Countering cyber extremism is a crucial challenge in the digital age. Social media algorithms, if designed and used properly, have the potential to be a powerful tool in this fight, development of technological solutions that can make social networks a safer and healthier space for all users. this study mainly aims to provide a comprehensive view of the role played by the algorithms of social networking sites in countering electronic extremism, and clarifying the expected ease of use by programmers in limiting the dissemination of extremist data. Additionally, to analyzing the intended benefit in controlling and organizing digital content for users from all societal groups. Through the systematic review tool, a variety of previous literature related to the applications of algorithms in the field of online radicalization reduction was evaluated. Algorithms use machine learning and analysis of text and images to detect content that may be harmful, hateful, or call for violence. Posts, comments, photos and videos are analyzed to detect any signs of extremism. Algorithms also contribute to enhancing content that promotes positive values, tolerance and understanding between individuals, which reduces the impact of extremist content. Algorithms are also constantly updated to be able to discover new methods used by extremists to spread their ideas and avoid detection. The results indicate that it is possible to make the most of these algorithms and use them to enhance electronic security and reduce digital threats.

The study is focusing on cyberspace—a new type of space mastered by humans with the help of digital technologies. This systematic review uses SPAR-4-SLR protocol to analyze over 30 years of scholarly research indexed in Scopus database, highlighting five time periods: before 1995, 1996–2008, 2009–2012, 2013–2019, and after 2020. A final sample of 6645 publications in social sciences, Business, management and accounting (BMA), and Economics, econometrics and finance (EEF) was analyzed across multiple parameters, including: chronology, types of documents, sources, countries, institutions, authors, topics, and most cited publications. The review has systematized information about the most influential organizations and individuals involved in cyberspace research. First of all, these are researchers from the United States, the United Kingdom, and China. Key journals that publish research on the topic have been identified, and a ranked list of funding organizations supporting research on the social and economic aspects of cyberspace are identified. The study provides insights into the achievements of the social and economic sciences in cyberspace over the past 30 years. The results will be useful to scholars who seek for a general overview on the topic of cyberspace, as well as experts and policymakers developing mechanisms and tools for regulating cyberspace as a mixture of the virtual and real worlds.

This paper tries to understand economic, social and legal implications of the introduction and usage of MediSearch (AI search engine) in the Indian healthcare context. Discussing the economic ramifications, the paper highlights the potential for cost savings, the influence on healthcare accessibility, and the shifts in traditional medical paradigms. On the social side, the study explains ability of AI based platforms to bridge healthcare disparities, with a potential for enhancing general health literacy among the general population. From a legal standpoint, study highlights the concerns related to data privacy, regulatory issues, and possible malpractice implications. With the integration of these perspectives, the study also explains opportunities, challenges and future of MediSearch from the Indian health perspective.

The rapid advancement of artificial intelligence (AI) technology is profoundly transforming the information ecosystem, reshaping the ways in which information is produced, distributed, and consumed. This study explores the impact of AI on the information environment, examining the challenges and opportunities for sustainable development in the age of AI. The research is motivated by the need to address the growing concerns about the reliability and sustainability of the information ecosystem in the face of AI-driven changes. Through a comprehensive analysis of the current AI landscape, including a review of existing literature and case studies, the study diagnoses the social implications of AI-driven changes in information ecosystems. The findings reveal a complex interplay between technological innovation and social responsibility, highlighting the need for collaborative governance strategies to navigate the tensions between the benefits and risks of AI. The study contributes to the growing discourse on AI governance by proposing a multi-stakeholder framework that emphasizes the importance of inclusive participation, transparency, and accountability in shaping the future of information. The research offers actionable insights for policymakers, industry leaders, and civil society organizations seeking to foster a trustworthy and inclusive information environment in the era of AI, while harnessing the potential of AI-driven innovations for sustainable development.

Professional judgments in business valuation should be based on persuasive comparative data and conclusive empirical studies. However, these judgments are frequently made without these conditions, causing professional skepticism. An appraiser should explain in detail what was done to get the market value because valuation is the initial crucial step in the investment decision process. In socially responsible investment schemes, an appraiser has a fiduciary duty and a vital role in protecting the public from fraud and the risk of asset value destruction. Professional skepticism is essential to direct the appraiser’s judgment towards independent valuation for the public interest, assisting in evaluating the relevance and reliability of information, especially relating to social, environmental, and ethical issues. This paper studies the business valuation process from a behavioral finance perspective in the United States and Indonesia, aiming to tweak business valuation practices, identify biases, and mitigate them to ensure the market value does not shift far from fairness opinion. The case study explores experiences from the professional role-learning process. The results highlight the need for an appraisal protocol in business valuation, improvements in the discount for lack of marketability application, and these findings are pertinent to business appraisers and regulators. Recommendations include enhancing the clarity of professional judgments and the integration of recent empirical studies into practice.