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Neural induction of a lexicon for fast and interpretable stance classification.

Clos, J�r�mie; Wiratunga, Nirmalie


J�r�mie Clos


Jorge Gracia

Francis Bond

John P. McCrae

Paul Buitelaar

Christian Chiarcos

Sebastian Hellmann


Large-scale social media classification faces the following two challenges: algorithms can be hard to adapt to Web-scale data, and the predictions that they provide are difficult for humans to understand. Those two challenges are solved at the cost of some accuracy by lexicon-based classifiers, which offer a white-box approach to text mining by using a trivially interpretable additive model. However current techniques for lexicon-based classification limit themselves to using hand-crafted lexicons, which suffer from human bias and are difficult to extend, or automatically generated lexicons, which are induced using point-estimates of some predefined probabilistic measure on a corpus of interest. In this work we propose a new approach to learn robust lexicons, using the backpropagation algorithm to ensure generalization power without sacrificing model readability. We evaluate our approach on a stance detection task, on two different datasets, and find that our lexicon outperforms standard lexicon approaches.


CLOS, J. and WIRATUNGA, N. 2017. Neural induction of a lexicon for fast and interpretable stance classification. In Gracia, J., Bond, F., McCrae, J.P., Buitelaar, P., Chiarcos, C. and Hellmann, S. (eds.) Language, data and knowledge: proceedings of the 1st International conference on language, data and knowledge (LDK 2017), 19-20 June 2017, Galway, Ireland. Lecture notes in computer science, 10318. Cham: Springer [online], pages 181-193. Available from:

Conference Name 1st International conference on language, data and knowledge (LDK 2017)
Conference Location Galway, Ireland
Start Date Jun 19, 2017
End Date Jun 20, 2017
Acceptance Date Apr 4, 2017
Online Publication Date May 27, 2017
Publication Date May 27, 2017
Deposit Date Jun 4, 2018
Publicly Available Date Jun 4, 2018
Print ISSN 0302-9743
Publisher Springer
Pages 181-193
Series Title Lecture notes in computer science
Series Number 10318
Series ISSN 0302-9743
ISBN 9783319598871
Keywords Decision function; Aggregation function; Computational graph; Sentiment lexicon; Pointwise mutual information
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