The Impact of Figurative Language on Sentiment Analysis
Tomáš Hercig
and
Ladislav Lenc
Proceedings of the International Conference Recent Advances in Natural Language Processing, RANLP 2017 (2017)
BibTex
|
PDF
Abstract
Figurative language such as irony, sarcasm, and metaphor is considered a
significant challenge in sentiment analysis. These figurative devices can
sculpt the affect of an utterance and test the limits of sentiment analysis of
supposedly literal texts.
We explore the effect of figurative language on sentiment analysis. We
incorporate the figurative language indicators into the sentiment analysis
process and compare the results with and without the additional information
about them. We evaluate on the SemEval-2015 Task 11 data and outperform the
first team with our convolutional neural network model and additional training
data in terms of mean squared error and we follow closely behind the first
place in terms of cosine similarity.