19,238 research outputs found
Citation sentence reuse behavior of scientists: A case study on massive bibliographic text dataset of computer science
Our current knowledge of scholarly plagiarism is largely based on the
similarity between full text research articles. In this paper, we propose an
innovative and novel conceptualization of scholarly plagiarism in the form of
reuse of explicit citation sentences in scientific research articles. Note that
while full-text plagiarism is an indicator of a gross-level behavior, copying
of citation sentences is a more nuanced micro-scale phenomenon observed even
for well-known researchers. The current work poses several interesting
questions and attempts to answer them by empirically investigating a large
bibliographic text dataset from computer science containing millions of lines
of citation sentences. In particular, we report evidences of massive copying
behavior. We also present several striking real examples throughout the paper
to showcase widespread adoption of this undesirable practice. In contrast to
the popular perception, we find that copying tendency increases as an author
matures. The copying behavior is reported to exist in all fields of computer
science; however, the theoretical fields indicate more copying than the applied
fields
The distorted mirror of Wikipedia: a quantitative analysis of Wikipedia coverage of academics
Activity of modern scholarship creates online footprints galore. Along with
traditional metrics of research quality, such as citation counts, online images
of researchers and institutions increasingly matter in evaluating academic
impact, decisions about grant allocation, and promotion. We examined 400
biographical Wikipedia articles on academics from four scientific fields to
test if being featured in the world's largest online encyclopedia is correlated
with higher academic notability (assessed through citation counts). We found no
statistically significant correlation between Wikipedia articles metrics
(length, number of edits, number of incoming links from other articles, etc.)
and academic notability of the mentioned researchers. We also did not find any
evidence that the scientists with better WP representation are necessarily more
prominent in their fields. In addition, we inspected the Wikipedia coverage of
notable scientists sampled from Thomson Reuters list of "highly cited
researchers". In each of the examined fields, Wikipedia failed in covering
notable scholars properly. Both findings imply that Wikipedia might be
producing an inaccurate image of academics on the front end of science. By
shedding light on how public perception of academic progress is formed, this
study alerts that a subjective element might have been introduced into the
hitherto structured system of academic evaluation.Comment: To appear in EPJ Data Science. To have the Additional Files and
Datasets e-mail the corresponding autho
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