Search (9 results, page 1 of 1)

  • × author_ss:"Wolfram, D."
  1. Ajiferuke, I.; Lu, K.; Wolfram, D.: ¬A comparison of citer and citation-based measure outcomes for multiple disciplines (2010) 0.05
    0.045783717 = product of:
      0.091567434 = sum of:
        0.091567434 = sum of:
          0.054574184 = weight(_text_:subject in 4000) [ClassicSimilarity], result of:
            0.054574184 = score(doc=4000,freq=4.0), product of:
              0.16275941 = queryWeight, product of:
                3.576596 = idf(docFreq=3361, maxDocs=44218)
                0.04550679 = queryNorm
              0.33530587 = fieldWeight in 4000, product of:
                2.0 = tf(freq=4.0), with freq of:
                  4.0 = termFreq=4.0
                3.576596 = idf(docFreq=3361, maxDocs=44218)
                0.046875 = fieldNorm(doc=4000)
          0.03699325 = weight(_text_:22 in 4000) [ClassicSimilarity], result of:
            0.03699325 = score(doc=4000,freq=2.0), product of:
              0.15935703 = queryWeight, product of:
                3.5018296 = idf(docFreq=3622, maxDocs=44218)
                0.04550679 = queryNorm
              0.23214069 = fieldWeight in 4000, 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=4000)
      0.5 = coord(1/2)
    
    Abstract
    Author research impact was examined based on citer analysis (the number of citers as opposed to the number of citations) for 90 highly cited authors grouped into three broad subject areas. Citer-based outcome measures were also compared with more traditional citation-based measures for levels of association. The authors found that there are significant differences in citer-based outcomes among the three broad subject areas examined and that there is a high degree of correlation between citer and citation-based measures for all measures compared, except for two outcomes calculated for the social sciences. Citer-based measures do produce slightly different rankings of authors based on citer counts when compared to more traditional citation counts. Examples are provided. Citation measures may not adequately address the influence, or reach, of an author because citations usually do not address the origin of the citation beyond self-citations.
    Date
    28. 9.2010 12:54:22
  2. Ross, N.C.M.; Wolfram, D.: End user searching on the Internet : an analysis of term pair topics submitted to the Excite search engine (2000) 0.02
    0.023631316 = product of:
      0.04726263 = sum of:
        0.04726263 = product of:
          0.09452526 = sum of:
            0.09452526 = weight(_text_:subject in 4998) [ClassicSimilarity], result of:
              0.09452526 = score(doc=4998,freq=12.0), product of:
                0.16275941 = queryWeight, product of:
                  3.576596 = idf(docFreq=3361, maxDocs=44218)
                  0.04550679 = queryNorm
                0.5807668 = fieldWeight in 4998, product of:
                  3.4641016 = tf(freq=12.0), with freq of:
                    12.0 = termFreq=12.0
                  3.576596 = idf(docFreq=3361, maxDocs=44218)
                  0.046875 = fieldNorm(doc=4998)
          0.5 = coord(1/2)
      0.5 = coord(1/2)
    
    Abstract
    Queries submitted to the Excite search engine were analyzed for subject content based on the cooccurrence of terms within multiterm queries. More than 1000 of the most frequently cooccurring term pairs were categorized into one or more of 30 developed subject areas. Subject area frequencies and their cooccurrences with one another were tallied and analyzed using hierarchical cluster analysis and multidimensional scaling. The cluster analyses revealed several anticipated and a few unanticipated groupings of subjects, resulting in several well-defined high-level clusters of broad subject areas. Multidimensional scaling of subject cooccurrences revealed similar relationships among the different subject categories. Applications that arise from a better understanding of the topics users search and their relationships are discussed
  3. Wolfram, D.; Olson, H.A.; Bloom, R.: Measuring consistency for multiple taggers using vector space modeling (2009) 0.02
    0.016709864 = product of:
      0.03341973 = sum of:
        0.03341973 = product of:
          0.06683946 = sum of:
            0.06683946 = weight(_text_:subject in 3113) [ClassicSimilarity], result of:
              0.06683946 = score(doc=3113,freq=6.0), product of:
                0.16275941 = queryWeight, product of:
                  3.576596 = idf(docFreq=3361, maxDocs=44218)
                  0.04550679 = queryNorm
                0.41066417 = fieldWeight in 3113, product of:
                  2.4494898 = tf(freq=6.0), with freq of:
                    6.0 = termFreq=6.0
                  3.576596 = idf(docFreq=3361, maxDocs=44218)
                  0.046875 = fieldNorm(doc=3113)
          0.5 = coord(1/2)
      0.5 = coord(1/2)
    
    Abstract
    A longstanding area of study in indexing is the identification of factors affecting vocabulary usage and consistency. This topic has seen a recent resurgence with a focus on social tagging. Tagging data for scholarly articles made available by the social bookmarking Website CiteULike (www.citeulike.org) were used to test the use of inter-indexer/tagger consistency density values, based on a method developed by the authors by comparing calculations for highly tagged documents representing three subject areas (Science, Social Science, Social Software). The analysis revealed that the developed method is viable for a large dataset. The findings also indicated that there were no significant differences in tagging consistency among the three topic areas, demonstrating that vocabulary usage in a relatively new subject area like social software is no more inconsistent than the more established subject areas investigated. The implications of the method used and the findings are discussed.
  4. Dimitroff, A.; Wolfram, D.: Searcher response in a hypertext-based bibliographic information retrieval system (1995) 0.01
    0.012331083 = product of:
      0.024662167 = sum of:
        0.024662167 = product of:
          0.049324334 = sum of:
            0.049324334 = weight(_text_:22 in 187) [ClassicSimilarity], result of:
              0.049324334 = score(doc=187,freq=2.0), product of:
                0.15935703 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.04550679 = queryNorm
                0.30952093 = fieldWeight in 187, 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=187)
          0.5 = coord(1/2)
      0.5 = coord(1/2)
    
    Source
    Journal of the American Society for Information Science. 46(1995) no.1, S.22-29
  5. Xie, H.I.; Wolfram, D.: State digital library usability contributing organizational factors (2002) 0.01
    0.011369622 = product of:
      0.022739245 = sum of:
        0.022739245 = product of:
          0.04547849 = sum of:
            0.04547849 = weight(_text_:subject in 5221) [ClassicSimilarity], result of:
              0.04547849 = score(doc=5221,freq=4.0), product of:
                0.16275941 = queryWeight, product of:
                  3.576596 = idf(docFreq=3361, maxDocs=44218)
                  0.04550679 = queryNorm
                0.27942157 = fieldWeight in 5221, product of:
                  2.0 = tf(freq=4.0), with freq of:
                    4.0 = termFreq=4.0
                  3.576596 = idf(docFreq=3361, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=5221)
          0.5 = coord(1/2)
      0.5 = coord(1/2)
    
    Abstract
    In this issue Xie and Wolfram study the Wisconsin state digital library BadgerLink to determine the organizational factors that lead to different use requirements and the degree to which these are met, as well as impact on physical libraries. To this end, usage data from EBSCOhost and ProQuest logs for BadgerLink were analyzed, 313 Wisconsin libraries of all types were surveyed (76% response rate), and analyzed along with 81 responses to a voluntary web survey of end users. Heaviest users were K-12 schools and institutions of higher education. Heaviest use sites were the two largest state universities and the state's largest public library. Small libraries were infrequent users. Web survey respondents were mature working professionals. Sixty percent searched for specific information, but 46% reported browsing in subject areas. Libraries with dedicated Internet access reported more frequent usage than those with dial-up connection. Those who accessed from libraries reported more frequent use than those at work or at home. Libraries that trained end users reported more use, but the majority of the web survey respondents reported themselves as self-taught. Logs confirm reported subject interests. Three surrogates were requested for every full text document but full text availability is reported as the reason for use by 30% of users. Availability has led to the cancellation of subscriptions in many libraries that are important promoters of the service. A model will need to include interactions based upon the influence of each involved participant on the others. It will also need to include the extension of the activities of one participant to other participant organizations and the communication among these organizations.
  6. Zhang, J.; Wolfram, D.; Wang, P.; Hong, Y.; Gillis, R.: Visualization of health-subject analysis based on query term co-occurrences (2008) 0.01
    0.011369622 = product of:
      0.022739245 = sum of:
        0.022739245 = product of:
          0.04547849 = sum of:
            0.04547849 = weight(_text_:subject in 2376) [ClassicSimilarity], result of:
              0.04547849 = score(doc=2376,freq=4.0), product of:
                0.16275941 = queryWeight, product of:
                  3.576596 = idf(docFreq=3361, maxDocs=44218)
                  0.04550679 = queryNorm
                0.27942157 = fieldWeight in 2376, product of:
                  2.0 = tf(freq=4.0), with freq of:
                    4.0 = termFreq=4.0
                  3.576596 = idf(docFreq=3361, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=2376)
          0.5 = coord(1/2)
      0.5 = coord(1/2)
    
    Abstract
    A multidimensional-scaling approach is used to analyze frequently used medical-topic terms in queries submitted to a Web-based consumer health information system. Based on a year-long transaction log file, five medical focus keywords (stomach, hip, stroke, depression, and cholesterol) and their co-occurring query terms are analyzed. An overlap-coefficient similarity measure and a conversion measure are used to calculate the proximity of terms to one another based on their co-occurrences in queries. The impact of the dimensionality of the visual configuration, the cutoff point of term co-occurrence for inclusion in the analysis, and the Minkowski metric power k on the stress value are discussed. A visual clustering of groups of terms based on the proximity within each focus-keyword group is also conducted. Term distributions within each visual configuration are characterized and are compared with formal medical vocabulary. This investigation reveals that there are significant differences between consumer health query-term usage and more formal medical terminology used by medical professionals when describing the same medical subject. Future directions are discussed.
  7. Zhang, J.; Chen, Y.; Zhao, Y.; Wolfram, D.; Ma, F.: Public health and social media : a study of Zika virus-related posts on Yahoo! Answers (2020) 0.01
    0.011369622 = product of:
      0.022739245 = sum of:
        0.022739245 = product of:
          0.04547849 = sum of:
            0.04547849 = weight(_text_:subject in 5672) [ClassicSimilarity], result of:
              0.04547849 = score(doc=5672,freq=4.0), product of:
                0.16275941 = queryWeight, product of:
                  3.576596 = idf(docFreq=3361, maxDocs=44218)
                  0.04550679 = queryNorm
                0.27942157 = fieldWeight in 5672, product of:
                  2.0 = tf(freq=4.0), with freq of:
                    4.0 = termFreq=4.0
                  3.576596 = idf(docFreq=3361, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=5672)
          0.5 = coord(1/2)
      0.5 = coord(1/2)
    
    Abstract
    This study investigates the content of questions and responses about the Zika virus on Yahoo! Answers as a recent example of how public concerns regarding an international health issue are reflected in social media. We investigate the contents of posts about the Zika virus on Yahoo! Answers, identify and reveal subject patterns about the Zika virus, and analyze the temporal changes of the revealed subject topics over 4 defined periods of the Zika virus outbreak. Multidimensional scaling analysis, temporal analysis, and inferential statistical analysis approaches were used in the study. A resulting 2-layer Zika virus schema, and term connections and relationships are presented. The results indicate that consumers' concerns changed over the 4 defined periods. Consumers paid more attention to the basic information about the Zika virus, and the prevention and protection from the Zika virus at the beginning of the outbreak of the Zika virus. During the later periods, consumers became more interested in the role that the government and health organizations played in the public health emergency.
  8. Zhang, J.; Wolfram, D.; Wang, P.: Analysis of query keywords of sports-related queries using visualization and clustering (2009) 0.01
    0.008039537 = product of:
      0.016079074 = sum of:
        0.016079074 = product of:
          0.032158148 = sum of:
            0.032158148 = weight(_text_:subject in 2947) [ClassicSimilarity], result of:
              0.032158148 = score(doc=2947,freq=2.0), product of:
                0.16275941 = queryWeight, product of:
                  3.576596 = idf(docFreq=3361, maxDocs=44218)
                  0.04550679 = queryNorm
                0.19758089 = fieldWeight in 2947, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.576596 = idf(docFreq=3361, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=2947)
          0.5 = coord(1/2)
      0.5 = coord(1/2)
    
    Abstract
    The authors investigated 11 sports-related query keywords extracted from a public search engine query log to better understand sports-related information seeking on the Internet. After the query log contents were cleaned and query data were parsed, popular sports-related keywords were identified, along with frequently co-occurring query terms associated with the identified keywords. Relationships among each sports-related focus keyword and its related keywords were characterized and grouped using multidimensional scaling (MDS) in combination with traditional hierarchical clustering methods. The two approaches were synthesized in a visual context by highlighting the results of the hierarchical clustering analysis in the visual MDS configuration. Important events, people, subjects, merchandise, and so on related to a sport were illustrated, and relationships among the sports were analyzed. A small-scale comparative study of sports searches with and without term assistance was conducted. Searches that used search term assistance by relying on previous query term relationships outperformed the searches without the search term assistance. The findings of this study provide insights into sports information seeking behavior on the Internet. The developed method also may be applied to other query log subject areas.
  9. Castanha, R.C.G.; Wolfram, D.: ¬The domain of knowledge organization : a bibliometric analysis of prolific authors and their intellectual space (2018) 0.01
    0.0077069276 = product of:
      0.015413855 = sum of:
        0.015413855 = product of:
          0.03082771 = sum of:
            0.03082771 = weight(_text_:22 in 4150) [ClassicSimilarity], result of:
              0.03082771 = score(doc=4150,freq=2.0), product of:
                0.15935703 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.04550679 = queryNorm
                0.19345059 = fieldWeight in 4150, 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=4150)
          0.5 = coord(1/2)
      0.5 = coord(1/2)
    
    Source
    Knowledge organization. 45(2018) no.1, S.13-22