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The COVID-19 pandemic, a period of great turmoil, was coupled with the emergence of an “infodemic”, a state when the public was bombarded with vast amounts of unverified information from dubious sources that led to a chaotic information landscape. The excessive flow of messages to citizens, combined with the justified fear and uncertainty imposed by the unknown virus, cast a shadow on the credibility of even well-intentioned sources and affected the emotional state of the public. Several studies highlighted the mental toll this environment took on citizens by analyzing their discourse on online social networks (OSNs). In this study, we focus on the activity of prominent pharmaceutical companies on Twitter, currently known as X, as well as the public’s response during the COVID-19 pandemic. Communication between companies and users is examined and compared in two discrete channels, the COVID-19 and the non-COVID-19 channel, based on the content of the posts circulated in them in the period between March 2020 and September 2022, while the emotional profile of the content is outlined through a state-of-the-art emotion analysis model. Our findings indicate significantly increased activity in the COVID-19 channel compared to the non-COVID-19 channel while the predominant emotion in both channels is joy. However, the COVID-19 channel exhibited an upward trend in the circulation of fear by the public. The quotes and replies produced by the users, with a stark presence of negative charge and diffusion indicators, reveal the public’s preference for promoting tweets conveying an emotional charge, such as fear, surprise, and joy. The findings of this research study can inform the development of communication strategies based on emotion-aware messages in future crises.

The classic example of machine learning is based on isolated learning—a single model for each task using a single dataset [...]

Immersive technologies are revolutionary technological advancements that offer users unparalleled experiences of immersion in a virtual or mixed world of virtual and real elements. In such technology, user privacy, security, and anonymity are paramount, as users often share private and sensitive information. Therefore, user authentication is a critical requirement in these environments. This paper presents a systematic literature review of recently published research papers on immersive technology-based user authentication mechanisms. After conducting the literature search in September 2023 using Scopus, the selection process identified 36 research publications that were further analyzed. The analysis revealed three major types of authentications related to immersive technologies, consistent with previous works: knowledge-based, biometric, and multi-factor methods. The reviewed papers are categorized according to these groups, and the methods used are scrutinized. To the best of our knowledge, this systematic literature review is the first that provides a comprehensive consolidation of immersive technologies for user authentication in virtual, augmented, and mixed reality.

BackgroundThe effectiveness of public health measures depends upon a community’s compliance as well as on its positive or negative emotions. ObjectiveThe purpose of this study was to perform an analysis of the expressed emotions in English tweets by Greek Twitter users during the first phase of the COVID-19 pandemic in Greece. MethodsThe period of this study was from January 25, 2020 to June 30, 2020. Data collection was performed by using appropriate search words with the filter-streaming application programming interface of Twitter. The emotional analysis of the tweets that satisfied the inclusion criteria was achieved using a deep learning approach that performs better by utilizing recurrent neural networks on sequences of characters. Emotional epidemiology tools such as the 6 basic emotions, that is, joy, sadness, disgust, fear, surprise, and anger based on the Paul Ekman classification were adopted. ResultsThe most frequent emotion that was detected in the tweets was “surprise” at the emerging contagion, while the imposed isolation resulted mostly in “anger” (odds ratio 2.108, 95% CI 0.986-4.506). Although the Greeks felt rather safe during the first phase of the COVID-19 pandemic, their positive and negative emotions reflected a masked “flight or fight” or “fear versus anger” response to the contagion. ConclusionsThe findings of our study show that emotional analysis emerges as a valid tool for epidemiology evaluations, design, and public health strategy and surveillance.

Blockchain is a distributed, immutable ledger technology initially developed to secure cryptocurrency transactions. Following its revolutionary use in cryptocurrencies, blockchain solutions are now being proposed to address various problems in different domains, and it is currently one of the most “disruptive” technologies. This paper presents a scoping review of the scientific literature for exploring the current research area of blockchain applications in the agricultural sector. The aim is to identify the service areas of agriculture where blockchain is used, the blockchain technology used, the data stored in it, its combination with external databases, the reason it is used, and the variety of agricultural products, as well as the level of maturity of the respective approaches. The study follows the PRISMA-ScR methodology. The purpose of conducting these scoping reviews is to identify the evidence in this field and clarify the key concepts. The literature search was conducted in April 2021 using Scopus and Google Scholar, and a systematic selection process identified 104 research articles for detailed study. Our findings show that in the field, although still in the early stages, with the majority of the studies in the design phase, several experiments have been conducted, so a significant percentage of the work is in the implementation or piloting phase. Finally, our research shows that the use of blockchain in this domain mainly concerns the integrity of agricultural production records, the monitoring of production steps, and the monitoring of products. However, other varied and remarkable blockchain applications include incentive mechanisms, a circular economy, data privacy, product certification, and reputation systems. This study is the first scoping review in this area, following a formal systematic literature review methodology and answering research questions that have not yet been addressed.

Blockchain is a distributed, immutable ledger technology introduced as the enabling mechanism to support cryptocurrencies. Blockchain solutions are currently being proposed to address diverse problems in different domains. This paper presents a scoping review of the scientific literature to map the current research area of blockchain applications in the biomedical domain. The goal is to identify biomedical problems treated with blockchain technology, the level of maturity of respective approaches, types of biomedical data considered, blockchain features and functionalities exploited and blockchain technology frameworks used. The study follows the PRISMA-ScR methodology. Literature search was conducted on August 2018 and the systematic selection process identified 47 research articles for detailed study. Our findings show that the field is still in its infancy, with the majority of studies in the conceptual or architectural design phase; only one study reports real world demonstration and evaluation. Research is greatly focused on integration, integrity and access control of health records and related patient data. However, other diverse and interesting applications are emerging, addressing medical research, clinical trials, medicines supply chain, and medical insurance. Keywords: Blockchain applications, Biomedical domain, Scoping review, PRISMA-ScR

The protection of personal data and privacy is a timeless challenge which has intensified in the modern era [...]

Online gambling, unlike other offline addiction forms, provides unprecedented opportunities for monitoring users’ behaviour in real-time, along with the ability to adapt persuasive interactions and messages that would match the gamblers usage and personal context. Online gambling industry usually offers Application Programming Interfaces (APIs) that are mainly intended to allow third-party applications to interact with their services and enhance user’s experience. In this article, we claim that such API’s can also be utilised to retrieve gamblers’ online data, such as browsing and betting history and other available offers, and use it to build more proactive and intelligent responsible gambling systems. We report on our experience in this field and make the argument that the available data for persuasive marketing and usability should, under certain usage conditions, also be made available for responsible online gambling services. We discuss the psychological foundations of our proposed approach and the risks and challenges typically identified when building such a software-assisted intervention, persuasion and emotion regulation technology. We also explain the potential impact of corporate social responsibility and data protection prospects. Furthermore, we explore the required principles that should be followed by the gambling industry for enabling responsible online gambling. We finally propose a conceptual architecture to show our vision and explain how it can be implemented. In the broader context, the article is intended to provide insights on building behavioural awareness and regulation information systems related to problematic digital media usage.

Biomedical research and clinical decision depend increasingly on scientific evidence realized by a number of authoritative databases, mostly public and continually enriched via peer scientific contributions. Given the dynamic nature of biomedical evidence data and their usage in the sensitive domain of biomedical science, it is important to ensure retrieved data integrity and non-repudiation. In this work, we present a blockchain-based notarization service that uses smart digital contracts to seal a biomedical database query and the respective results. The goal is to ensure that retrieved data cannot be modified after retrieval and that the database cannot validly deny that the particular data has been provided as a result of a specific query. Biomedical evidence data versioning is also supported. The feasibility of the proposed notarization approach is demonstrated using a real blockchain infrastructure and is tested on two different biomedical evidence databases: a publicly available medical risk factor reference repository and on the PubMed database of biomedical literature references and abstracts. Keywords: Biomedical repositories, Cryptographic techniques, Blockchain, Integrity, Non-repudiation, Versioning

e-Government services have evolved significantly over the last decade, from a paper-based bureaucratic procedure to digital services. Electronically processed transactions require limited physical interaction with the public administration, and provide reduced response times, increased transparency, confidentiality and integrity. Blockchain technology enhances many of the above properties as it facilitates immutability and transparency for the recorded transactions and can help establish trust among participants. In this paper, we conduct a literature review on the use of blockchain technology in e-government applications to identify e-government services that can benefit from the use of blockchains, types of technologies that are chosen for the proposed solutions, and their corresponding maturity levels. The aim is to demonstrate blockchain’s potential and contribution to the field, provide useful insights to governments who are considering investing in this innovative technology, and facilitate researchers in their future activities in blockchain-enabled e-government services.

Blockchain, a promising technology that has matured and nowadays is widely used in many fields, such as supply chain management, smart grids, agriculture and logistics, has also been proposed for the Internet of Vehicles (IoV) ecosystem to enhance the protection of the data that roadside units and vehicles exchange. Blockchain technology can inherently guarantee the availability, integrity and immutability of data stored in IoV, yet it cannot protect privacy and data confidentiality on its own. As such, solutions that utilise this technology have to consider the adoption of privacy-preserving schemes to address users’ privacy concerns. This paper provides a literature review of proposed solutions that provide different vehicular services using blockchain technology while preserving privacy. In this context, it analyses existing solutions’ main characteristics and properties to provide a comprehensive and critical overview and identifies their contribution in the field. Moreover, it provides suggestions to researchers for future work in the field of privacy-preserving blockchain-enabled solutions for vehicular networks.

The evolution of the Internet of Things is significantly affected by legal restrictions imposed for personal data handling, such as the European General Data Protection Regulation (GDPR). The main purpose of this regulation is to provide people in the digital age greater control over their personal data, with their freely given, specific, informed and unambiguous consent to collect and process the data concerning them. ADVOCATE is an advanced framework that fully complies with the requirements of GDPR, which, with the extensive use of blockchain and artificial intelligence technologies, aims to provide an environment that will support users in maintaining control of their personal data in the IoT ecosystem. This paper proposes and presents the Intelligent Policies Analysis Mechanism (IPAM) of the ADVOCATE framework, which, in an intelligent and fully automated manner, can identify conflicting rules or consents of the user, which may lead to the collection of personal data that can be used for profiling. In order to clearly identify and implement IPAM, the problem of recording user data from smart entertainment devices using Fuzzy Cognitive Maps (FCMs) was simulated. FCMs are an intelligent decision-making system that simulates the processes of a complex system, modeling the correlation base, knowing the behavioral and balance specialists of the system. Respectively, identifying conflicting rules that can lead to a profile, training is done using Extreme Learning Machines (ELMs), which are highly efficient neural systems of small and flexible architecture that can work optimally in complex environments.

We focus on personal data generated by the sensors and through the everyday usage of smart devices and take advantage of these data to build a non-invasive contextual suggestion system for tourism. The system, which we call Pythia, exploits the computational capabilities of modern smart devices to offer high quality personalized POI (point of interest) recommendations. To protect user privacy, we apply a privacy by design approach within all of the steps of creating Pythia. The outcome is a system that comprises important architectural and operational innovations. The system is designed to process sensitive personal data, such as location traces, browsing history and web searches (query logs), to automatically infer user preferences and build corresponding POI-based user profiles. These profiles are then used by a contextual suggestion engine to anticipate user choices and make POI recommendations for tourists. Privacy leaks are minimized by implementing an important part of the system functionality at the user side, either as a mobile app or as a client-side web application, and by taking additional precautions, like data generalization, wherever necessary. As a proof of concept, we present a prototype that implements the aforementioned mechanisms on the Android platform accompanied with certain web applications. Even though the current prototype focuses only on location data, the results from the evaluation of the contextual suggestion algorithms and the user experience feedback from volunteers who used the prototype are very positive.