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  • Neural, Non-neural and Hybrid Stance Detection in Tweets on Catalan Independence

Neural, Non-neural and Hybrid Stance Detection in Tweets on Catalan Independence

We present our system LTL_UNI_DUE which participated in the shared task on automated stance detection in tweets on Catalan independence at IberEval 2017. In our system, we combine neural (LSTM) and non-neural (SVM) classifiers to a hybrid approach using a decision tree and heuristics.

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Conference:
Second Workshop on Evaluation of Human Language Technologies for Iberian Languages (IberEval 2017), Murcia, Spain, September 19, 2017
Date Issued:
27.07.2017
URN:
urn:nbn:de:hbz:464-20180627-144710-9
DOI:
10.17185/duepublico/46448
Language:
English
Type of Resource:
Text
Keywords:
IberEval
Collection:
E-Publications
Dewey Decimal Classification:
000 Computer science, information & general works
Subject categories of the Deutsche Nationalbibliografie:
004 Data processing Computer sciences
URL:
http://ceur-ws.org/Vol-1881/
Hosting institution:
Faculty of Engineering, Computer Science and Applied Cognitive Science
Info on primary publication:

Wojatzki, Michael; Zesch, Torsten: Neural, Non-neural and Hybrid Stance Detection in Tweets on Catalan Independence.

Published in: Proceedings of the Second Workshop on Evaluation of Human Language Technologies for Iberian Languages (IberEval 2017), Murcia, Spain, September 19, 2017, (CEUR Workshop Proceedings, vol. 1881), urn:nbn:de:0074-1881-7, pp. 178-184

Published on CEUR-WS: 27-Jul-2017

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