91,590 research outputs found
Popular and/or Prestigious? Measures of Scholarly Esteem
Citation analysis does not generally take the quality of citations into
account: all citations are weighted equally irrespective of source. However, a
scholar may be highly cited but not highly regarded: popularity and prestige
are not identical measures of esteem. In this study we define popularity as the
number of times an author is cited and prestige as the number of times an
author is cited by highly cited papers. Information Retrieval (IR) is the test
field. We compare the 40 leading researchers in terms of their popularity and
prestige over time. Some authors are ranked high on prestige but not on
popularity, while others are ranked high on popularity but not on prestige. We
also relate measures of popularity and prestige to date of Ph.D. award, number
of key publications, organizational affiliation, receipt of prizes/honors, and
gender.Comment: 26 pages, 5 figure
The Closer the Better: Similarity of Publication Pairs at Different Co-Citation Levels
We investigate the similarities of pairs of articles which are co-cited at
the different co-citation levels of the journal, article, section, paragraph,
sentence and bracket. Our results indicate that textual similarity,
intellectual overlap (shared references), author overlap (shared authors),
proximity in publication time all rise monotonically as the co-citation level
gets lower (from journal to bracket). While the main gain in similarity happens
when moving from journal to article co-citation, all level changes entail an
increase in similarity, especially section to paragraph and paragraph to
sentence/bracket levels. We compare results from four journals over the years
2010-2015: Cell, the European Journal of Operational Research, Physics Letters
B and Research Policy, with consistent general outcomes and some interesting
differences. Our findings motivate the use of granular co-citation information
as defined by meaningful units of text, with implications for, among others,
the elaboration of maps of science and the retrieval of scholarly literature
Recognizing cited facts and principles in legal judgements
In common law jurisdictions, legal professionals cite facts and legal principles from precedent cases to support their arguments before the court for their intended outcome in a current case. This practice stems from the doctrine of stare decisis, where cases that have similar facts should receive similar decisions with respect to the principles. It is essential for legal professionals to identify such facts and principles in precedent cases, though this is a highly time intensive task. In this paper, we present studies that demonstrate that human annotators can achieve reasonable agreement on which sentences in legal judgements contain cited facts and principles (respectively, Îș=0.65 and Îș=0.95 for inter- and intra-annotator agreement). We further demonstrate that it is feasible to automatically annotate sentences containing such legal facts and principles in a supervised machine learning framework based on linguistic features, reporting per category precision and recall figures of between 0.79 and 0.89 for classifying sentences in legal judgements as cited facts, principles or neither using a Bayesian classifier, with an overall Îș of 0.72 with the human-annotated gold standard
Choosing and using methodological search filters : searchers' views
© 2014 The authors. Health Information and Libraries Journal © 2014 Health Libraries Group.Peer reviewedPostprin
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