Autosoft Journal

Online Manuscript Access

Building Ontology for Different Emotional Contexts and Multilingual Environment in Opinion Mining



With the explosive growth of various social media applications, individuals and organizations are increasingly using their contents (e.g. reviews, forum discussions, blogs, micro-blogs, comments, and postings in social network sites) for decision-making. These contents are typical big data. Opinion mining or sentiment analysis focuses on how to extract emotional semantics from these big data to help users to get a better decision. That is not an easy task, because it faces many problems, such as different context may make the meaning of the same word change variously, at the same time multilingual environment restricts the full use of the analysis results. Ontology provides knowledge about specific domains that are understandable by both the computers and developers. Building ontology is mainly a useful first step in providing and formalizing the semantics of information representation. We proposed an ontology DEMLOnto based on six basic emotions to help users to share existed information. The ontology DEMLOnto would help in identifying the opinion features associated with the contextual environment, which may change along with applications. We built the ontology according to ontology engineering. It was developed on the platform Protégé by using OWL2.



Total Pages: 7
Pages: 65-72


Manuscript ViewPdf Subscription required to access this document

Obtain access this manuscript in one of the following ways

Already subscribed?

Need information on obtaining a subscription? Personal and institutional subscriptions are available.

Already an author? Have access via email address?


Volume: 24
Issue: 1
Year: 2018

Cite this document


Baldoni M. Intelligenza Artificiale

Gruber, Thomas R. "A Translation Approach to Portable Ontology Specifications." Knowledge Acquisition 5.2 (1993): 199-220. Crossref. Web.

Hu, Chuanping et al. "Semantic Link Network-Based Model for Organizing Multimedia Big Data." IEEE Transactions on Emerging Topics in Computing 2.3 (2014): 376-387. Crossref. Web.

Liu, Bing, and Lei Zhang. "A Survey of Opinion Mining and Sentiment Analysis." Mining Text Data (2012): 415-463. Crossref. Web.

Luo, Xiangfeng et al. "Building Association Link Network for Semantic Link on Web Resources." IEEE Transactions on Automation Science and Engineering 8.3 (2011): 482-494. Crossref. Web.

Noy N.F. Stanford Medical Informatics Technical Report SMI-2001-0880

Parrott Gerrod., W. Emotions in social psychology

Thakor, Pratik, and Sreela Sasi. "Ontology-Based Sentiment Analysis Process for Social Media Content." Procedia Computer Science 53 (2015): 199-207. Crossref. Web.

Xu L. Journal of the China Society for Scientific and Technical Information

Xu, Zheng et al. "Semantic Based Representing and Organizing Surveillance Big Data Using Video Structural Description Technology." Journal of Systems and Software 102 (2015): 217-225. Crossref. Web.

Bellatreche, Ladjel et al., eds. Concurrency and Computation: Practice and Experience 28.15 (2016): n. pag. Crossref. Web.

Xu, Zheng et al. "Building the Search Pattern of Web Users Using Conceptual Semantic Space Model." International Journal of Web and Grid Services 12.3 (2016): 328. Crossref. Web.

Xu, Zheng et al. "Participatory Sensing-Based Semantic and Spatial Analysis of Urban Emergency Events Using Mobile Social Media." EURASIP Journal on Wireless Communications and Networking 2016.1 (2016): n. pag. Crossref. Web.

Yaakub, Mohd Ridzwan, Yuefeng Li, and Jinglan Zhang. "Integration of Sentiment Analysis into Customer Relational Model: The Importance of Feature Ontology and Synonym." Procedia Technology 11 (2013): 495-501. Crossref. Web.


ISSN PRINT: 1079-8587
ISSN ONLINE: 2326-005X
DOI PREFIX: 10.31209
10.1080/10798587 with T&F
IMPACT FACTOR: 0.652 (2017/2018)

SJR: "The two years line is equivalent to journal impact factor ™ (Thomson Reuters) metric."

Journal: 1995-Present


TSI Press
18015 Bullis Hill
San Antonio, TX 78258 USA
PH: 210 479 1022
FAX: 210 479 1048