SMI-Based Opinion Analysis of Cloud Services from Online Reviews

Ben-Abdallah, Emna; Boukadi, Khouloud; Hammami, Mohamed

doi:10.1007/978-3-319-76348-4_66

Cited by 3 publications

(2 citation statements)

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“…(3) Step 3: Content-based population: this step is mainly based on the review content, the SentiWordNet dictionary (Esuli and Sebastiani, 2006), the work presented in Ben-Abdallah et al (2018) and the populated ontology generated through the two previous steps. In fact, we identify from the review content the reviewed service properties, the use case and the used tools and languages.…”

Section: Ontology Implementationmentioning

confidence: 99%

“…Roughly, 77% of people read consumer reviews before buying as much as personal recommendations (RODELA, 2017). A multitude of theories in the literature is meant to evaluate and analyze the consumers' views on products or services using other users' insights through online reviews in several domains (Abirami;Askarunisa, 2017;Ben-Abdallah et al, 2018;Villanueva et al, 2016). In the cloud service field, several online review sites, such as TrustRadius and G2 Crowd have been proposed over the last decade and more and more cloud providers create their own official pages on social media networks, such as Facebook and Twitter.…”

Section: Introductionmentioning

confidence: 99%

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Personalized cloud service review analysis based on modularized ontology

Ben-Abdallah

Boukadi

Hammami

et al. 2020

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PurposeThe purpose of this paper is to analyze cloud reviews according to the end-user context and requirements.Design/methodology/approachpropose a comprehensive knowledge base composed of interconnected Web Ontology Language, namely, modular ontology for cloud service opinion analysis (SOPA). The SOPA knowledge base will be the basis of context-aware cloud service analysis using consumers' reviews. Moreover, the authors provide a framework to evaluate cloud services based on consumers' reviews opinions.FindingsThe findings show that there is a positive impact of personalizing the cloud service analysis by considering the reviewers' contexts in the performance of the framework. The authors also proved that the SOPA-based framework outperforms the available cloud review sites in term of precision, recall and F-measure.Research limitations/implicationsLimited information has been provided in the semantic web literature about the relationships between the different domains and the details on how that can be used to evaluate cloud service through consumer reviews and latent opinions. Furthermore, existing approaches are lacking lightweight and modular mechanisms which can be utilized to effectively exploit information existing in social media.Practical implicationsThe SOPA-based framework facilitates the opinion based service evaluation through a large number of consumer's reviews and assists the end-users in analyzing services as per their requirements and their own context.Originality/valueThe SOPA ontology is capable of representing the content of a product/service as well as its related opinions, which are extracted from the customer's reviews written in a specific context. Furthermore, the SOPA-based framework facilitates the opinion based service evaluation through a large number of consumer's reviews and assists the end-users in analyzing services as per their requirements and their own context.