16,695 research outputs found
Automated scholarly paper review: Technologies and challenges
Peer review is a widely accepted mechanism for research evaluation, playing a
pivotal role in scholarly publishing. However, criticisms have long been
leveled on this mechanism, mostly because of its inefficiency and subjectivity.
Recent years have seen the application of artificial intelligence (AI) in
assisting the peer review process. Nonetheless, with the involvement of humans,
such limitations remain inevitable. In this review paper, we propose the
concept and pipeline of automated scholarly paper review (ASPR) and review the
relevant literature and technologies of achieving a full-scale computerized
review process. On the basis of the review and discussion, we conclude that
there is already corresponding research and implementation at each stage of
ASPR. We further look into the challenges in ASPR with the existing
technologies. The major difficulties lie in imperfect document parsing and
representation, inadequate data, defective human-computer interaction and
flawed deep logical reasoning. Moreover, we discuss the possible moral &
ethical issues and point out the future directions of ASPR. In the foreseeable
future, ASPR and peer review will coexist in a reinforcing manner before ASPR
is able to fully undertake the reviewing workload from humans
Detecting Emerging Technologies in Artificial Intelligence Scientific Ecosystem Using an Indicator-based Model
Early identification of emergent topics is of eminent importance due to their
potential impacts on society. There are many methods for detecting emerging
terms and topics, all with advantages and drawbacks. However, there is no
consensus about the attributes and indicators of emergence. In this study, we
evaluate emerging topic detection in the field of artificial intelligence using
a new method to evaluate emergence. We also introduce two new attributes of
collaboration and technological impact which can help us use both paper and
patent information simultaneously. Our results confirm that the proposed new
method can successfully identify the emerging topics in the period of the
study. Moreover, this new method can provide us with the score of each
attribute and a final emergence score, which enable us to rank the emerging
topics with their emergence scores and each attribute score
Early identification of important patents through network centrality
One of the most challenging problems in technological forecasting is to
identify as early as possible those technologies that have the potential to
lead to radical changes in our society. In this paper, we use the US patent
citation network (1926-2010) to test our ability to early identify a list of
historically significant patents through citation network analysis. We show
that in order to effectively uncover these patents shortly after they are
issued, we need to go beyond raw citation counts and take into account both the
citation network topology and temporal information. In particular, an
age-normalized measure of patent centrality, called rescaled PageRank, allows
us to identify the significant patents earlier than citation count and PageRank
score. In addition, we find that while high-impact patents tend to rely on
other high-impact patents in a similar way as scientific papers, the patents'
citation dynamics is significantly slower than that of papers, which makes the
early identification of significant patents more challenging than that of
significant papers.Comment: 14 page
“Excellence R Us”: university research and the fetishisation of excellence
The rhetoric of “excellence” is pervasive across the academy. It is used to refer to research outputs as well as researchers, theory and education, individuals and organisations, from art history to zoology. But does “excellence” actually mean anything? Does this pervasive narrative of “excellence” do any good? Drawing on a range of sources we interrogate “excellence” as a concept and find that it has no intrinsic meaning in academia. Rather it functions as a linguistic interchange mechanism. To investigate whether this linguistic function is useful we examine how the rhetoric of excellence combines with narratives of scarcity and competition to show that the hypercompetition that arises from the performance of “excellence” is completely at odds with the qualities of good research. We trace the roots of issues in reproducibility, fraud, and homophily to this rhetoric. But we also show that this rhetoric is an internal, and not primarily an external, imposition. We conclude by proposing an alternative rhetoric based on soundness and capacity-building. In the final analysis, it turns out that that “excellence” is not excellent. Used in its current unqualified form it is a pernicious and dangerous rhetoric that undermines the very foundations of good research and scholarship
The citation wake of publications detects Nobel laureates' papers
For several decades, a leading paradigm of how to quantitatively assess
scientific research has been the analysis of the aggregated citation
information in a set of scientific publications. Although the representation of
this information as a citation network has already been coined in the 1960s, it
needed the systematic indexing of scientific literature to allow for impact
metrics that actually made use of this network as a whole improving on the then
prevailing metrics that were almost exclusively based on the number of direct
citations. However, besides focusing on the assignment of credit, the paper
citation network can also be studied in terms of the proliferation of
scientific ideas. Here we introduce a simple measure based on the
shortest-paths in the paper's in-component or, simply speaking, on the shape
and size of the wake of a paper within the citation network. Applied to a
citation network containing Physical Review publications from more than a
century, our approach is able to detect seminal articles which have introduced
concepts of obvious importance to the further development of physics. We
observe a large fraction of papers co-authored by Nobel Prize laureates in
physics among the top-ranked publications.Comment: 11 pages, 3 figure
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