Detection of Stance-Related Characteristics in Social Media Text

Simaki, Vasiliki and Simakis, Panagiotis and Paradis, Carita and Kerren, Andreas (2018) Detection of Stance-Related Characteristics in Social Media Text. In: SETN '18 Proceedings of the 10th Hellenic Conference on Artificial Intelligence. Association for Computing Machinery, Inc, New York. ISBN 9781450364331

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Abstract

In this paper, we present a study for the identification of stance-related features in text data from social media. Based on our previous work on stance and our findings on stance patterns, we detected stance-related characteristics in a data set from Twitter and Facebook. We extracted various corpus-, quantitative- and computational-based features that proved to be significant for six stance categories (contrariety, hypotheticality, necessity, prediction, source of knowledge, and uncertainty), and we tested them in our data set. The results of a preliminary clustering method are presented and discussed as a starting point for future contributions in the field. The results of our experiments showed a strong correlation between different characteristics and stance constructions, which can lead us to a methodology for automatic stance annotation of these data.

Item Type:
Contribution in Book/Report/Proceedings
ID Code:
124841
Deposited By:
Deposited On:
23 Apr 2018 13:14
Refereed?:
Yes
Published?:
Published
Last Modified:
23 Sep 2020 06:57