TopicThunder at SemEval-2017 Task 4: Sentiment Classification Using a Convolutional Neural Network with Distant Supervision

Simon Müller, Tobias Huonder, Jan Deriu, Mark Cieliebak


Abstract
In this paper, we propose a classifier for predicting topic-specific sentiments of English Twitter messages. Our method is based on a 2-layer CNN.With a distant supervised phase we leverage a large amount of weakly-labelled training data. Our system was evaluated on the data provided by the SemEval-2017 competition in the Topic-Based Message Polarity Classification subtask, where it ranked 4th place.
Anthology ID:
S17-2129
Volume:
Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017)
Month:
August
Year:
2017
Address:
Vancouver, Canada
Venue:
*SEMEVAL
SIGs:
SIGLEX | SIGSEM
Publisher:
Association for Computational Linguistics
Note:
Pages:
766–770
Language:
URL:
https://www.aclweb.org/anthology/S17-2129
DOI:
10.18653/v1/S17-2129
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PDF:
http://aclanthology.lst.uni-saarland.de/S17-2129.pdf