@inproceedings{jacques-etal-2018-clac,
title = "{CL}a{C} @ {DEFT} 2018: Sentiment analysis of tweets on transport from {{\^I}}le-de-{F}rance",
author = "Jacques, Simon and
Farahnak, Farhood and
Kosseim, Leila",
editor = "S{\'e}billot, Pascale and
Claveau, Vincent",
booktitle = "Actes de la Conf{\'e}rence TALN. Volume 2 - D{\'e}monstrations, articles des Rencontres Jeunes Chercheurs, ateliers DeFT",
month = "5",
year = "2018",
address = "Rennes, France",
publisher = "ATALA",
url = "https://aclanthology.org/2018.jeptalnrecital-deft.3",
pages = "239--248",
abstract = "CLaC @ DEFT 2018: Analysis of tweets on transport on the {\^I}le-de-France This paper describes the system deployed by the CLaC lab at Concordia University in Montreal for the DEFT 2018 shared task. The competition consisted in four different tasks; however, due to lack of time, we only participated in the first two. We participated with a system based on conventional supervised learning methods: a support vector machine classifier and an artificial neural network. For task 1, our best approach achieved an F-measure of 87.61{\%}; while at task 2, we achieve 51.03{\%}, situating our system below the average of the other participants.",
}
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%0 Conference Proceedings
%T CLaC @ DEFT 2018: Sentiment analysis of tweets on transport from Île-de-France
%A Jacques, Simon
%A Farahnak, Farhood
%A Kosseim, Leila
%Y Sébillot, Pascale
%Y Claveau, Vincent
%S Actes de la Conférence TALN. Volume 2 - Démonstrations, articles des Rencontres Jeunes Chercheurs, ateliers DeFT
%D 2018
%8 May
%I ATALA
%C Rennes, France
%F jacques-etal-2018-clac
%X CLaC @ DEFT 2018: Analysis of tweets on transport on the Île-de-France This paper describes the system deployed by the CLaC lab at Concordia University in Montreal for the DEFT 2018 shared task. The competition consisted in four different tasks; however, due to lack of time, we only participated in the first two. We participated with a system based on conventional supervised learning methods: a support vector machine classifier and an artificial neural network. For task 1, our best approach achieved an F-measure of 87.61%; while at task 2, we achieve 51.03%, situating our system below the average of the other participants.
%U https://aclanthology.org/2018.jeptalnrecital-deft.3
%P 239-248
Markdown (Informal)
[CLaC @ DEFT 2018: Sentiment analysis of tweets on transport from Île-de-France](https://aclanthology.org/2018.jeptalnrecital-deft.3) (Jacques et al., JEP/TALN/RECITAL 2018)
ACL