@inproceedings{lozic-etal-2017-takelab,
title = "{T}ake{L}ab at {S}em{E}val-2017 Task 4: Recent Deaths and the Power of Nostalgia in Sentiment Analysis in {T}witter",
author = "Lozi{\'c}, David and
{\v{S}}ari{\'c}, Doria and
Toki{\'c}, Ivan and
Medi{\'c}, Zoran and
{\v{S}}najder, Jan",
editor = "Bethard, Steven and
Carpuat, Marine and
Apidianaki, Marianna and
Mohammad, Saif M. and
Cer, Daniel and
Jurgens, David",
booktitle = "Proceedings of the 11th International Workshop on Semantic Evaluation ({S}em{E}val-2017)",
month = aug,
year = "2017",
address = "Vancouver, Canada",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/S17-2132",
doi = "10.18653/v1/S17-2132",
pages = "784--789",
abstract = "This paper describes the system we submitted to SemEval-2017 Task 4 (Sentiment Analysis in Twitter), specifically subtasks A, B, and D. Our main focus was topic-based message polarity classification on a two-point scale (subtask B). The system we submitted uses a Support Vector Machine classifier with rich set of features, ranging from standard to more creative, task-specific features, including a series of rating-based features as well as features that account for sentimental reminiscence of past topics and deceased famous people. Our system ranked 14th out of 39 submissions in subtask A, 5th out of 24 submissions in subtask B, and 3rd out of 16 submissions in subtask D.",
}
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%0 Conference Proceedings
%T TakeLab at SemEval-2017 Task 4: Recent Deaths and the Power of Nostalgia in Sentiment Analysis in Twitter
%A Lozić, David
%A Šarić, Doria
%A Tokić, Ivan
%A Medić, Zoran
%A Šnajder, Jan
%Y Bethard, Steven
%Y Carpuat, Marine
%Y Apidianaki, Marianna
%Y Mohammad, Saif M.
%Y Cer, Daniel
%Y Jurgens, David
%S Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017)
%D 2017
%8 August
%I Association for Computational Linguistics
%C Vancouver, Canada
%F lozic-etal-2017-takelab
%X This paper describes the system we submitted to SemEval-2017 Task 4 (Sentiment Analysis in Twitter), specifically subtasks A, B, and D. Our main focus was topic-based message polarity classification on a two-point scale (subtask B). The system we submitted uses a Support Vector Machine classifier with rich set of features, ranging from standard to more creative, task-specific features, including a series of rating-based features as well as features that account for sentimental reminiscence of past topics and deceased famous people. Our system ranked 14th out of 39 submissions in subtask A, 5th out of 24 submissions in subtask B, and 3rd out of 16 submissions in subtask D.
%R 10.18653/v1/S17-2132
%U https://aclanthology.org/S17-2132
%U https://doi.org/10.18653/v1/S17-2132
%P 784-789
Markdown (Informal)
[TakeLab at SemEval-2017 Task 4: Recent Deaths and the Power of Nostalgia in Sentiment Analysis in Twitter](https://aclanthology.org/S17-2132) (Lozić et al., SemEval 2017)
ACL