Work

Adaptive Recursive Neural Network for Target-dependent Twitter Sentiment Classification

Year: 2014

Type: conference-paper

Abstract: We propose Adaptive Recursive Neural Network (AdaRNN) for target-dependent Twitter sentiment classification.AdaRNN adaptively propagates the sentiments of words to target depending on the context and syntactic relationships between them.It consists of more than one composition functions, and we model the adaptive sentiment propagations as distributions over these composition functions.The experimental studies illustrate that AdaRNN improves the baseline methods.Furthermore, we introduce a manually annotated dataset for target-dependent Twitter sentiment analysis.

Source: Annual Meeting of the Association for Computational Linguistics (ACL)

DOI: 10.3115/v1/p14-2009

Authors: Li Dong, Furu Wei, Chuanqi Tan, Duyu Tang, Ming Zhou, Ke Xu

Institutions: Beihang University, Harbin Institute of Technology

Language: English

Topic: Sentiment Analysis and Opinion Mining

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

Funders: State Key Laboratory of Software Development Environment, National High-tech Research and Development Program, Specialized Research Fund for the Doctoral Program of Higher Education of China

Awards: G6883653490, G8784154758