
  0.083375216 = sum of:
    0.03381079 = weight(_text_:it in 40) [ClassicSimilarity], result of:
      0.03381079 = score(doc=40,freq=2.0), product of:
        0.15115225 = queryWeight, product of:
          2.892262 = idf(docFreq=6664, maxDocs=44218)
          0.052260913 = queryNorm
        0.22368698 = fieldWeight in 40, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          2.892262 = idf(docFreq=6664, maxDocs=44218)
          0.0546875 = fieldNorm(doc=40)
    0.04956443 = weight(_text_:22 in 40) [ClassicSimilarity], result of:
      0.04956443 = score(doc=40,freq=2.0), product of:
        0.18300882 = queryWeight, product of:
          3.5018296 = idf(docFreq=3622, maxDocs=44218)
          0.052260913 = queryNorm
        0.2708308 = fieldWeight in 40, 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=40)
  0.4 = coord(2/5)

Abstract

Conclusion There is a reason why Google Scholar and Web of Science/Scopus are kings of the hills in their various arenas. They have strong brand recogniton, a head start in development and a mass of eyeballs and users that leads to an almost virtious cycle of improvement. Competing against such well established competitors is not easy even when one has deep pockets (Microsoft) or a killer idea (scite). It will be interesting to see how the landscape will look like in 2030. Stay tuned for part II where I review each particular index.

Date

17.11.2020 12:22:59

0.03177586 = product of:
  0.07943964 = sum of:
    0.05111711 = weight(_text_:it in 5655) [ClassicSimilarity], result of:
      0.05111711 = score(doc=5655,freq=14.0), product of:
        0.15115225 = queryWeight, product of:
          2.892262 = idf(docFreq=6664, maxDocs=44218)
          0.052260913 = queryNorm
        0.33818293 = fieldWeight in 5655, product of:
          3.7416575 = tf(freq=14.0), with freq of:
            14.0 = termFreq=14.0
          2.892262 = idf(docFreq=6664, maxDocs=44218)
          0.03125 = fieldNorm(doc=5655)
    0.02832253 = weight(_text_:22 in 5655) [ClassicSimilarity], result of:
      0.02832253 = score(doc=5655,freq=2.0), product of:
        0.18300882 = queryWeight, product of:
          3.5018296 = idf(docFreq=3622, maxDocs=44218)
          0.052260913 = queryNorm
        0.15476047 = fieldWeight in 5655, 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=5655)
  0.4 = coord(2/5)

Abstract

Purpose The purpose of this paper is to lay a theoretical foundation for identifying operational information units for library and information professional activities in the context of scholarly communication. Design/methodology/approach The study adopts a deduction-verification approach to formulate a typology of units for scholarly information. It first deduces possible units from an existing conceptualization of information, which defines information as the combined product of data and meaning, and then tests the usefulness of these units via two empirical investigations, one with a group of scholarly papers and the other with a sample of scholarly information users. Findings The results show that, on defining an information unit as a piece of information that is complete in both data and meaning, to such an extent that it remains meaningful to its target audience when retrieved and displayed independently in a database, it is then possible to formulate a hierarchical typology of units for scholarly information. The typology proposed in this study consists of three levels, which in turn, consists of 1, 5 and 44 units, respectively. Research limitations/implications The result of this study has theoretical implications on both the philosophical and conceptual levels: on the philosophical level, it hinges on, and reinforces the objective view of information; on the conceptual level, it challenges the conceptualization of work by IFLA's Functional Requirements for Bibliographic Records and Library Reference Model but endorses that by Library of Congress's BIBFRAME 2.0 model. Practical implications It calls for reconsideration of existing operational units in a variety of library and information activities. Originality/value The study strengthens the conceptual foundation of operational information units and brings to light the primacy of "one work" as an information unit and the possibility for it to be supplemented by smaller units.

Date

14. 1.2020 11:15:22

0.030893266 = product of:
  0.077233166 = sum of:
    0.041830003 = weight(_text_:it in 1096) [ClassicSimilarity], result of:
      0.041830003 = score(doc=1096,freq=6.0), product of:
        0.15115225 = queryWeight, product of:
          2.892262 = idf(docFreq=6664, maxDocs=44218)
          0.052260913 = queryNorm
        0.27674085 = fieldWeight in 1096, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          2.892262 = idf(docFreq=6664, maxDocs=44218)
          0.0390625 = fieldNorm(doc=1096)
    0.035403162 = weight(_text_:22 in 1096) [ClassicSimilarity], result of:
      0.035403162 = score(doc=1096,freq=2.0), product of:
        0.18300882 = queryWeight, product of:
          3.5018296 = idf(docFreq=3622, maxDocs=44218)
          0.052260913 = queryNorm
        0.19345059 = fieldWeight in 1096, 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=1096)
  0.4 = coord(2/5)

Abstract

A table of contents (ToC) is a kind of document representation as well as a paratext and a kind of finding device to the document it represents. TOCs are very common in books and some other kinds of documents, but not in all kinds. This article discusses the definition and functions of ToC, normative guidelines for their design, and the history and forms of ToC in different kinds of documents and media. A main part of the article is about the role of ToC in information searching, in current awareness services and as items added to bibliographical records. The introduction and the conclusion focus on the core theoretical issues concerning ToCs. Should they be document-oriented or request-oriented, neutral, or policy-oriented, objective, or subjective? It is concluded that because of the special functions of ToCs, the arguments for the request-oriented (policy-oriented, subjective) view are weaker than they are in relation to indexing and knowledge organization in general. Apart from level of granularity, the evaluation of a ToC is difficult to separate from the evaluation of the structuring and naming of the elements of the structure of the document it represents.

Date

18.11.2023 13:47:22

0.02858579 = product of:
  0.07146447 = sum of:
    0.028980678 = weight(_text_:it in 5620) [ClassicSimilarity], result of:
      0.028980678 = score(doc=5620,freq=2.0), product of:
        0.15115225 = queryWeight, product of:
          2.892262 = idf(docFreq=6664, maxDocs=44218)
          0.052260913 = queryNorm
        0.19173169 = fieldWeight in 5620, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          2.892262 = idf(docFreq=6664, maxDocs=44218)
          0.046875 = fieldNorm(doc=5620)
    0.042483795 = weight(_text_:22 in 5620) [ClassicSimilarity], result of:
      0.042483795 = score(doc=5620,freq=2.0), product of:
        0.18300882 = queryWeight, product of:
          3.5018296 = idf(docFreq=3622, maxDocs=44218)
          0.052260913 = queryNorm
        0.23214069 = fieldWeight in 5620, 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=5620)
  0.4 = coord(2/5)

Abstract

There is a mutual resemblance between the behavior of users of the Stack Exchange and the dynamics of the citations accumulation process in the scientific community, which enabled us to tackle the outwardly intractable problem of assessing the impact of introducing "negative" citations. Although the most frequent reason to cite an article is to highlight the connection between the 2 publications, researchers sometimes mention an earlier work to cast a negative light. While computing citation-based scores, for instance, the h-index, information about the reason why an article was mentioned is neglected. Therefore, it can be questioned whether these indices describe scientific achievements accurately. In this article we shed insight into the problem of "negative" citations, analyzing data from Stack Exchange and, to draw more universal conclusions, we derive an approximation of citations scores. Here we show that the quantified influence of introducing negative citations is of lesser importance and that they could be used as an indicator of where the attention of the scientific community is allocated.

Date

6. 1.2020 18:10:22

0.02858579 = product of:
  0.07146447 = sum of:
    0.028980678 = weight(_text_:it in 919) [ClassicSimilarity], result of:
      0.028980678 = score(doc=919,freq=2.0), product of:
        0.15115225 = queryWeight, product of:
          2.892262 = idf(docFreq=6664, maxDocs=44218)
          0.052260913 = queryNorm
        0.19173169 = fieldWeight in 919, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          2.892262 = idf(docFreq=6664, maxDocs=44218)
          0.046875 = fieldNorm(doc=919)
    0.042483795 = weight(_text_:22 in 919) [ClassicSimilarity], result of:
      0.042483795 = score(doc=919,freq=2.0), product of:
        0.18300882 = queryWeight, product of:
          3.5018296 = idf(docFreq=3622, maxDocs=44218)
          0.052260913 = queryNorm
        0.23214069 = fieldWeight in 919, 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=919)
  0.4 = coord(2/5)

Abstract

Despite the prominence of the concept of the information ecosystem (hereafter IE) in information literacy documents and literature, it is under-theorized. This article proposes a general definition of IE for information literacy. After reviewing the current use of the IE concept in the Association of College and Research Libraries (ACRL) Framework for Information Literacy and other information literacy sources, existing definitions of IE and similar concepts (e.g., "evidence ecosystems") will be examined from other fields. These will form the basis of the definition of IE proposed in the article for the field of information literacy: "all structures, entities, and agents related to the flow of semantic information relevant to a research domain, as well as the information itself."

Date

22. 3.2023 11:52:50

0.027822888 = product of:
  0.06955722 = sum of:
    0.034154054 = weight(_text_:it in 5843) [ClassicSimilarity], result of:
      0.034154054 = score(doc=5843,freq=4.0), product of:
        0.15115225 = queryWeight, product of:
          2.892262 = idf(docFreq=6664, maxDocs=44218)
          0.052260913 = queryNorm
        0.22595796 = fieldWeight in 5843, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          2.892262 = idf(docFreq=6664, maxDocs=44218)
          0.0390625 = fieldNorm(doc=5843)
    0.035403162 = weight(_text_:22 in 5843) [ClassicSimilarity], result of:
      0.035403162 = score(doc=5843,freq=2.0), product of:
        0.18300882 = queryWeight, product of:
          3.5018296 = idf(docFreq=3622, maxDocs=44218)
          0.052260913 = queryNorm
        0.19345059 = fieldWeight in 5843, 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=5843)
  0.4 = coord(2/5)

Abstract

Purpose Personal information management (PIM) is an activity in which people store information items in order to retrieve them later. The purpose of this paper is to test and quantify the effect of factors related to collection size, file properties and workload on file retrieval success and efficiency. Design/methodology/approach In the study, 289 participants retrieved 1,557 of their shared files in a naturalistic setting. The study used specially developed software designed to collect shared files' names and present them as targets for the retrieval task. The dependent variables were retrieval success, retrieval time and misstep/s. Findings Various factors compromise shared files retrieval including: collection size (large number of files), file properties (multiple versions, size of team sharing the file, time since most recent retrieval and folder depth) and workload (daily e-mails sent and received). The authors discuss theoretical reasons for these negative effects and suggest possible ways to overcome them. Originality/value Retrieval is the main reason people manage personal information. It is essential for retrieval to be successful and efficient, as information cannot be used unless it can be re-accessed. Prior PIM research has assumed that factors related to collection size, file properties and workload affect file retrieval. However, this is the first study to systematically quantify the negative effects of these factors. As each of these factors is expected to be exacerbated in the future, this study is a necessary first step toward addressing these problems.

Date

20. 1.2015 18:30:22

0.027822888 = product of:
  0.06955722 = sum of:
    0.034154054 = weight(_text_:it in 5985) [ClassicSimilarity], result of:
      0.034154054 = score(doc=5985,freq=4.0), product of:
        0.15115225 = queryWeight, product of:
          2.892262 = idf(docFreq=6664, maxDocs=44218)
          0.052260913 = queryNorm
        0.22595796 = fieldWeight in 5985, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          2.892262 = idf(docFreq=6664, maxDocs=44218)
          0.0390625 = fieldNorm(doc=5985)
    0.035403162 = weight(_text_:22 in 5985) [ClassicSimilarity], result of:
      0.035403162 = score(doc=5985,freq=2.0), product of:
        0.18300882 = queryWeight, product of:
          3.5018296 = idf(docFreq=3622, maxDocs=44218)
          0.052260913 = queryNorm
        0.19345059 = fieldWeight in 5985, 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=5985)
  0.4 = coord(2/5)

Abstract

Purpose Continuous knowledge sharing by active users, who are highly active in answering questions, is crucial to the sustenance of social question-and-answer (Q&A) sites. The purpose of this paper is to examine such knowledge sharing considering reason-based elaborate decision and habit-based automated cognitive processes. Design/methodology/approach To verify the research hypotheses, survey data on subjective intentions and web-crawled data on objective behavior are utilized. The sample size is 337 with the response rate of 27.2 percent. Negative binomial and hierarchical linear regressions are used given the skewed distribution of the dependent variable (i.e. the number of answers). Findings Both elaborate decision (linking satisfaction, intentions and continuance behavior) and automated cognitive processes (linking past and continuance behavior) are significant and substitutable. Research limitations/implications By measuring both subjective intentions and objective behavior, it verifies a detailed mechanism linking continuance intentions, past behavior and continuous knowledge sharing. The significant influence of automated cognitive processes implies that online knowledge sharing is habitual for active users. Practical implications Understanding that online knowledge sharing is habitual is imperative to maintaining continuous knowledge sharing by active users. Knowledge sharing trends should be monitored to check if the frequency of sharing decreases. Social Q&A sites should intervene to restore knowledge sharing behavior through personalized incentives. Originality/value This is the first study utilizing both subjective intentions and objective behavior data in the context of online knowledge sharing. It also introduces habit-based automated cognitive processes to this context. This approach extends the current understanding of continuous online knowledge sharing behavior.

Date

20. 1.2015 18:30:22

0.027822888 = product of:
  0.06955722 = sum of:
    0.034154054 = weight(_text_:it in 678) [ClassicSimilarity], result of:
      0.034154054 = score(doc=678,freq=4.0), product of:
        0.15115225 = queryWeight, product of:
          2.892262 = idf(docFreq=6664, maxDocs=44218)
          0.052260913 = queryNorm
        0.22595796 = fieldWeight in 678, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          2.892262 = idf(docFreq=6664, maxDocs=44218)
          0.0390625 = fieldNorm(doc=678)
    0.035403162 = weight(_text_:22 in 678) [ClassicSimilarity], result of:
      0.035403162 = score(doc=678,freq=2.0), product of:
        0.18300882 = queryWeight, product of:
          3.5018296 = idf(docFreq=3622, maxDocs=44218)
          0.052260913 = queryNorm
        0.19345059 = fieldWeight in 678, 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=678)
  0.4 = coord(2/5)

Abstract

Purpose This article examines the relation between place, space and information behaviour. Design/methodology/approach Concepts of place and space are explored through a comparison of three leisure pursuits: running, urban exploration and genealogy, based on the authors' research and the published literature. Findings A socially constructed meaning of place is central to each leisure activity but how it is experienced physically, emotionally and imaginatively are different. Places have very different meanings within each practice. Mirroring this, information behaviours are also very different: such as the sources used, the type of information created and how it is shared or not shared. Information behaviour contributes to the meanings associated with place in particular social practices. Research limitations/implications Meaning attached to place can be understood as actively constructed within social practices. Rather than context for information behaviours in the sense of an outside, containing, even constraining, environment, the meaning of place can be seen as actively constructed within social practices and by the information behaviours that are part of them. Originality/value The paper adds a new perspective to the understanding of place and space in the study of information behaviour.

Date

5. 6.2022 17:20:22

0.024714613 = product of:
  0.061786532 = sum of:
    0.033464003 = weight(_text_:it in 566) [ClassicSimilarity], result of:
      0.033464003 = score(doc=566,freq=6.0), product of:
        0.15115225 = queryWeight, product of:
          2.892262 = idf(docFreq=6664, maxDocs=44218)
          0.052260913 = queryNorm
        0.22139269 = fieldWeight in 566, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          2.892262 = idf(docFreq=6664, maxDocs=44218)
          0.03125 = fieldNorm(doc=566)
    0.02832253 = weight(_text_:22 in 566) [ClassicSimilarity], result of:
      0.02832253 = score(doc=566,freq=2.0), product of:
        0.18300882 = queryWeight, product of:
          3.5018296 = idf(docFreq=3622, maxDocs=44218)
          0.052260913 = queryNorm
        0.15476047 = fieldWeight in 566, 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=566)
  0.4 = coord(2/5)

Abstract

Knowledge Architectures reviews traditional approaches to managing information and explains why they need to adapt to support 21st-century information management and discovery. Exploring the rapidly changing environment in which information is being managed and accessed, the book considers how to use knowledge architectures, the basic structures and designs that underlie all of the parts of an effective information system, to best advantage. Drawing on 40 years of work with a variety of organizations, Bedford explains that failure to understand the structure behind any given system can be the difference between an effective solution and a significant and costly failure. Demonstrating that the information user environment has shifted significantly in the past 20 years, the book explains that end users now expect designs and behaviors that are much closer to the way they think, work, and act. Acknowledging how important it is that those responsible for developing an information or knowledge management system understand knowledge structures, the book goes beyond a traditional library science perspective and uses case studies to help translate the abstract and theoretical to the practical and concrete. Explaining the structures in a simple and intuitive way and providing examples that clearly illustrate the challenges faced by a range of different organizations, Knowledge Architectures is essential reading for those studying and working in library and information science, data science, systems development, database design, and search system architecture and engineering.

Content

Section 1 Context and purpose of knowledge architecture -- 1 Making the case for knowledge architecture -- 2 The landscape of knowledge assets -- 3 Knowledge architecture and design -- 4 Knowledge architecture reference model -- 5 Knowledge architecture segments -- Section 2 Designing for availability -- 6 Knowledge object modeling -- 7 Knowledge structures for encoding, formatting, and packaging -- 8 Functional architecture for identification and distinction -- 9 Functional architectures for knowledge asset disposition and destruction -- 10 Functional architecture designs for knowledge preservation and conservation -- Section 3 Designing for accessibility -- 11 Functional architectures for knowledge seeking and discovery -- 12 Functional architecture for knowledge search -- 13 Functional architecture for knowledge categorization -- 14 Functional architectures for indexing and keywording -- 15 Functional architecture for knowledge semantics -- 16 Functional architecture for knowledge abstraction and surrogation -- Section 4 Functional architectures to support knowledge consumption -- 17 Functional architecture for knowledge augmentation, derivation, and synthesis -- 18 Functional architecture to manage risk and harm -- 19 Functional architectures for knowledge authentication and provenance -- 20 Functional architectures for securing knowledge assets -- 21 Functional architectures for authorization and asset management -- Section 5 Pulling it all together - the big picture knowledge architecture -- 22 Functional architecture for knowledge metadata and metainformation -- 23 The whole knowledge architecture - pulling it all together

0.023821492 = product of:
  0.059553728 = sum of:
    0.024150565 = weight(_text_:it in 107) [ClassicSimilarity], result of:
      0.024150565 = score(doc=107,freq=2.0), product of:
        0.15115225 = queryWeight, product of:
          2.892262 = idf(docFreq=6664, maxDocs=44218)
          0.052260913 = queryNorm
        0.15977642 = fieldWeight in 107, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          2.892262 = idf(docFreq=6664, maxDocs=44218)
          0.0390625 = fieldNorm(doc=107)
    0.035403162 = weight(_text_:22 in 107) [ClassicSimilarity], result of:
      0.035403162 = score(doc=107,freq=2.0), product of:
        0.18300882 = queryWeight, product of:
          3.5018296 = idf(docFreq=3622, maxDocs=44218)
          0.052260913 = queryNorm
        0.19345059 = fieldWeight in 107, 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=107)
  0.4 = coord(2/5)

Abstract

Purpose Trends in information technology and contemplative practices compel us to consider the intersections of information and contemplation. The purpose of this paper is to consider these intersections at the level of institutions. Design/methodology/approach First, the notion of institution is defined and discussed, along with information institutions and contemplative institutions. Next, sanctuary is proposed and explored as a vision for institutions in the digital age. Findings Sanctuary is a primordial human institution that has especial urgency in the digital age. This paper develops an info-contemplative framework for sanctuaries, including the elements: stability, silence, refuge, privacy and reform. Research limitations/implications This is a conceptual paper that, though guided by prior empirical and theoretical work, would benefit from application, validation and critique. This paper is meant as a starting point for discussions of institutions for the digital age. Practical implications As much as this paper is meant to prompt further research, it also provides guidance and inspiration for professionals to infuse their work with aspects of sanctuary and be attentive to the tensions inherent in sanctuary. Originality/value This paper builds on discourse at the intersection of information studies and contemplative studies, also connecting this with recent work on information institutions.

Date

22. 1.2021 14:20:55

0.023821492 = product of:
  0.059553728 = sum of:
    0.024150565 = weight(_text_:it in 173) [ClassicSimilarity], result of:
      0.024150565 = score(doc=173,freq=2.0), product of:
        0.15115225 = queryWeight, product of:
          2.892262 = idf(docFreq=6664, maxDocs=44218)
          0.052260913 = queryNorm
        0.15977642 = fieldWeight in 173, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          2.892262 = idf(docFreq=6664, maxDocs=44218)
          0.0390625 = fieldNorm(doc=173)
    0.035403162 = weight(_text_:22 in 173) [ClassicSimilarity], result of:
      0.035403162 = score(doc=173,freq=2.0), product of:
        0.18300882 = queryWeight, product of:
          3.5018296 = idf(docFreq=3622, maxDocs=44218)
          0.052260913 = queryNorm
        0.19345059 = fieldWeight in 173, 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=173)
  0.4 = coord(2/5)

Abstract

Purpose The purpose of this paper is to propose a theoretical framework to illustrate the archival knowledge applied by archivists in their personal archiving (PA) and the mechanism of the application of archival knowledge in their PA. Design/methodology/approach The grounded theory methodology was adopted. For data collection, in-depth interviews were conducted with 21 archivists in China. Data analysis was performed using the open coding, axial coding and selective coding to organise the archival knowledge composition of PA and develops the awareness-knowledge-action (AKA) integration model of archival knowledge application in the field of PA, according to the principles of the grounded theory. Findings The archival knowledge involved in the field of PA comprises four principal categories: documentation, arrangement, preservation and appraisal. Three interactive factors involved in archivists' archival knowledge application in the field of PA behaviour: awareness, knowledge and action, which form a pattern of awareness leading, knowledge guidance and action innovation, and archivists' PA practice is flexible and innovative. The paper underscored that it is need to improve archival literacy among general public. Originality/value The study constructs a theoretical framework to identify the specialised archival knowledge and skills of PA which is able to provide solutions for non-specialist PA and develops an AKA model to explain the interaction relationships between awareness, knowledge and action in the field of PA.

Date

22. 1.2021 14:20:27

0.023821492 = product of:
  0.059553728 = sum of:
    0.024150565 = weight(_text_:it in 178) [ClassicSimilarity], result of:
      0.024150565 = score(doc=178,freq=2.0), product of:
        0.15115225 = queryWeight, product of:
          2.892262 = idf(docFreq=6664, maxDocs=44218)
          0.052260913 = queryNorm
        0.15977642 = fieldWeight in 178, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          2.892262 = idf(docFreq=6664, maxDocs=44218)
          0.0390625 = fieldNorm(doc=178)
    0.035403162 = weight(_text_:22 in 178) [ClassicSimilarity], result of:
      0.035403162 = score(doc=178,freq=2.0), product of:
        0.18300882 = queryWeight, product of:
          3.5018296 = idf(docFreq=3622, maxDocs=44218)
          0.052260913 = queryNorm
        0.19345059 = fieldWeight in 178, 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=178)
  0.4 = coord(2/5)

Abstract

Purpose Public attitudes towards COVID-19 and social distancing are critical in reducing its spread. It is therefore important to understand public reactions and information dissemination in all major forms, including on social media. This article investigates important issues reflected on Twitter in the early stages of the public reaction to COVID-19. Design/methodology/approach A thematic analysis of the most retweeted English-language tweets mentioning COVID-19 during March 10-29, 2020. Findings The main themes identified for the 87 qualifying tweets accounting for 14 million retweets were: lockdown life; attitude towards social restrictions; politics; safety messages; people with COVID-19; support for key workers; work; and COVID-19 facts/news. Research limitations/implications Twitter played many positive roles, mainly through unofficial tweets. Users shared social distancing information, helped build support for social distancing, criticised government responses, expressed support for key workers and helped each other cope with social isolation. A few popular tweets not supporting social distancing show that government messages sometimes failed. Practical implications Public health campaigns in future may consider encouraging grass roots social web activity to support campaign goals. At a methodological level, analysing retweet counts emphasised politics and ignored practical implementation issues. Originality/value This is the first qualitative analysis of general COVID-19-related retweeting.

Date

20. 1.2015 18:30:22

0.023821492 = product of:
  0.059553728 = sum of:
    0.024150565 = weight(_text_:it in 180) [ClassicSimilarity], result of:
      0.024150565 = score(doc=180,freq=2.0), product of:
        0.15115225 = queryWeight, product of:
          2.892262 = idf(docFreq=6664, maxDocs=44218)
          0.052260913 = queryNorm
        0.15977642 = fieldWeight in 180, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          2.892262 = idf(docFreq=6664, maxDocs=44218)
          0.0390625 = fieldNorm(doc=180)
    0.035403162 = weight(_text_:22 in 180) [ClassicSimilarity], result of:
      0.035403162 = score(doc=180,freq=2.0), product of:
        0.18300882 = queryWeight, product of:
          3.5018296 = idf(docFreq=3622, maxDocs=44218)
          0.052260913 = queryNorm
        0.19345059 = fieldWeight in 180, 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=180)
  0.4 = coord(2/5)

Abstract

Purpose This investigation aims to examine the differences and similarities between activity tracking technology users from two regions (the USA and Germany) in their intended privacy-related behavior. The focus lies on data handling after hypothetical discontinuance of use, data protection and privacy policy seeking, and privacy concerns. Design/methodology/approach The data was collected through an online survey in 2019. In order to identify significant differences between participants from Germany and the USA, the chi-squared test and the Mann-Whitney U test were applied. Findings The intensity of several privacy-related concerns was significantly different between the two groups. The majority of the participants did not inform themselves about the respective data privacy policies or terms and conditions before installing an activity tracking application. The majority of the German participants knew that they could request the deletion of all their collected data. In contrast, only 35% out of 68 participants from the US knew about this option. Research limitations/implications This study intends to raise awareness about managing the collected health and fitness data after stopping to use activity tracking technologies. Furthermore, to reduce privacy and security concerns, the involvement of the government, companies and users is necessary to handle and share data more considerably and in a sustainable way. Originality/value This study sheds light on users of activity tracking technologies from a broad perspective (here, participants from the USA and Germany). It incorporates not only concerns and the privacy paradox but (intended) user behavior, including seeking information on data protection and privacy policy and handling data after hypothetical discontinuance of use of the technology.

Date

20. 1.2015 18:30:22