Sentiment Analysis Based on Heterogeneous Multi-Relation Signed Network

Qin Zhao, Chenglei Yu, Jingyi Huang, Jie Lian and Dongdong An ()
Additional contact information
Qin Zhao: Shanghai Engineering Research Center of Intelligent Education and Big Data, Shanghai Normal University, Shanghai 201418, China
Chenglei Yu: Shanghai Engineering Research Center of Intelligent Education and Big Data, Shanghai Normal University, Shanghai 201418, China
Jingyi Huang: Shanghai Engineering Research Center of Intelligent Education and Big Data, Shanghai Normal University, Shanghai 201418, China
Jie Lian: Shanghai Engineering Research Center of Intelligent Education and Big Data, Shanghai Normal University, Shanghai 201418, China
Dongdong An: Shanghai Engineering Research Center of Intelligent Education and Big Data, Shanghai Normal University, Shanghai 201418, China

Mathematics, 2024, vol. 12, issue 2, 1-20

Abstract: Existing sentiment prediction methods often only classify users’ emotions into a few categories and cannot predict the variation of emotions under different topics. Meanwhile, network embedding methods that consider structural information often assume that links represent positive relationships, ignoring the possibility of negative relationships. To address these challenges, we present an innovative approach in sentiment analysis, focusing on the construction of a denser heterogeneous signed information network from sparse heterogeneous data. We explore the extraction of latent relationships between similar node types, integrating emotional reversal and meta-path similarity for relationship prediction. Our approach uniquely handles user-entity and topic-entity relationships, offering a tailored methodology for diverse entity types within heterogeneous networks. We contribute to a deeper understanding of emotional expressions and interactions in social networks, enhancing sentiment analysis techniques. Experimental results on four publicly available datasets demonstrate the superiority of our proposed model over state-of-the-art approaches.

Keywords: sentiment analysis; relationship prediction; heterogeneous signed networks; emotional prediction (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2024
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2227-7390/12/2/331/pdf (application/pdf)
https://www.mdpi.com/2227-7390/12/2/331/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:12:y:2024:i:2:p:331-:d:1322572

Access Statistics for this article

Mathematics is currently edited by Ms. Emma He

More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().