The Impact of Figurative Language on Sentiment Analysis
Proceedings of the International Conference Recent Advances in Natural Language Processing, RANLP 2017 (2017)
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.
Authors
BibTex
@InProceedings{hercig-lenc:2017:RANLP, author = {Hercig, Tom\'{a}\v{s} and Lenc, Ladislav}, title = {The Impact of Figurative Language on Sentiment Analysis}, booktitle = {Proceedings of the International Conference Recent Advances in Natural Language Processing, RANLP 2017}, month = {September}, year = {2017}, address = {Varna, Bulgaria}, publisher = {INCOMA Ltd.}, pages = {301--308}, 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.}, url = {https://doi.org/10.26615/978-954-452-049-6_041} }
