Improving short text modeling by two-level attention networks for sentiment classification

Yulong Li, Yi Cai, Ho Fung Leung, Qing Li

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

8 Citations (Scopus)


Understanding short texts is crucial to many applications, but it has always been challenging, due to the sparsity and ambiguity of information in short texts. In addition, sentiments expressed in those user-generated short texts are often implicit and context dependent. To address this, we propose a novel model based on two-level attention networks to identify the sentiment of short text. Our model first adopts attention mechanism to capture both local features and long-distance dependent features simultaneously, so that it is more robust against irrelevant information. Then the attention-based features are non-linearly combined with a bidirectional recurrent attention network, which enhances the expressive power of our model and automatically captures more relevant feature combinations. We evaluate the performance of our model on MR, SST-1 and SST-2 datasets. The experimental results show that our model can outperform the previous methods.

Original languageEnglish
Title of host publicationDatabase Systems for Advanced Applications - 23rd International Conference, DASFAA 2018, Proceedings
EditorsYannis Manolopoulos, Jianxin Li, Shazia Sadiq, Jian Pei
Number of pages13
ISBN (Print)9783319914510
Publication statusPublished - 1 Jan 2018
Externally publishedYes
Event23rd International Conference on Database Systems for Advanced Applications, DASFAA 2018 - Gold Coast, Australia
Duration: 21 May 201824 May 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10827 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference23rd International Conference on Database Systems for Advanced Applications, DASFAA 2018
CityGold Coast

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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