Skip to Main content Skip to Navigation
Conference papers

Synalp-Empathic: A Valence Shifting Hybrid System for Sentiment Analysis

Alexandre Denis 1 Samuel Cruz-Lara 1 Nadia Bellalem 1 Lotfi Bellalem 1
1 SYNALP - Natural Language Processing : representations, inference and semantics
LORIA - NLPKD - Department of Natural Language Processing & Knowledge Discovery
Abstract : This paper describes the Synalp-Empathic system that competed in SemEval-2014 Task 9B Sentiment Analysis in Twitter. Our system combines syntactic-based va-lence shifting rules with a supervised learning algorithm (Sequential Minimal Optimization). We present the system, its features and evaluate their impact. We show that both the valence shifting mech-anism and the supervised model enable to reach good results.
Complete list of metadatas

Cited literature [18 references]  Display  Hide  Download

https://hal.archives-ouvertes.fr/hal-01099671
Contributor : Alexandre Denis <>
Submitted on : Thursday, January 22, 2015 - 4:12:11 PM
Last modification on : Tuesday, December 18, 2018 - 4:38:01 PM
Document(s) archivé(s) le : Thursday, April 23, 2015 - 10:05:12 AM

File

semeval2014.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : hal-01099671, version 1

Collections

Citation

Alexandre Denis, Samuel Cruz-Lara, Nadia Bellalem, Lotfi Bellalem. Synalp-Empathic: A Valence Shifting Hybrid System for Sentiment Analysis. 8th International Workshop on Semantic Evaluation (SemEval 2014), Aug 2014, Dublin, Ireland. pp.605 - 609. ⟨hal-01099671⟩

Share

Metrics

Record views

234

Files downloads

1484