ECNU at SemEval-2018 Task 1: Emotion Intensity Prediction Using Effective Features and Machine Learning Models

Huimin Xu; Man Lan; Yuanbin Wu

doi:10.18653/v1/s18-1035

ECNU at SemEval-2018 Task 1: Emotion Intensity Prediction Using Effective Features and Machine Learning Models

Huimin Xu
, Man Lan^*
, Yuanbin Wu

^*此作品的通讯作者

计算机科学与技术学院

East China Normal University
Shanghai Key Laboratory of Multidimensional Information Processing

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

6 引用（Scopus）

摘要

In this paper we describe our systems submitted to Semeval 2018 Task 1 “Affect in Tweet” (Mohammad et al., 2018). We participated in all subtasks of English tweets, including emotion intensity classification and quantification, valence intensity classification and quantification. In our systems, we extracted four types of features, including linguistic, sentiment lexicon, emotion lexicon and domain-specific features, then fed them to different regressors, finally combined the models to create an ensemble for the better performance. Officially released results showed that our system can be further extended.

源语言	英语
主期刊名	NAACL HLT 2018 - International Workshop on Semantic Evaluation, SemEval 2018 - Proceedings of the 12th Workshop
编辑	Marianna Apidianaki, Marianna Apidianaki, Saif M. Mohammad, Jonathan May, Ekaterina Shutova, Steven Bethard, Marine Carpuat
出版商	Association for Computational Linguistics (ACL)
页	231-235
页数	5
ISBN（电子版）	9781948087209
DOI	https://doi.org/10.18653/v1/s18-1035
出版状态	已出版 - 2018
活动	12th International Workshop on Semantic Evaluation, SemEval 2018, co-located with the 16th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL HLT 2018 - New Orleans, 美国期限: 5 6月 2018 → 6 6月 2018

出版系列

姓名	NAACL HLT 2018 - International Workshop on Semantic Evaluation, SemEval 2018 - Proceedings of the 12th Workshop

会议

会议	12th International Workshop on Semantic Evaluation, SemEval 2018, co-located with the 16th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL HLT 2018
国家/地区	美国
市	New Orleans
时期	5/06/18 → 6/06/18

访问文件

10.18653/v1/s18-1035

其它文件与链接

链接到 Scopus 的出版物

引用此

Xu, H., Lan, M., & Wu, Y. (2018). ECNU at SemEval-2018 Task 1: Emotion Intensity Prediction Using Effective Features and Machine Learning Models. 在 M. Apidianaki, M. Apidianaki, S. M. Mohammad, J. May, E. Shutova, S. Bethard, & M. Carpuat (编辑), NAACL HLT 2018 - International Workshop on Semantic Evaluation, SemEval 2018 - Proceedings of the 12th Workshop (页码 231-235). (NAACL HLT 2018 - International Workshop on Semantic Evaluation, SemEval 2018 - Proceedings of the 12th Workshop). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/s18-1035

Xu, Huimin ; Lan, Man ; Wu, Yuanbin. / ECNU at SemEval-2018 Task 1 : Emotion Intensity Prediction Using Effective Features and Machine Learning Models. NAACL HLT 2018 - International Workshop on Semantic Evaluation, SemEval 2018 - Proceedings of the 12th Workshop. 编辑 / Marianna Apidianaki ; Marianna Apidianaki ; Saif M. Mohammad ; Jonathan May ; Ekaterina Shutova ; Steven Bethard ; Marine Carpuat. Association for Computational Linguistics (ACL), 2018. 页码 231-235 (NAACL HLT 2018 - International Workshop on Semantic Evaluation, SemEval 2018 - Proceedings of the 12th Workshop).

@inproceedings{8c09cb9b54014e33b9203367b075d99d,

title = "ECNU at SemEval-2018 Task 1: Emotion Intensity Prediction Using Effective Features and Machine Learning Models",

abstract = "In this paper we describe our systems submitted to Semeval 2018 Task 1 “Affect in Tweet” (Mohammad et al., 2018). We participated in all subtasks of English tweets, including emotion intensity classification and quantification, valence intensity classification and quantification. In our systems, we extracted four types of features, including linguistic, sentiment lexicon, emotion lexicon and domain-specific features, then fed them to different regressors, finally combined the models to create an ensemble for the better performance. Officially released results showed that our system can be further extended.",

author = "Huimin Xu and Man Lan and Yuanbin Wu",

note = "Publisher Copyright: {\textcopyright} 2018 Association for Computational Linguistics; 12th International Workshop on Semantic Evaluation, SemEval 2018, co-located with the 16th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL HLT 2018 ; Conference date: 05-06-2018 Through 06-06-2018",

year = "2018",

doi = "10.18653/v1/s18-1035",

language = "英语",

series = "NAACL HLT 2018 - International Workshop on Semantic Evaluation, SemEval 2018 - Proceedings of the 12th Workshop",

publisher = "Association for Computational Linguistics (ACL)",

pages = "231--235",

editor = "Marianna Apidianaki and Marianna Apidianaki and Mohammad, \{Saif M.\} and Jonathan May and Ekaterina Shutova and Steven Bethard and Marine Carpuat",

booktitle = "NAACL HLT 2018 - International Workshop on Semantic Evaluation, SemEval 2018 - Proceedings of the 12th Workshop",

address = "澳大利亚",

}

Xu, H, Lan, M & Wu, Y 2018, ECNU at SemEval-2018 Task 1: Emotion Intensity Prediction Using Effective Features and Machine Learning Models. 在 M Apidianaki, M Apidianaki, SM Mohammad, J May, E Shutova, S Bethard & M Carpuat (编辑), NAACL HLT 2018 - International Workshop on Semantic Evaluation, SemEval 2018 - Proceedings of the 12th Workshop. NAACL HLT 2018 - International Workshop on Semantic Evaluation, SemEval 2018 - Proceedings of the 12th Workshop, Association for Computational Linguistics (ACL), 页码 231-235, 12th International Workshop on Semantic Evaluation, SemEval 2018, co-located with the 16th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL HLT 2018, New Orleans, 美国, 5/06/18. https://doi.org/10.18653/v1/s18-1035

ECNU at SemEval-2018 Task 1: Emotion Intensity Prediction Using Effective Features and Machine Learning Models. / Xu, Huimin; Lan, Man; Wu, Yuanbin.
NAACL HLT 2018 - International Workshop on Semantic Evaluation, SemEval 2018 - Proceedings of the 12th Workshop. 编辑 / Marianna Apidianaki; Marianna Apidianaki; Saif M. Mohammad; Jonathan May; Ekaterina Shutova; Steven Bethard; Marine Carpuat. Association for Computational Linguistics (ACL), 2018. 页码 231-235 (NAACL HLT 2018 - International Workshop on Semantic Evaluation, SemEval 2018 - Proceedings of the 12th Workshop).

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

TY - GEN

T1 - ECNU at SemEval-2018 Task 1

T2 - 12th International Workshop on Semantic Evaluation, SemEval 2018, co-located with the 16th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL HLT 2018

AU - Xu, Huimin

AU - Lan, Man

AU - Wu, Yuanbin

PY - 2018

Y1 - 2018

N2 - In this paper we describe our systems submitted to Semeval 2018 Task 1 “Affect in Tweet” (Mohammad et al., 2018). We participated in all subtasks of English tweets, including emotion intensity classification and quantification, valence intensity classification and quantification. In our systems, we extracted four types of features, including linguistic, sentiment lexicon, emotion lexicon and domain-specific features, then fed them to different regressors, finally combined the models to create an ensemble for the better performance. Officially released results showed that our system can be further extended.

AB - In this paper we describe our systems submitted to Semeval 2018 Task 1 “Affect in Tweet” (Mohammad et al., 2018). We participated in all subtasks of English tweets, including emotion intensity classification and quantification, valence intensity classification and quantification. In our systems, we extracted four types of features, including linguistic, sentiment lexicon, emotion lexicon and domain-specific features, then fed them to different regressors, finally combined the models to create an ensemble for the better performance. Officially released results showed that our system can be further extended.

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DO - 10.18653/v1/s18-1035

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BT - NAACL HLT 2018 - International Workshop on Semantic Evaluation, SemEval 2018 - Proceedings of the 12th Workshop

A2 - Apidianaki, Marianna

A2 - Mohammad, Saif M.

A2 - May, Jonathan

A2 - Shutova, Ekaterina

A2 - Bethard, Steven

A2 - Carpuat, Marine

PB - Association for Computational Linguistics (ACL)

Y2 - 5 June 2018 through 6 June 2018

ER -

Xu H, Lan M, Wu Y. ECNU at SemEval-2018 Task 1: Emotion Intensity Prediction Using Effective Features and Machine Learning Models. 在 Apidianaki M, Apidianaki M, Mohammad SM, May J, Shutova E, Bethard S, Carpuat M, 编辑, NAACL HLT 2018 - International Workshop on Semantic Evaluation, SemEval 2018 - Proceedings of the 12th Workshop. Association for Computational Linguistics (ACL). 2018. 页码 231-235. (NAACL HLT 2018 - International Workshop on Semantic Evaluation, SemEval 2018 - Proceedings of the 12th Workshop). doi: 10.18653/v1/s18-1035

ECNU at SemEval-2018 Task 1: Emotion Intensity Prediction Using Effective Features and Machine Learning Models

摘要

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