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This study explores the motivations for sharing personal information and self-disclosure by mentally ill people in public and private Facebook groups. The purpose of the self-disclosure comparison between public and private groups is to understand how mentally ill people use different kinds of online communication channels in order to advance their goals and needs concerning their illness.

The study was carried out using questionnaires distributed in Facebook groups for people with mental illnesses. A total of 123 full and valid questionnaires were received. Statistical analysis was performed on the data.

Findings revealed that there are no significant differences between public and private groups concerning motivations for self-disclosure and that both types of groups create a safe and supportive place for mentally ill people. However, findings suggest that participants in public groups tend to display higher social involvement than those who participate in private groups.

This is a path breaking study on the entire subject of discourse of people with mental illnesses in private Facebook groups and its importance is derived from this. The study clarified and emphasized the importance of the sense of belonging to a community. Moreover, findings encourage people with mental illnesses to make use of social media channels to meet their social and personal needs.

People with pre-existing mental health conditions are more likely to be affected by global crises. The Covid-19 pandemic has presented them with unique challenges, including reduced contact with the psychiatric rehabilitation and support systems. Thus, understanding the emotional experience of this population may assist mental health organizations in future global crises.

In this paper, researchers analyzed the discourse of the mentally ill during the Covid-19 pandemic, as reflected in Israeli Facebook groups: three private groups and one public group. Researchers explored the language, reactions, emotions and sentiments used in these groups during the year before the pandemic, outbreak periods and remission periods, as well as the period before the vaccine’s introduction and after its appearance.

Analyzing groups’ discourse using the collective emotion theory suggests that the group that expressed the most significant difficulty was the Depression group, while individuals who suffer from social phobia/anxiety and PTSD were less affected during the lockdowns and restrictions forced by the outbreak.

Findings may serve as a tool for service providers during crises to monitor patients’ conditions, and assist individuals who need support and help.

Exploring the considerations that guide and influence members of Facebook medical support groups to disclose private information.

The sample included 293 participants, aged 18–85 years, who answered an online survey, 155 members of Facebook medical support groups and 138 members of other Facebook groups.

Members of medical support groups attach greater importance to privacy policy, give greater value to privacy and reveal more private information, compared to members of other groups. Members of medical support groups tend to feel that they receive more support and feel that the privacy policy preserves their privacy much more. These feelings are associated with greater self-disclosure of groups' members.

The research insights will help medical support groups' members and admins to put into action the fundamental right to privacy and build a set of rules tailored to their individual and group needs.

The aim of this study is to examine the information needs and information seeking behaviors of Israeli citizens during the outbreak of the coronavirus disease (COVID-19) in 2020, with an emphasis on the dissemination of digital information by government agencies.

The research approach underlying this investigation is of the “case study” type, employing semi-structured, in-depth interviews conducted with 24 Israeli citizens regarding their perceptions and experiences with government information and government services during the first months of the coronavirus.

The findings of this study reveal that most participants indicated feelings of media fatigue as a result of increased exposure to news media and social media, to the point of experiencing information overload. Second, participants described feeling a lack of clear information and poor access to accurate health and official information at the outset of the COVID-19 crisis in Israel. Third, participants in the authors’ study noted that most of the information to which they were exposed about the virus came to them through communal connections such as friends and family, via social media and messaging apps like WhatsApp. In general, the participants expressed satisfaction with the quality and availability of the data and extensive information of government ministries on social networks, together with a lack of satisfaction due to difficulties in usage and a lack of clear information on traditional government websites.

The findings present the information acquisition and the experience of citizens in situations of national emergencies and crises, in a new light, through a focus on the dissemination of government, health and news information.

The current study examined Israeli researchers from various disciplines concerning their perceptions, attitudes and awareness of scientific publications in open access (OA) journals and repositories.

A survey instrument was developed and distributed to 202 Israeli researchers from universities, colleges and research institutions. The study used the united theory of acceptance and use of technology (UTAUT) model as a tool for mapping the factors known to influence researchers to publish in OA journals and repositories.

The empirical model confirmed the mediating effect of the association between researchers’ perceptions and the actual publishing in OA, through their behavioral intentions (BI). Furthermore, the BI are mediated by researchers’ self-decision to publish in OA. More specifically, a researcher's publication level in OA depended not only on the positive attitudes (Atti), performance expectancy (PE) and social influence (SI) mediated by BI, but also on conditions that support researchers who publish in OA, and disciplinary affiliation to science, technology, engineering and math (STEM) which lead the researcher to voluntarily publish in both green and gold OA.

This study contributed to the cumulative understanding of OA publishing by formulating and validating an empirical research model of acceptance and use.

The implications of the findings for scientific publication theory and practices are discussed.

The study suggests an effective framework to understand the researcher's final decision to publish in OA. This study's results are an essential step towards the cumulative understanding of OA publicity adoption and use by researchers as a global issue in general and in Israeli academic institutions in particular.

This research conducts bibliometric analyses and network mapping on smart libraries worldwide. It examines publication profiles, identifies the most cited publications and preferred sources and considers the cooperation of the authors, organizations and countries worldwide. The research also highlights keyword trends and clusters and finds new developments and emerging trends from the co-cited references network.

A total of 264 records with 1,200 citations were extracted from the Web of Science database from 2003 to 2021. The trends in the smart library were analyzed and visualized using BibExcel, VOSviewer, Biblioshiny and CiteSpace.

The People’s Republic of China had the most publications (119), the most citations (374), the highest H-index (12) and the highest total link strength (TLS = 25). Wuhan University had the highest H-index (6). Chiu, Dickson K. W. (H-index = 4, TLS = 22) and Lo, Patrick (H-index = 4, TLS = 21) from the University of Hong Kong had the highest H-indices and were the most cooperative authors. Library Hi Tech was the most preferred journal. “Mobile library” was the most frequently used keyword. “Mobile context” was the largest cluster on the research front.

This study helps librarians, scientists and funders understand smart library trends.

There are several studies and solid background research on smart libraries. However, to the best of the author’s knowledge, this study is the first to conduct bibliometric analyses and network mapping on smart libraries around the globe.

Exact solution of time–cost trade-off problem (TCTP) by the state-of-the-art meta-heuristic algorithms can be obtained for small- and medium-scale problems, while satisfactory results cannot be obtained for large construction projects. In this study, a hybrid heuristic meta-heuristic algorithm that adapts the search domain is developed to solve the large-scale discrete TCTP more efficiently.

Minimum cost slope–based heuristic network analysis algorithm (NAA), which eliminates the unfeasible search domain, is embedded into differential evolution meta-heuristic algorithm. Heuristic NAA narrows the search domain at the initial phase of the optimization. Moreover, activities with float durations higher than the predetermined threshold value are eliminated and then the meta-heuristic algorithm starts and searches the global optimum through the narrowed search space. However, narrowing the search space may increase the probability of obtaining a local optimum. Therefore, adaptive search domain approach is employed to make reintroduction of the eliminated activities to the design variable set possible, which reduces the possibility of converging into local minima.

The developed algorithm is compared with plain meta-heuristic algorithm with two separate analyses. In the first analysis, both algorithms have the same computational demand, and in the latter analysis, the meta-heuristic algorithm has fivefold computational demand. The tests on case study problems reveal that the developed algorithm presents lower total project costs according to the dependent t-test for paired samples with α = 0.0005.

In this study, TCTP is solved without considering quality or restrictions on the resources.

The proposed method enables to adapt the number of parameters, that is, the search domain and provides the opportunity of obtaining significant improvements on the meta-heuristic algorithms for other engineering optimization problems, which is the theoretical contribution of this study. The proposed approach reduces the total construction cost of the large-scale projects, which can be the practical benefit of this study.