Context-Sensitive twitter sentiment classification using neural network

Yafeng Ren; Yue Zhang; Meishan Zhang; Donghong Ji

Context-Sensitive twitter sentiment classification using neural network

Yafeng Ren
, Yue Zhang
, Meishan Zhang
, Donghong Ji

Wuhan University
Singapore University of Technology and Design
Heilongjiang University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

150 Scopus citations

Abstract

Sentiment classification on Twitter has attracted increasing research in recent years. Most existing work focuses on feature engineering according to the tweet content itself. In this paper, we propose a contextbased neural network model for Twitter sentiment analysis, incorporating contextualized features from relevant Tweets into the model in the form of word embedding vectors. Experiments on both balanced and unbalanced datasets show that our proposed models outperform the current state-of-The-Art.

Original language	English
Title of host publication	30th AAAI Conference on Artificial Intelligence, AAAI 2016
Publisher	AAAI press
Pages	215-221
Number of pages	7
ISBN (Electronic)	9781577357605
State	Published - 2016
Externally published	Yes
Event	30th AAAI Conference on Artificial Intelligence, AAAI 2016 - Phoenix, United States Duration: 12 Feb 2016 → 17 Feb 2016

Publication series

Name	30th AAAI Conference on Artificial Intelligence, AAAI 2016

Conference

Conference	30th AAAI Conference on Artificial Intelligence, AAAI 2016
Country/Territory	United States
City	Phoenix
Period	12/02/16 → 17/02/16

Cite this

@inproceedings{d3cd95e2b1b54259a0574cad8c835ea0,

title = "Context-Sensitive twitter sentiment classification using neural network",

abstract = "Sentiment classification on Twitter has attracted increasing research in recent years. Most existing work focuses on feature engineering according to the tweet content itself. In this paper, we propose a contextbased neural network model for Twitter sentiment analysis, incorporating contextualized features from relevant Tweets into the model in the form of word embedding vectors. Experiments on both balanced and unbalanced datasets show that our proposed models outperform the current state-of-The-Art.",

author = "Yafeng Ren and Yue Zhang and Meishan Zhang and Donghong Ji",

note = "Publisher Copyright: {\textcopyright} Copyright 2016, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.; 30th AAAI Conference on Artificial Intelligence, AAAI 2016 ; Conference date: 12-02-2016 Through 17-02-2016",

year = "2016",

language = "英语",

series = "30th AAAI Conference on Artificial Intelligence, AAAI 2016",

publisher = "AAAI press",

pages = "215--221",

booktitle = "30th AAAI Conference on Artificial Intelligence, AAAI 2016",

}

Context-Sensitive twitter sentiment classification using neural network. / Ren, Yafeng; Zhang, Yue; Zhang, Meishan et al.
30th AAAI Conference on Artificial Intelligence, AAAI 2016. AAAI press, 2016. p. 215-221 (30th AAAI Conference on Artificial Intelligence, AAAI 2016).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

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AU - Ren, Yafeng

AU - Zhang, Yue

AU - Zhang, Meishan

AU - Ji, Donghong

PY - 2016

Y1 - 2016

N2 - Sentiment classification on Twitter has attracted increasing research in recent years. Most existing work focuses on feature engineering according to the tweet content itself. In this paper, we propose a contextbased neural network model for Twitter sentiment analysis, incorporating contextualized features from relevant Tweets into the model in the form of word embedding vectors. Experiments on both balanced and unbalanced datasets show that our proposed models outperform the current state-of-The-Art.

AB - Sentiment classification on Twitter has attracted increasing research in recent years. Most existing work focuses on feature engineering according to the tweet content itself. In this paper, we propose a contextbased neural network model for Twitter sentiment analysis, incorporating contextualized features from relevant Tweets into the model in the form of word embedding vectors. Experiments on both balanced and unbalanced datasets show that our proposed models outperform the current state-of-The-Art.

UR - https://www.scopus.com/pages/publications/85007275345

M3 - 会议稿件

AN - SCOPUS:85007275345

T3 - 30th AAAI Conference on Artificial Intelligence, AAAI 2016

SP - 215

EP - 221

BT - 30th AAAI Conference on Artificial Intelligence, AAAI 2016

PB - AAAI press

T2 - 30th AAAI Conference on Artificial Intelligence, AAAI 2016

Y2 - 12 February 2016 through 17 February 2016

ER -

Context-Sensitive twitter sentiment classification using neural network

Abstract

Publication series

Conference

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