CROSA: Context-aware cloud service ranking approach using online reviews based on sentiment analysis

[EN] The explosion of cloud services over the Internet has raised new challenges in cloud service selection and ranking. The existence of a great variety of offered cloud services made the users think deeply about the most appropriate services that meet their needs and at the same time are adaptable to their context. Nowadays, online reviews are used for the purpose of enhancing the effectiveness of finding useful product information, having impact on the consumers' decision-making process. In this context, the current paper suggests a context-aware cloud service ranking approach using online reviews and based on sentiment analysis (CROSA). Its main objective is to ease the cloud service selection. The CROSA approach analyzes sentiments associated with service measurement index (SMI)-based service properties for each alternative cloud service. Moreover, it enhances the cloud service decision-making by supporting fuzzy sentiments through the intuitionistic fuzzy set theory and PROMETHEE II. The experimental results presented in this paper show that this approach is efficient and performing.Ben-Abdallah, E.; Boukadi, K.; Lloret, J.; Hammami, M. (2021). CROSA: Context-aware cloud service ranking approach using online reviews based on sentiment analysis. Concurrency and Computation: Practice and Experience. 33(7):1-16. https://doi.org/10.1002/cpe.5358S11633

THE DRIVERS AND IMPACTS OF SOCIAL MEDIA INFLUENCERS: THE ROLE OF MIMICRY

Despite the growing trend of influencer marketing, little effort has been made to understanding the comprehensive mechanism as to how social media influencers (SMIs) influence their target audiences. Although previous SMI literature identified possible drivers and effects of SMIs, much of former research has focused on the peripheral traits of SMIs: identifying the effect of a SMI’s number of followers on a target’s influencer likability. Not much investigation has been undertaken to understand the principal traits of SMIs that allow them to amass audience in the first place and gain influence over their audiences. The dissertation filled this void in the literature. Drawing upon Influence Framework and Consumer’s Doppelganger Effect theory, the study developed an overarching, structural framework that explains the influence mechanism of a SMI over her target audience as a whole in which (i) a target’s perceptions toward a SMI’s influence attempts (attractiveness, prestige, expertise, information, and interaction) affect the target’s attitudes toward the SMI, believing that the SMI exercises taste leadership and opinion leadership (H1 to H6), (ii) the target’s positive attitudes toward the SMI trigger her conscious mimicry desire toward the SMI (H7 and H8), and (iii) the target’s mimicry desire directs her performance outcomes of social media WOM and purchase intention (H9 and H10). The study included both a qualitative method approach (focus group (n = 11)) and quantitative approaches (pre-test (n = 48), pilot test (n = 155), and main-test (n = 395) surveys via Mechanical Turk) to attest its conceptual model. The main-test results, using the Structural Equation Modeling (SEM) analysis via AMOS 23, confirmed that the conceptual model and all the hypothesized relationships were statistically significant. Further, the bootstrap results demonstrated that a target’s mimicry desire indeed served as a significant mediator linking the target’s attitudinal beliefs to behavioral decisions. The study’s findings provide insightful contributions to the SMI literature and practical implications for brand marketers in developing successful influencer marketing strategies

Designing Human-Centered Collective Intelligence

Human-Centered Collective Intelligence (HCCI) is an emergent research area that seeks to bring together major research areas like machine learning, statistical modeling, information retrieval, market research, and software engineering to address challenges pertaining to deriving intelligent insights and solutions through the collaboration of several intelligent sensors, devices and data sources. An archetypal contextual CI scenario might be concerned with deriving affect-driven intelligence through multimodal emotion detection sources in a bid to determine the likability of one movie trailer over another. On the other hand, the key tenets to designing robust and evolutionary software and infrastructure architecture models to address cross-cutting quality concerns is of keen interest in the “Cloud” age of today. Some of the key quality concerns of interest in CI scenarios span the gamut of security and privacy, scalability, performance, fault-tolerance, and reliability. I present recent advances in CI system design with a focus on highlighting optimal solutions for the aforementioned cross-cutting concerns. I also describe a number of design challenges and a framework that I have determined to be critical to designing CI systems. With inspiration from machine learning, computational advertising, ubiquitous computing, and sociable robotics, this literature incorporates theories and concepts from various viewpoints to empower the collective intelligence engine, ZOEI, to discover affective state and emotional intent across multiple mediums. The discerned affective state is used in recommender systems among others to support content personalization. I dive into the design of optimal architectures that allow humans and intelligent systems to work collectively to solve complex problems. I present an evaluation of various studies that leverage the ZOEI framework to design collective intelligence

The Social Media Influencer and Brand Switching.

The purpose of this study was to find out which type of informant the Social Media Influencer embodies when consumers voluntarily switch brands after the endorsement of a brand by a Social Media Influencer. To answer the research question, this thesis utilised a quantitative questionnaire which was created with the help of a qualitative pre-study to assess the relevance of dimensions proposed in the literature.The data results of the 190 successful questionnaires indicated that when the consumer switches out of dissatisfaction and a need for variety, the Social Media Influencer foremost embodies the role of an opinion leader. Oppositely, when the consumer switches out of a desire for social identification, the results indicated that the Social Media Influencer functions as an opinion leader, social leader and micro-celebrity. The findings of this thesis provide academics and practitioners with valuable insights into how to the Social Media Influencer can be perceived and analysed, specifically when the consumer voluntarily switches brands

Evaluation Theory for Characteristics of Cloud Identity Trust Framework

Trust management is a prominent area of security in cloud computing because insufficient trust management hinders cloud growth. Trust management systems can help cloud users to make the best decision regarding the security, privacy, Quality of Protection (QoP), and Quality of Service (QoS). A Trust model acts as a security strength evaluator and ranking service for the cloud and cloud identity applications and services. It might be used as a benchmark to setup the cloud identity service security and to find the inadequacies and enhancements in cloud infrastructure. This chapter addresses the concerns of evaluating cloud trust management systems, data gathering, and synthesis of theory and data. The conclusion is that the relationship between cloud identity providers and Cloud identity users can greatly benefit from the evaluation and critical review of current trust models

Diachronic profile of startup companies through social media

Peixoto, A. R., Almeida, A. D., António, N., Batista, F., & Ribeiro, R. (2023). Diachronic profile of startup companies through social media. Social Network Analysis and Mining, 13(1), 1-18. [52]. https://doi.org/10.1007/s13278-023-01055-2 --- Funding: Open access funding provided by FCT|FCCN (b-on). This work was partially supported by Fundação para a Ciência e a Tecnologia, I.P. (FCT) namely by ISTAR Projects: UIDB/04466/2020 and UIDP/04466/2020; UIDB/04152/2020 (MagIC/NOVA IMS); and UIDB/50021/2020 (INESC-ID).Social media platforms have become powerful tools for startups, helping them find customers and raise funding. In this study, we applied a social media intelligence-based methodology to analyze startups’ content and to understand how their communication strategies may differ during their scaling process. To understand if a startup’s social media content reflects its current business maturation position, we first defined an adequate life cycle model for startups based on funding rounds and product maturity. Using Twitter as the source of information and selecting a sample of known Portuguese IT startups at different phases of their life cycle, we analyzed their Twitter data. After preprocessing the data, using latent Dirichlet allocation, topic modeling techniques enabled the categorization of the data according to the topics arising in the published contents of the startups, making it possible to discover that contents can be grouped into five specific topics: “Fintech and ML,” “IT,” “Business Operations,” “Product/Service R&D,” and “Bank and Funding.” By comparing those profiles against the startup’s life cycle, we were able to understand how contents change over time. This provided a diachronic profile for each company, showing that while certain topics remain prevalent in the startup’s scaling, others depend on a particular phase of the startup’s cycle. Our analysis revealed that startups’ social media content differs along their life cycle, highlighting the importance of understanding how startups use social media at different stages of their development.publishersversioninpres

Public Discourse in the Russian Blogosphere: Mapping RuNet Politics and Mobilization

We analyzed Russian blogs to discover networks of discussion around politics and public affairs. Beginning with an initial set of over five million blogs, we used social network analysis to identify a highly active ‘Discussion Core’ of over 11,000. These were clustered according to long term patterns of citations within posts, and the resulting segmentation characterized through both automated and human content analysis. Key findings include: * Unlike their counterparts in the US and elsewhere, Russian bloggers prefer platforms that combine features typical of blogs with features of social network services (SNSs) like Facebook. Russian blogging is dominated by a handful of these “SNS hybrids.” * While the larger Russian blogosphere is highly divided according to platform, there is a central Discussion Core that contains the majority of political and public affairs discourse. This core is comprised mainly, though not exclusively, of blogs on the LiveJournal platform

Information and Communication Technologies in Tourism 2022

This open access book presents the proceedings of the International Federation for IT and Travel & Tourism (IFITT)’s 29th Annual International eTourism Conference, which assembles the latest research presented at the ENTER2022 conference, which will be held on January 11–14, 2022. The book provides an extensive overview of how information and communication technologies can be used to develop tourism and hospitality. It covers the latest research on various topics within the field, including augmented and virtual reality, website development, social media use, e-learning, big data, analytics, and recommendation systems. The readers will gain insights and ideas on how information and communication technologies can be used in tourism and hospitality. Academics working in the eTourism field, as well as students and practitioners, will find up-to-date information on the status of research

Forgotten In Local Jails: A Carceral System Created To Fail Women.

The United States has seen an influx of incarcerated women since the 1980s with a 750% increase between 1980 and 2017. There is a substantial amount of literature about how women experience prison and the unique challenges they face as they reenter society such as motherhood, previous abuse, mental health, and housing. Conclusions drawn suggest that the current structure fails to prepare women for a society that denounces women who have been incarcerated. What is less known is how this research translates to the jail environment. For reasons to be discussed, it is likely that local jails are even less equipped to address women’s needs. We used data from in-depth semi-structured interviews with 14 women housed in a local urban jail to explore perceptions of jail and reentry prospects. The overriding feeling was that the jail was indifferent toward women and failed to prepare them for successful integration into society. Recommendations for improved jail conditions and reentry programming for women housed in jail are discussed

Cloud service data collection for cloud service selection

Data collection for cloud DSS tools is a huge challenge not only because of the lack of integration of quality of experience with existing cloud data but also by not having a holistic view of security characteristics in cloud. We solve it by using crowdsourcing techniques&providing a security V too