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Abstract
In this paper, we present a study for the identification of stancerelated 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.
Original language | English |
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Title of host publication | SETN '18 Proceedings of the 10th Hellenic Conference on Artificial Intelligence |
Place of Publication | New York |
Publisher | Association for Computing Machinery (ACM) |
Number of pages | 7 |
ISBN (Print) | 978-1-4503-6433-1 |
DOIs | |
Publication status | Published - 2018 Jul 15 |
Event | The 10th Hellenic Conference on Artificial Intelligence - University of Patras, Patras, Greece Duration: 2018 Jul 9 → 2018 Jul 15 Conference number: 10 http://setn2018.upatras.gr/ |
Conference
Conference | The 10th Hellenic Conference on Artificial Intelligence |
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Abbreviated title | SETN '18 |
Country/Territory | Greece |
City | Patras |
Period | 2018/07/09 → 2018/07/15 |
Internet address |
Subject classification (UKÄ)
- General Language Studies and Linguistics
Free keywords
- stance-taking
- text
- clustering
- feature extraction
- social media
Fingerprint
Dive into the research topics of 'Detection of Stance-Related Characteristics in Social Media Text'. Together they form a unique fingerprint.Projects
- 1 Finished
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StaViCTA - Advances in the description and explanation of stance in discourse using visual and computational text analytics
Paradis, C. (PI), Kerren, A. (PI), Sahlgren, M. (PI), Kucher, K. (Researcher), Skeppstedt, M. (Researcher) & Simaki, V. (PI)
2013/01/01 → 2018/01/02
Project: Research