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Lexicon induction for interpretable text classification.

Clos, J�r�mie; Wiratunga, Nirmalie


J�r�mie Clos


Jaap Kamps

Giannis Tsakonas

Yannis Manolopoulos

Lazaros Iliadis

Ioannis Karydis


The automated classification of text documents is an active research challenge in document-oriented information systems, helping users browse massive amounts of data, detecting likely authors of unsigned work, or analyzing large corpora along predefined dimensions of interest such as sentiment or emotion. Existing approaches to text classification tend toward building black-box algorithms, offering accurate classification at the price of not understanding the rationale behind each algorithmic prediction. Lexicon-based classifiers offer an alternative to black-box classifiers by modeling the classification problem with a trivially interpretable classifier. However, current techniques for lexiconbased document classification limit themselves to using either handcrafted lexicons, which suffer from human bias and are difficult to extend, or automatically generated lexicons, which are induced using pointestimates of some predefined probabilistic measure in the corpus of interest. This paper proposes LexicNet, an alternative way of generating high accuracy classification lexicons offering an optimal generalization power without sacrificing model interpretability. We evaluate our approach on two tasks: stance detection and sentiment classification. We find that our lexicon outperforms baseline lexicon induction approaches as well as several standard text classifiers.


CLOS, J. and WIRATUNGA, N. 2017. Lexicon induction for interpretable text classification. In Kampus, J., Tsakonas, G., Manolopoulos, Y., Iliadis, L. and Karydis, I. (eds.) Proceedings of the 21st International conference on theory and practice of digital libraries (TPDL 2017): research and advanced technology for digital libraries, 18-21 September 2017, Thessaloniki, Greece. Lecture notes in computer science, 10450. Cham: Springer [online], pages 498-510. Available from:

Conference Name 21st International conference on theory and practice of digital libraries (TPDL 2017)
Conference Location Thessaloniki, Greece
Start Date Sep 18, 2017
End Date Sep 21, 2017
Acceptance Date May 26, 2017
Online Publication Date Sep 2, 2017
Publication Date Sep 30, 2017
Deposit Date Oct 16, 2018
Publicly Available Date Oct 16, 2018
Print ISSN 0302-9743
Electronic ISSN 1611-3349
Publisher Springer
Pages 498-510
Series Title Lecture notes in computer science
Series Number 10450
Series ISSN 1611-3349
ISBN 9783319670072
Keywords Text classification; Lexicon induction; Sentiment analysis; Stance classification
Public URL


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