Topic-aware sentiment prediction for Chinese ConceptNet

Po Hao Chou, Richard Tzong Han Tsai, Jane Yung Jen Hsu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

Sentiment dictionary is a valuable resource in sentiment analysis research. Previous works propagate sentiment values from existing high quality dictionary on semantic networks to build wide coverage dictionary efficiently. But this approach suffers from quality degradation during propagation. In this work, we propose a topic-aware propagation method on Chinese ConceptNet to ease the issue. With this approach, every terms will have different sentiment values under different topics. The experimental result shows that the generated topic-aware sentiment dictionary helps improve the performance of polarity classification for texts.

Original languageEnglish
Title of host publicationTAAI 2015 - 2015 Conference on Technologies and Applications of Artificial Intelligence
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages419-426
Number of pages8
ISBN (Electronic)9781467396066
DOIs
StatePublished - 12 02 2016
Externally publishedYes
EventConference on Technologies and Applications of Artificial Intelligence, TAAI 2015 - Tainan, Taiwan
Duration: 20 11 201522 11 2015

Publication series

NameTAAI 2015 - 2015 Conference on Technologies and Applications of Artificial Intelligence

Conference

ConferenceConference on Technologies and Applications of Artificial Intelligence, TAAI 2015
Country/TerritoryTaiwan
CityTainan
Period20/11/1522/11/15

Bibliographical note

Publisher Copyright:
© 2015 IEEE.

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