Full Seminar Details

David Pride

 David Pride
Incidental or influential: Challenges in automatic detection of citation importance
This event took place on Thursday 21 September 2017 at 11:30


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.

Watch the webcast replay >>

Jobs

Senior Research Fellow x 2

Knowledge Media Institute (KMi)
50,618 - 56,950 (Grade AC4)
Based in Milton Keynes
Permanent Position

WE ACCEPT APPLICATIONS FROM CITIZENS GLOBALLY The Knowledge Media Institute (KMi) is one of the top research centres in the world in the area of knowledge and media technologies, and we offer a creative and flexible working environment. The...

Research Assistant / Associate

Knowledge Media Institute (KMi)
29.799 - 38,833 (Grade AC1 / AC2)
Based in Milton Keynes
Temporary contract until 30th November 2018

WE ACCEPT APPLICATIONS FROM CITIZENS GLOBALLY The Knowledge Media Institute (KMi) is a distinct research unit within the Faculty of Science, Technology, Engineering and Mathematics (STEM) at the Open University. KMi is looking for a Research...

Research Assistant / Associate

Knowledge Media Institute (KMi)
29,799 - 38,833 (Grade AC1 / AC2)
Based in Milton Keynes
Temporary contract until 31st December 2018

WE ACCEPT APPLICATIONS FROM CITIZENS GLOBALLY The Knowledge Media Institute (KMi) is a distinct research unit within the Faculty of Science, Technology, Engineering and Mathematics (STEM) at the Open University. KMi is looking for a Research...

CONTACT US

Knowledge Media Institute
The Open University
Walton Hall
Milton Keynes
MK7 6AA
United Kingdom

Tel: +44 (0)1908 653800

Fax: +44 (0)1908 653169

Email: KMi Support

COMMENT

If you have any comments, suggestions or general feedback regarding our website, please email us at the address below.

Email: KMi Development Team