Disney at IEST 2018: Predicting Emotions using an Ensemble

Wojciech Witon, Pierre Colombo, Ashutosh Modi, Mubbasir Kapadia

Research output: Chapter in Book/Report/Conference proceedingConference contribution

27 Scopus citations

Abstract

This paper describes our participating system in the WASSA 2018 shared task on emotion prediction. The task focuses on implicit emotion prediction in a tweet. In this task, keywords corresponding to the six emotion labels used (anger, fear, disgust, joy, sad, and surprise) have been removed from the tweet text, making emotion prediction implicit and the task challenging. We propose a model based on an ensemble of classifiers for prediction. Each classifier uses a sequence of Convolutional Neural Network (CNN) architecture blocks and uses ELMo (Embeddings from Language Model) as an input. Our system achieves a 66.2% F1 score on the test set. The best performing system in the shared task has reported a 71.4% F1 score.

Original languageEnglish (US)
Title of host publicationWASSA 2018 - 9th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, Proceedings of the Workshop
PublisherAssociation for Computational Linguistics (ACL)
Pages248-253
Number of pages6
ISBN (Electronic)9781948087803
DOIs
StatePublished - 2018
Event9th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, WASSA 2018 - Brussels, Belgium
Duration: Oct 31 2018 → …

Publication series

NameWASSA 2018 - 9th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, Proceedings of the Workshop

Conference

Conference9th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, WASSA 2018
Country/TerritoryBelgium
CityBrussels
Period10/31/18 → …

All Science Journal Classification (ASJC) codes

  • Language and Linguistics
  • Linguistics and Language

Fingerprint

Dive into the research topics of 'Disney at IEST 2018: Predicting Emotions using an Ensemble'. Together they form a unique fingerprint.

Cite this