Search (10 results, page 1 of 1)

0.036979202 = product of:
  0.073958404 = sum of:
    0.073958404 = product of:
      0.14791681 = sum of:
        0.14791681 = weight(_text_:journals in 4349) [ClassicSimilarity], result of:
          0.14791681 = score(doc=4349,freq=6.0), product of:
            0.25656942 = queryWeight, product of:
              5.021064 = idf(docFreq=792, maxDocs=44218)
              0.05109862 = queryNorm
            0.5765177 = fieldWeight in 4349, product of:
              2.4494898 = tf(freq=6.0), with freq of:
                6.0 = termFreq=6.0
              5.021064 = idf(docFreq=792, maxDocs=44218)
              0.046875 = fieldNorm(doc=4349)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

Ranking scientific productivity and prestige are often limited to homogeneous networks. These networks are unable to account for the multiple factors that constitute the scholarly communication and reward system. This study proposes a new informetric indicator, P-Rank, for measuring prestige in heterogeneous scholarly networks containing articles, authors, and journals. P-Rank differentiates the weight of each citation based on its citing papers, citing journals, and citing authors. Articles from 16 representative library and information science journals are selected as the dataset. Principle Component Analysis is conducted to examine the relationship between P-Rank and other bibliometric indicators. We also compare the correlation and rank variances between citation counts and P-Rank scores. This work provides a new approach to examining prestige in scholarly communication networks in a more comprehensive and nuanced way.

0.030193392 = product of:
  0.060386784 = sum of:
    0.060386784 = product of:
      0.12077357 = sum of:
        0.12077357 = weight(_text_:journals in 686) [ClassicSimilarity], result of:
          0.12077357 = score(doc=686,freq=4.0), product of:
            0.25656942 = queryWeight, product of:
              5.021064 = idf(docFreq=792, maxDocs=44218)
              0.05109862 = queryNorm
            0.47072473 = fieldWeight in 686, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              5.021064 = idf(docFreq=792, maxDocs=44218)
              0.046875 = fieldNorm(doc=686)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

Journals in the Information Science & Library Science category of Journal Citation Reports (JCR) were compared using both bibliometric and bibliographic features. Data collected covered journal impact factor (JIF), number of issues per year, number of authors per article, longevity, editorial board membership, frequency of publication, number of databases indexing the journal, number of aggregators providing full-text access, country of publication, JCR categories, Dewey decimal classification, and journal statement of scope. Three features significantly correlated with JIF: number of editorial board members and number of JCR categories in which a journal is listed correlated positively; journal longevity correlated negatively with JIF. Coword analysis of journal descriptions provided a proximity clustering of journals, which differed considerably from the clusters based on editorial board membership. Finally, a multiple linear regression model was built to predict the JIF based on all the collected bibliographic features.

0.028466603 = product of:
  0.056933206 = sum of:
    0.056933206 = product of:
      0.11386641 = sum of:
        0.11386641 = weight(_text_:journals in 3705) [ClassicSimilarity], result of:
          0.11386641 = score(doc=3705,freq=2.0), product of:
            0.25656942 = queryWeight, product of:
              5.021064 = idf(docFreq=792, maxDocs=44218)
              0.05109862 = queryNorm
            0.44380352 = fieldWeight in 3705, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              5.021064 = idf(docFreq=792, maxDocs=44218)
              0.0625 = fieldNorm(doc=3705)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

The authors propose using the technique of weighted citation to measure an article's prestige. The technique allocates a different weight to each reference by taking into account the impact of citing journals and citation time intervals. Weightedcitation captures prestige, whereas citation counts capture popularity. They compare the value variances for popularity and prestige for articles published in the Journal of the American Society for Information Science and Technology from 1998 to 2007, and find that the majority have comparable status.

0.024908276 = product of:
  0.049816553 = sum of:
    0.049816553 = product of:
      0.099633105 = sum of:
        0.099633105 = weight(_text_:journals in 3083) [ClassicSimilarity], result of:
          0.099633105 = score(doc=3083,freq=2.0), product of:
            0.25656942 = queryWeight, product of:
              5.021064 = idf(docFreq=792, maxDocs=44218)
              0.05109862 = queryNorm
            0.38832808 = fieldWeight in 3083, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              5.021064 = idf(docFreq=792, maxDocs=44218)
              0.0546875 = fieldNorm(doc=3083)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

Many studies on coauthorship networks focus on network topology and network statistical mechanics. This article takes a different approach by studying micro-level network properties with the aim of applying centrality measures to impact analysis. Using coauthorship data from 16 journals in the field of library and information science (LIS) with a time span of 20 years (1988-2007), we construct an evolving coauthorship network and calculate four centrality measures (closeness centrality, betweenness centrality, degree centrality, and PageRank) for authors in this network. We find that the four centrality measures are significantly correlated with citation counts. We also discuss the usability of centrality measures in author ranking and suggest that centrality measures can be useful indicators for impact analysis.

0.021349952 = product of:
  0.042699903 = sum of:
    0.042699903 = product of:
      0.08539981 = sum of:
        0.08539981 = weight(_text_:journals in 5219) [ClassicSimilarity], result of:
          0.08539981 = score(doc=5219,freq=2.0), product of:
            0.25656942 = queryWeight, product of:
              5.021064 = idf(docFreq=792, maxDocs=44218)
              0.05109862 = queryNorm
            0.33285263 = fieldWeight in 5219, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              5.021064 = idf(docFreq=792, maxDocs=44218)
              0.046875 = fieldNorm(doc=5219)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

Publishing articles in high-impact English journals is difficult for scholars around the world, especially for non-native English-speaking scholars (NNESs), most of whom struggle with proficiency in English. To uncover the differences in English scientific writing between native English-speaking scholars (NESs) and NNESs, we collected a large-scale data set containing more than 150,000 full-text articles published in PLoS between 2006 and 2015. We divided these articles into three groups according to the ethnic backgrounds of the first and corresponding authors, obtained by Ethnea, and examined the scientific writing styles in English from a two-fold perspective of linguistic complexity: (a) syntactic complexity, including measurements of sentence length and sentence complexity; and (b) lexical complexity, including measurements of lexical diversity, lexical density, and lexical sophistication. The observations suggest marginal differences between groups in syntactical and lexical complexity.

0.017791625 = product of:
  0.03558325 = sum of:
    0.03558325 = product of:
      0.0711665 = sum of:
        0.0711665 = weight(_text_:journals in 4608) [ClassicSimilarity], result of:
          0.0711665 = score(doc=4608,freq=2.0), product of:
            0.25656942 = queryWeight, product of:
              5.021064 = idf(docFreq=792, maxDocs=44218)
              0.05109862 = queryNorm
            0.2773772 = fieldWeight in 4608, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              5.021064 = idf(docFreq=792, maxDocs=44218)
              0.0390625 = fieldNorm(doc=4608)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

This study comprises a suite of analyses of words in article titles in order to reveal the cognitive structure of Library and Information Science (LIS). The use of title words to elucidate the cognitive structure of LIS has been relatively neglected. The present study addresses this gap by performing (a) co-word analysis and hierarchical clustering, (b) multidimensional scaling, and (c) determination of trends in usage of terms. The study is based on 10,344 articles published between 1988 and 2007 in 16 LIS journals. Methodologically, novel aspects of this study are: (a) its large scale, (b) removal of non-specific title words based on the "word concentration" measure (c) identification of the most frequent terms that include both single words and phrases, and (d) presentation of the relative frequencies of terms using "heatmaps". Conceptually, our analysis reveals that LIS consists of three main branches: the traditionally recognized library-related and information-related branches, plus an equally distinct bibliometrics/scientometrics branch. The three branches focus on: libraries, information, and science, respectively. In addition, our study identifies substructures within each branch. We also tentatively identify "information seeking behavior" as a branch that is establishing itself separate from the three main branches. Furthermore, we find that cognitive concepts in LIS evolve continuously, with no stasis since 1992. The most rapid development occurred between 1998 and 2001, influenced by the increased focus on the Internet. The change in the cognitive landscape is found to be driven by the emergence of new information technologies, and the retirement of old ones.

0.017791625 = product of:
  0.03558325 = sum of:
    0.03558325 = product of:
      0.0711665 = sum of:
        0.0711665 = weight(_text_:journals in 4445) [ClassicSimilarity], result of:
          0.0711665 = score(doc=4445,freq=2.0), product of:
            0.25656942 = queryWeight, product of:
              5.021064 = idf(docFreq=792, maxDocs=44218)
              0.05109862 = queryNorm
            0.2773772 = fieldWeight in 4445, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              5.021064 = idf(docFreq=792, maxDocs=44218)
              0.0390625 = fieldNorm(doc=4445)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

Citations in scientific literature are important both for tracking the historical development of scientific ideas and for forecasting research trends. However, the diffusion mechanisms underlying the citation process remain poorly understood, despite the frequent and longstanding use of citation counts for assessment purposes within the scientific community. Here, we extend the study of citation dynamics to a more general diffusion process to understand how citation growth associates with different diffusion patterns. Using a classic diffusion model, we quantify and illustrate specific diffusion mechanisms which have been proven to exert a significant impact on the growth and decay of citation counts. Experiments reveal a positive relation between the "low p and low q" pattern and high scientific impact. A sharp citation peak produced by rapid change of citation counts, however, has a negative effect on future impact. In addition, we have suggested a simple indicator, saturation level, to roughly estimate an individual article's current stage in the life cycle and its potential to attract future attention. The proposed approach can also be extended to higher levels of aggregation (e.g., individual scientists, journals, institutions), providing further insights into the practice of scientific evaluation.

0.017791625 = product of:
  0.03558325 = sum of:
    0.03558325 = product of:
      0.0711665 = sum of:
        0.0711665 = weight(_text_:journals in 5963) [ClassicSimilarity], result of:
          0.0711665 = score(doc=5963,freq=2.0), product of:
            0.25656942 = queryWeight, product of:
              5.021064 = idf(docFreq=792, maxDocs=44218)
              0.05109862 = queryNorm
            0.2773772 = fieldWeight in 5963, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              5.021064 = idf(docFreq=792, maxDocs=44218)
              0.0390625 = fieldNorm(doc=5963)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

Collaborations are pervasive in current science. Collaborations have been studied and encouraged in many disciplines. However, little is known about how a team really functions from the detailed division of labor within. In this research, we investigate the patterns of scientific collaboration and division of labor within individual scholarly articles by analyzing their co-contributorship networks. Co-contributorship networks are constructed by performing the one-mode projection of the author-task bipartite networks obtained from 138,787 articles published in PLoS journals. Given an article, we define 3 types of contributors: Specialists, Team-players, and Versatiles. Specialists are those who contribute to all their tasks alone; team-players are those who contribute to every task with other collaborators; and versatiles are those who do both. We find that team-players are the majority and they tend to contribute to the 5 most common tasks as expected, such as "data analysis" and "performing experiments." The specialists and versatiles are more prevalent than expected by our designed 2 null models. Versatiles tend to be senior authors associated with funding and supervision. Specialists are associated with 2 contrasting roles: the supervising role as team leaders or marginal and specialized contributors.

0.012115525 = product of:
  0.02423105 = sum of:
    0.02423105 = product of:
      0.0484621 = sum of:
        0.0484621 = weight(_text_:22 in 4188) [ClassicSimilarity], result of:
          0.0484621 = score(doc=4188,freq=2.0), product of:
            0.17893866 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.05109862 = queryNorm
            0.2708308 = fieldWeight in 4188, 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=4188)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Date

22. 1.2011 13:02:21

0.010384736 = product of:
  0.020769471 = sum of:
    0.020769471 = product of:
      0.041538943 = sum of:
        0.041538943 = weight(_text_:22 in 1521) [ClassicSimilarity], result of:
          0.041538943 = score(doc=1521,freq=2.0), product of:
            0.17893866 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.05109862 = queryNorm
            0.23214069 = fieldWeight in 1521, 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=1521)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Date

22. 8.2014 16:52:04