Detecting Expressions of Blame or Praise in Text

Udochukwu Orizu, Yulan He


Abstract
The growth of social networking platforms has drawn a lot of attentions to the need for social computing. Social computing utilises human insights for computational tasks as well as design of systems that support social behaviours and interactions. One of the key aspects of social computing is the ability to attribute responsibility such as blame or praise to social events. This ability helps an intelligent entity account and understand other intelligent entities’ social behaviours, and enriches both the social functionalities and cognitive aspects of intelligent agents. In this paper, we present an approach with a model for blame and praise detection in text. We build our model based on various theories of blame and include in our model features used by humans determining judgment such as moral agent causality, foreknowledge, intentionality and coercion. An annotated corpus has been created for the task of blame and praise detection from text. The experimental results show that while our model gives similar results compared to supervised classifiers on classifying text as blame, praise or others, it outperforms supervised classifiers on more finer-grained classification of determining the direction of blame and praise, i.e., self-blame, blame-others, self-praise or praise-others, despite not using labelled training data.
Anthology ID:
L16-1651
Volume:
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)
Month:
May
Year:
2016
Address:
Portorož, Slovenia
Editors:
Nicoletta Calzolari, Khalid Choukri, Thierry Declerck, Sara Goggi, Marko Grobelnik, Bente Maegaard, Joseph Mariani, Helene Mazo, Asuncion Moreno, Jan Odijk, Stelios Piperidis
Venue:
LREC
SIG:
Publisher:
European Language Resources Association (ELRA)
Note:
Pages:
4124–4129
Language:
URL:
https://aclanthology.org/L16-1651
DOI:
Bibkey:
Cite (ACL):
Udochukwu Orizu and Yulan He. 2016. Detecting Expressions of Blame or Praise in Text. In Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16), pages 4124–4129, Portorož, Slovenia. European Language Resources Association (ELRA).
Cite (Informal):
Detecting Expressions of Blame or Praise in Text (Orizu & He, LREC 2016)
Copy Citation:
PDF:
https://aclanthology.org/L16-1651.pdf