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Incidental or Influential? - Challenges in Automatically Detecting Citation Importance Using Publication Full Texts

Pride, David and Knoth, Petr (2017). Incidental or Influential? - Challenges in Automatically Detecting Citation Importance Using Publication Full Texts. In: Research and Advanced Technology for Digital Libraries (Kamps, Jaap; Tsakonas, Giannis; Manolopoulos, Yannis; Iliadis, Lazaros and Karydis, Ioannis eds.), Lecture Notes in Computer Science ; Information Systems and Applications, incl. Internet/Web, and HCI, Springer, Cham, Switzerland, pp. 572–578.

DOI (Digital Object Identifier) Link: https://doi.org/10.1007/978-3-319-67008-9_48
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Abstract

This work looks in depth at several studies that have attempted to automate the process of citation importance classification based on the publications’ full text. We analyse a range of features that have been previously used in this task. Our experimental results confirm that the number of in-text references are highly predictive of influence. Contrary to the work of Valenzuela et al. (2015), we find abstract similarity one of the most predictive features. Overall, we show that many of the features previously described in literature are not particularly predictive. Consequently, we discuss challenges and potential improvements in the classification pipeline, provide a critical review of the performance of individual features and address the importance of constructing a large scale gold-standard reference dataset.

Item Type: Conference or Workshop Item
Copyright Holders: 2017 Springer International Publishing
Project Funding Details:
Funded Project NameProject IDFunding Body
OpenMinTeD654021EC (European Commission): FP(inc.Horizon2020, H2020, ERC)
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Item ID: 56753
Depositing User: Kay Dave
Date Deposited: 26 Sep 2018 14:28
Last Modified: 07 Dec 2018 11:12
URI: http://oro.open.ac.uk/id/eprint/56753
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