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In the modern digital realm, while artificial intelligence (AI) technologies pave the way for unprecedented opportunities, they also give rise to intricate cybersecurity issues, including threats like deepfakes and unanticipated AI-induced risks. This study aims to address the insufficient exploration of AI cybersecurity awareness in the current literature.

Using in-depth surveys across varied sectors (N = 150), the authors analyzed the correlation between the absence of AI risk content in organizational cybersecurity awareness programs and its impact on employee awareness.

A significant AI-risk knowledge void was observed among users: despite frequent interaction with AI tools, a majority remain unaware of specialized AI threats. A pronounced knowledge difference existed between those that are trained in AI risks and those who are not, more apparent among non-technical personnel and sectors managing sensitive information.

This study paves the way for thorough research, allowing for refinement of awareness initiatives tailored to distinct industries.

It is imperative for organizations to emphasize AI risk training, especially among non-technical staff. Industries handling sensitive data should be at the forefront.

Ensuring employees are aware of AI-related threats can lead to a safer digital environment for both organizations and society at large, given the pervasive nature of AI in everyday life.

Unlike most of the papers about AI risks, the authors do not trust subjective data from second hand papers, but use objective authentic data from the authors’ own up-to-date anonymous survey.

This review aims to show, broadly, how the h‐index has become a subject of widespread debate, how it has spawned many variants and diverse applications since first introduced in 2005 and some of the issues in its use.

The review drew on a range of material published in 1990 or so sources published since 2005. From these sources, a number of themes were identified and discussed ranging from the h‐index's advantages to which citation database might be selected for its calculation.

The analysis shows how the h‐index has quickly established itself as a major subject of interest in the field of bibliometrics. Study of the index ranges from its mathematical underpinning to a range of variants perceived to address the indexes' shortcomings. The review illustrates how widely the index has been applied but also how care must be taken in its application.

The use of bibliometric indicators to measure research performance continues, with the h‐index as its latest addition. The use of the h‐index, its variants and many applications to which it has been put are still at the exploratory stage. The review shows the breadth and diversity of this research and the need to verify the veracity of the h‐index by more studies.

The purpose of this paper is to examine participation in online social platforms consisting of information exchange, social network interactions, and political deliberation. Despite the proven benefits of online participation, the majority of internet users read social media data but do not directly contribute, a phenomenon called lurking.

A survey was administered electronically to 507 participants and consisted of ten sections in a questionnaire to gather data on the relationship between online participation and the following variables: anonymity, social value orientation, motivations, and participation in offline activities, as well as the internet’s political influence and personality traits.

Findings show that users with high levels of participation also identify themselves, report higher levels of extroversion, openness, and activity outside the internet, the motivations being an intermediary variable in the relationship between the variables value.

The study shows that participation in online social platforms is not only related to personality traits, but they are impacted by the nature of the motivations that drive them to participate in the particular social platform, as well as by the interest toward the specific topic, or the type or nature of the social group with whom they are communicating.

The purpose of this paper, the fourth in a series, is to discuss the pros and cons of the h‐index in the Web of Science (WoS).

The paper looks at the content and software advantages and disadvantages of WoS from the perspective of calculating the h‐index as a single measure of published research output and influence at the individual researcher level.

The paper finds that there are notable similarities and differences between WoS and Scopus, and that any WoS edition has a unique and important feature. As opposed to other cited reference enhanced databases, WoS always includes all the cited references for every record created, irrespective of the publication year.

The paper provides insights into the advantages and disadvantages of WoS from the perspective of calculating the h‐index.

This paper aims to provide a general overview, to be followed by a series of papers focusing on the analysis of pros and cons of the three largest, cited‐reference‐enhanced, multidisciplinary databases (Google Scholar, Scopus, and Web of Science) for determining the h‐index.

The paper focuses on the analysis of pros and cons of the three largest, cited‐reference‐enhanced, multidisciplinary databases (Google Scholar, Scopus and Web of Science).

The h‐index, developed by Jorge E. Hirsch to quantify the scientific output of researchers, has immediately received well‐deserved attention in academia. The theoretical part of his idea was widely embraced, and even enhanced, by several researchers. Many of them also recommended derivative metrics based on Hirsch's idea to compensate for potential distortion factors, such as high self‐citation rates. The practical aspects of determining the h‐index also need scrutiny, because some content and software characteristics of reference‐enhanced databases can strongly influence the h‐index values.

The paper focuses on the analysis of pros and cons of the three largest, cited‐reference‐enhanced, multidisciplinary databases.

The purpose of this paper is to shed light on the use of bibliometric indicators as a people analytics tool for examining research performance outcome differences in faculty mobility and turnover.

Employing bibliometric information from research databases, the publication, citations, h-index and newly developed individual annualized h-index (hIa-index) for a sample of university faculty is examined (N = 684). Information relating to turnover decisions from a human resource (HR) information system and bibliometric data from a research database are combined to explore research performance differences across cohorts of retained, resigned or terminated faculty over a five-year period in a single university.

Analysis of variance (ANOVA) results indicate traditional bibliometric indicators of h-index, publication count and citation count which are limited in their ability to identify performance differences between employment status cohorts. Results do show some promise for the newly developed hIa-index, as it is found to be significantly lower for terminated faculty (p < 0.001), as compared to both retained and resigned faculty. Multinomial logistic regression analysis also confirms the hIa metric as a predictor of terminated employment status.

First, the results imply that the hIa-index, which controls for career length and elements of coauthorship is a superior bibliometric indicator for comparison of research performance.

Results suggest that the hIa metric may serve as a useful tool for the examination of employment decisions for universities. It also highlights the potential usefulness of bibliometric indicators for people analytics and the examination of employment decisions, performance management and faculty turnover in research-intensive higher education contexts.

This empirical paper is entirely unique. No research has previously examined the issue of turnover in a university setting using the bibliometric measures employed here. This is a first example of the potential use of hIa bibliometric index as an HR analytics tool for the examination of HR decisions such as employee turnover in the university context.

The rapid growth of social media has changed how people interact and connect with one another while also giving rise to new social-media associated psychological experiences, such as the well-known fear of missing out (FoMO) and the somewhat new phenomena, the joy of missing out (JoMO). This study aims to develop a new scale for measuring JoMO and explore its independent nature and relationships with well-being, social comparison and demographic variables.

A sample of 230 participants filled out an online survey, including questions about demographic details, well-being, social media engagement, social comparison, FoMO and a new JoMO scale. The data was analyzed using exploratory factor analysis, hierarchical regression and structural equation modeling.

The study confirmed the validity and reliability of the new JoMO scale in three sub-categories: active JoMO, passive JoMO and coping with disconnection. Younger individuals and those who were single, with weaker psychological well-being, higher engagement in social media and greater social comparison inclinations tended to experience higher levels of FoMO. Conversely, older individuals, women and those who enjoyed stronger psychological well-being and reduced social media engagement demonstrated higher levels of JoMO. The findings also suggest a complex relationship between FoMO and JoMO.

The creation of an innovative JoMO measurement tool could transform both scholarly research and practical approaches to digital media interactions. This tool offers a deeper understanding of the intricate links between JoMO and factors such as social comparison and FoMO, paving the way for targeted interventions. By utilizing this, experts can foster healthier online behaviors and better psychological health through increased JoMO consciousness, reduced social media engagement and social comparisons, and FoMO management. Therefore, this fresh instrument assists in clarifying and improving how individuals engage with digital technology.

This research validates the JoMO scale, enhancing our understanding of JoMO and its potential effects on well-being, as well as its associations with other variables. In addition, this research provides valuable insights for future studies on social media use and JoMO, and for developing effective strategies for managing healthier online experiences.

This paper seeks to describe and discuss a tagging experiment involving images related to Israeli and Jewish cultural heritage. The aim of this experiment was to compare freely assigned tags with values (free text) assigned to predefined metadata elements.

Two groups of participants were asked to provide tags for 12 images. The first group of participants was asked to assign descriptive tags to the images without guidance (unstructured tagging), while the second group was asked to provide free‐text values to predefined metadata elements (structured tagging).

The results show that on the one hand structured tagging provides guidance to the users, but on the other hand different interpretations of the meaning of the elements may worsen the tagging quality instead of improving it. In addition, unstructured tagging allows for a wider range of tags.

The recommendation is to experiment with a system where the users provide both the tags and the context of these tags.

Unstructured tagging has become highly popular on the web, thus it is important to evaluate its merits and shortcomings compared to more conventional methods.

Seven years after the release of Google Scholar in 2004, it was enhanced by a new module, the Google Scholar Author Citation Tracker (GSACT), currently a small subset of the complete Google Scholar (GS) database. The aim of this paper is to focus on this enhancement.

The paper discusses the Google Scholar Author Citation Tracker, its features, potential benefits and problems.

GSACT allows registered users to create and edit their scientific profiles and some bibliometric indicators, such as the h‐index, total citation counts, and the i10 index. These metrics are provided for the entire academic career of authors and for the most recent five‐year period. The new module also offers some long overdue essential options, such as sorting result lists of the documents by their publication year, title, and the citations received

The paper shows that, at present, GSACT may be too little, too late. However, with an extension of the current clean‐up project it could possibly become a really scholarly resource in the long run.

The purpose of this paper is to discuss the results of recent experiments in determining the h‐index at the country level for the 10 Ibero‐American countries of South America.

The three citation index components (Science Citation Index, Social Science Citation Index, and Arts & Humanities Citation Index) of the Web of Science system of Thomson‐Reuters and the Scopus database of Elsevier are used to gauge the comparability of the h‐indexes reported by the two systems.

The results show that in spite of the significant differences in the content of the two databases in terms of their source base and the extent of cited reference enhancement of records, the rank correlation of the ten countries based on the h‐index values returned by Web of Science and Scopus is very high.

For this sample, in spite of differences between WoS and Scopus in the number of papers from each country, the rank position of the countries by the h‐index is almost the same. There is only a single rank position difference – Scopus rank Argentina second and Chile third, while the order is the reverse in WoS. This reconfirms the robustness of the h‐index at the country level.