This study examines the influence of physical activity on the augmentation of social intelligence among secondary school students in Ain Beida, Ouargla. A total of 128 students from both the Arabic Literature and Natural Sciences streams took part. The Social Intelligence Scale and a Physical Activity Questionnaire were used to gather data. Both of these tools were shown to be very valid and reliable. The findings indicated that the majority of students participated in consistent physical activity and exhibited relatively elevated levels of social intelligence. There was a statistically significant positive association (r = 0.399, p < .001) between physical exercise and social intelligence. This means that kids who played sports, especially team sports, were more likely to learn how to communicate, work together, lead, and feel for others. These results underscore the necessity of including physical education and extracurricular sports into school curricula to facilitate adolescents' social and emotional development, while simultaneously advocating for additional longitudinal and experimental research to enhance comprehension of this relationship.

Character strengths are central constructs in positive psychology, yet empirical evidence from collectivistic cultural contexts remains limited. This study aims to examine the distribution of the 24 character strengths and to compare character strength profiles between male and female university students. The participants consisted of 285 undergraduate students recruited from several private universities in Semarang, Indonesia, using an incidental sampling technique. The research instrument was the 72-item Values in Action Inventory of Strengths (VIA-72) developed by Peterson and Seligman (2004). Validity testing using Corrected Item–Total Correlation indicated that all items met the validity criteria, with correlation coefficients ranging from 0.320 to 0.661. Reliability analysis demonstrated excellent internal consistency, with a Cronbach’s Alpha of 0.966. Data were analyzed using descriptive and comparative statistical methods. Descriptive findings revealed that kindness, teamwork, appreciation of beauty and excellence, gratitude, and fairness were the five highest character strengths across the total sample. Specifically, male students showed the highest scores in teamwork, kindness, fairness, appreciation of beauty and excellence, and humor, whereas female students scored highest in kindness, gratitude, appreciation of beauty and excellence, teamwork, and fairness. Comparative analysis using the Mann–Whitney U test identified statistically significant gender differences in four character strengths – open-mindedness, bravery, social intelligence, and humor – although the observed effect sizes ranged from small to moderate. These findings contribute to a deeper understanding of university students’ character strength profiles within the Indonesian higher education context and offer practical implications for the development of strength-based student interventions and educational programs.

Globalization and accelerated digitalization have reshaped international procurement, shifting supplier evaluation beyond technical criteria toward digital visibility and relational capabilities. This study examines how social media, digital communication, and emotional intelligence (EI) influence supplier selection in Asia, using the Strategic Alignment Model (SAM) as the analytical foundation and extending it through the Digital–Emotional Strategic Alignment (DESA) perspective. A qualitative exploratory case study was conducted through digital document analysis and interviews with procurement practitioners from China, Thailand, and Indonesia. The findings indicate that social media serves as a practical digital strategy tool for early supplier screening by enhancing transparency and reducing uncertainty. The quality of digital communication, reflected in clarity, responsiveness, and communication tone, signals suppliers’ professionalism and digital readiness. EI further strengthens cross-border relationships by fostering empathy, adaptability, and trust in digital interactions where non-verbal cues are limited. Together, these elements reinforce alignment with organizational strategy by supporting risk mitigation, negotiation effectiveness, and relational continuity. The study contributes by extending SAM with two key dimensions for digital global sourcing: social media as an indicator of digital readiness and EI as a driver of relational resilience. The DESA framework enhances theoretical understanding of strategic alignment in supplier selection and offers practical guidance for improving global sourcing effectiveness in the digital era.

Many psychosocial strengths have been studied in the positive psychology and resilience literatures. This presents a challenge for narrowing down the most helpful strengths for resilience, the process of overcoming trauma and adversity to achieve wellbeing. We bring together measures from two common strengths frameworks to see which ones are most closely associated with thriving after adversity. People who visited the values in action (VIA) website to complete the VIA questionnaire were invited to participate in a research study. 6,430 U.S. participants completed the VIA and answered questions on five psychosocial strengths (sense of purpose, psychological endurance, social support, eco-connections, and mindfulness), two types of adversities (interpersonal victimization and institutional betrayal), and three measures of current functioning (subjective wellbeing [SWB], health-related quality of life [HRQOL], and posttraumatic growth). Logistic regression analyses showed that higher levels of sense of purpose, hope, psychological endurance, zest, self-regulation, social support, and gratitude were significantly associated with above-average scores on all three indicators of functioning. Humor, mindfulness, bravery, perspective taking, love, teamwork, curiosity, and humility were associated with at least one positive outcome. Unexpectedly, several strengths were associated with poorer functioning in at least one analysis, including judgment, prudence, perseverance, creativity, appreciation of beauty, spirituality, kindness, teamwork, and social intelligence. In this first national study of institutional betrayal, it had a unique negative impact on SWB and HRQOL, even after accounting for interpersonal polyvictimization. Some strengths are more helpful for overcoming adversity than others. Although there are doubtless other benefits to these psychosocial strengths, some may create unexpected burdens that can hinder resilience. A basic science of healing can help identify the best intervention targets for people who have been exposed to trauma.

This study examines how spiritual intelligence (SI) can serve as a catalyst for ethical, culturally rooted social innovation in social enterprises, an area often overlooked in literature dominated by Western, profit-oriented perspectives. Drawing on an integrative review of 63 peer-reviewed works published between 2014 and 2024, the research weaves together theoretical and contextual insights to develop a conceptual model. SI is presented not simply as another form of intelligence, but as a guiding moral compass grounded in transcendence, setting it apart from emotional and social intelligences that primarily focus on interpersonal dynamics. Through dimensions such as consciousness, purpose, serenity, and transcendence, SI equips entrepreneurs to turn deeply held values into tangible, innovative solutions, with purpose acting as a bridge and cultural context shaping outcomes. Indonesia, with traditions like gotong royong and tri hita karana, emerges as a rich setting to observe this phenomenon in practice. The study offers practical pathways, from short-term pilot initiatives such as community co-design workshops to long-term strategies like embedding SI in entrepreneurial education and adapting evaluation metrics to local cultures. While conceptual in scope and limited to English-language literature, the work lays the groundwork for future empirical research using mixed methods across diverse cultural contexts.

Internalizing symptoms emerge early and can negatively affect engagement and achievement during the primary-school years. At the same time, children's socio-emotional competencies may shape how they appraise and regulate school-related stress. This cross-sectional study tested whether Trait Emotional Intelligence (trait EI) and Social Intelligence (SI) are associated with anxiety and depressive symptoms and academic/behavioral outcomes, and whether these competencies distinguish clinical vs. non-clinical internalizing levels. Participants were 228 Italian primary-school children (8-11 years). Measures included the TEIQue-CSF (trait EI), a child-adapted TSIS (SI: Social Awareness, Social Information Processing, Social Skills), the Anxiety Scale Questionnaire for Children (scholastic anxiety), the Children's Depression Inventory (depression; clinical cut-off = 19), teacher-reported grades (Italian, English, Mathematics), and behavior ratings. Analyses comprised correlations, binomial logistic regressions predicting clinical status, and hierarchical multiple regressions for grades and behavior. Higher trait EI was inversely related to scholastic anxiety and depression and reduced the odds of meeting clinical criteria for both outcomes. SI showed weaker, facet-specific links: Social Information Processing was the most informative SI dimension for Mathematics grades. Trait EI predicted higher language grades (Italian and English), whereas associations with behavior ratings were small or non-significant. Findings highlight trait EI as a school-relevant protective correlate of internalizing symptoms in late childhood, while suggesting that Social Intelligence relates more to academic performance. Implications for brief, classroom-based socio-emotional learning are discussed.

The pervasive use of digital devices among elementary school students has given rise to emerging digital phenomena such as Nomophobia, Phubbing, and Fear of Missing Out (FoMO), which are presumed to influence children’s social intelligence. This study aims to examine the impact of these three variables on the social intelligence of upper-grade students at SDN Kanigaran 1, Probolinggo. Employing a quantitative explanatory causal approach, data were collected through a Likert-scale questionnaire from a purposive sample of 172 students in grades IV to VI. The data were analyzed using multiple linear regression via SPSS version 31. Findings reveal that Nomophobia, Phubbing, and FoMO collectively exert a statistically significant effect on social intelligence. Partially, Phubbing and FoMO showed significant effects, whereas Nomophobia did not. These results suggest that emotional dependency on digital devices does not inherently hinder children’s social intelligence, particularly when external regulation by teachers and parents remains strong. Conversely, Phubbing the tendency to ignore real-life interactions in favor of device use and FoMO, characterized by anxiety over missing digital content, were found to detrimentally affect students’ capacity for social engagement. This study underscores the urgent need for digital literacy education and the early cultivation of social skills to ensure a balanced development between digital interaction and authentic social experience.

In this research, it is aimed to examine the relationship between the leadership orientations and social intelligence levels of sports sciences faculty students and to determine the relationship. Relational scanning model was used in this research. The study group of the research consisted of 482 Sports Sciences Faculty students studying at Muğla Sıtkı Koçman University Faculty of Sports Sciences in the 2023-2024 academic year. The survey part of the research consists of three parts. The first section includes demographic information, the second section includes the Leadership Orientation Scale, and the third section includes the Tromso Social Intelligence Scale. The data was analyzed using the SPSS 25.0 package program. The normality of the data was evaluated by looking at kurtosis and skewness values, and it was determined that the data did not have a normal distribution (George & Malley, 2003). The relationship between the dependent and independent variables was evaluated with the spearman correlation test. Mann Witney U test and Kruskal Wallis H test were applied to analyze descriptive data. In addition, frequency and percentage calculations, reliability coefficient calculations, mean and standard deviation calculations were made. While making the analysis, the analysis was made according to the 95% confidence interval. In the research findings, leadership orientation, age and department variables; A significant difference was detected between social intelligence and gender, age and department variables. As a result, participants leadership orientation with social intelligence levels between in all sub- dimensions and total in points significant and negative relationship detection has been (p

The article explores the relationship between reflexivity and social intelligence as essential factors in personal and professional development. Using psychodiagnostic methods by S. Hall and V.V. Ponomaryova, the study identifies a significant correlation between self-direction, self-management, and social intelligence components such as self-control and motivation. Theoretical analysis based on the views of E. Thorndike and G. Allport highlights that developing reflexivity enhances self-awareness, empathy, and adaptability. The research concludes that strengthening reflexivity supports effective communication and social competence, offering recommendations for educators and psychologists to integrate these skills into learning and development processes.

Vocabulary, a cornerstone of linguistic proficiency, significantly influences cognitive skills, academic success, and career potential. This paper presents effective strategies for vocabulary expansion, including extensive reading, active conversation, digital tools, and memory techniques. Results indicate that systematic vocabulary improvement enhances cognitive abilities, expands job prospects, and drives overall success. The abstract also explores the psychological benefits and the impact of lexical richness on social and emotional intelligence.

The article offers a comprehensive examination of Open Source Intelligence (OSINT) as one of the key instruments for countering information warfare, disinformation campaigns, and hybrid threats in the contemporary digital environment. The relevance of the research stems from the increasing scale of informational influence, the use of social media to manipulate public opinion, and the growing role of digital technologies in modern military-political conflicts. In light of the challenges triggered by the full-scale armed aggression of the Russian Federation against Ukraine, particular attention is devoted to analysing the analytical potential of OSINT in detecting, documenting, and refuting fake narratives, collecting evidence of war crimes, and strengthening the strategic communications of the state. The study classifies the principal branches of OSINT, including geospatial intelligence (GeoINT), social media intelligence (SOCMINT), technical intelligence (TECHINT), and specific elements of human intelligence (HUMINT), which collectively form a multi-layered system of gathering, verifying, and validating data from open sources. The methodological approaches to information analysis and verification algorithms are elucidated, and contemporary tools for automating data collection using artificial intelligence systems – particularly AI-assisted OSINT – are presented as means of significantly enhancing analytical efficiency. At the same time, the article emphasises the legal and ethical dimensions of open-source intelligence, focusing on the protection of personal data and adherence to the principles of legality, proportionality, and data minimisation, in accordance with the requirements of the EU General Data Protection Regulation (GDPR). Both national and international approaches to the legal regulation of OSINT use in law-enforcement and judicial practice are analysed. The scientific novelty of the study lies in the integration of technological, legal, and ethical dimensions of OSINT application as a tool for evidence gathering and countering informational threats. The paper concludes that the development of unified international standards for the collection and verification of OSINT data is essential to ensure their legitimacy in criminal proceedings, enhance state information security, and promote a culture of responsible and ethical use of open data within democratic societies.

This study focused on the correlation between elementary students' emotional intelligence (EI) and interpersonal intelligence (II) and their interaction with peers in Siloreng, Wonosobo. The primary purpose of this study was to explore emotional and interpersonal intelligence as they contribute to the dynamics of peer relationships in school. Applying a quantitative investigation method supported by intervention and non-intervention groups, we surveyed 150 students in primary schools. We tested their EI and II using standardised psychological scales and analysed their peer data to see how they interact with their peers. Correlation and regression analyses also consistently showed that II positively predicts interpersonal intelligence, peer cooperation, empathy, and problem solving. The findings of this study reveal that students who have developed a high awareness of their own emotions and those of others are more able to create meaningful relationships with peers. The findings suggest the potential benefits of including emotion and social intelligence training in enhancing relationships among peers and their well-being. Some of the implications of the findings for educational practice in Siloreng Wonosobo and suggestions for further studies are also given.

In the highly volatile realm of global security, the necessity for leading-edge and effectual border resilience tactics has never been more imperative. This PRISMA 2020 guided systematic literature review (SLR) examines the intersection of artificial intelligence (AI), open-source intelligence (OSINT), and social media intelligence (SOCMINT) for enhancing border protection. Our systematic investigation across major databases (IEEE Xplore, Scopus, SpringerLink, MDPI, ACM) and grey literature sources yielded 3932 initial records and, after screening and eligibility assessment, 73 studies and reports from acknowledged organizations, contributing to the evidence synthesis. Three research questions (RQ1–RQ3) were addressed concerning the following: (a) the effectiveness and application of AI in OSINT/SOCMINT for border protection, its (b) data, technical, and operational limitations, and its (c) ethical, legal, and societal implications (GELSI). Evidence matrices summarize the findings, while narrative syntheses underline and thematically group the extracted insights. Results indicate that AI techniques—fluctuating from machine learning (ML) and natural language processing (NLP) to computer vision and emerging large language models (LLMs)—produce quantifiable improvements in forecasting irregular migration, detecting human trafficking, and supporting multimodal intelligence fusion. However, limitations include misinformation, data bias, adversarial vulnerabilities, governance deficits, and sandbox-to-production gaps. Ethical and societal concerns highlight risks of surveillance overreach, discrimination, and insufficient oversight, among others. To our knowledge, this is the first SLR at this intersection. We conclude that, AI-assisted OSINT/SOCMINT presents transformative potential for border protection requiring, nonetheless, balanced governance, robust validation, and future research on LLM/agentic AI, human–AI teaming, and oversight mechanisms.

The development of social and emotional intelligence (SEI) is increasingly recognized as a key factor in fostering students' holistic development. This article explores pedagogical approaches aimed at enhancing SEI in students, highlighting the role of teachers and educational systems in this process. Through examining various strategies, including collaborative learning, emotional regulation exercises, and social awareness activities, the paper investigates the impact of these methods on students' academic performance, mental well-being, and social interactions. The findings suggest that integrating SEI development into curricula not only improves students’ emotional and social capabilities but also contributes to a more supportive and engaging learning environment.

The rapid deployment of AI reveals persistent socio-technical and data-driven biases that reflect profound epistemic limitations in knowledge production. These biases are not accidental, but symptomatic of deeper epistemic limitations in the way AI knowledge is produced — often by homogeneous teams within technocentric paradigms that exclude alternative perspectives. This paper argues that the underrepresentation of diverse social actors in AI development not only perpetuates inequality, but also severely limits the epistemic and ethical robustness of AI systems. The focus of this paper arises in particular from the preliminary findings obtained in the Horizon Europe project STEP, which highlight the potential of the framework to improve the inclusivity and trustworthiness of AI. The central thesis is that social diversity must be considered as an epistemic condition and not just an ethical or demographic ideal. Drawing on sociology, psychology and educational science, the authors show how integrating plural forms of knowledge, lived experiences and cultural perspectives into the design and development process can lead to AI systems that are more context-sensitive, equitable and trustworthy. Rather than proposing inclusion as an external corrective, this paper discusses a paradigm shift in AI development - a paradigm shift that embeds diversity into the infrastructure of knowledge production itself. The contribution of this paper is twofold. First, it proposes a theoretical model of integrative knowledge production that identifies mechanisms through which interdisciplinary collaboration can challenge dominant epistemologies and promote systemic reflexivity. Second, a participatory design framework is outlined to operationalise this model through concrete methodological tools, including dialogic co-design workshops, ethnographic participation in data selection and cross-functional team structuring. These practises aim to break through technocratic compartmentalisation by creating space for social critique and situated intelligence within AI development cycles. Finally, the authors reflect on the transformative potential of this approach and suggest that rethinking who is involved in AI knowledge production will not only change the outcomes of AI systems, but also the normative foundations of the technological future. From this perspective, ethical AI is not just explainable or compliant — it is structurally inclusive, responsive to different lifeworlds and open to critical reinvention.

The integration of Artificial Intelligence (AI) into early childhood education presents new opportunities and challenges in fostering cognitive, social, and emotional development. This theoretical discussion synthesizes recent research on AI’s role in personalized learning, educational robotics, gamified learning, and social-emotional development. The study explores theoretical frameworks such as Vygotsky’s Sociocultural Theory, Distributed Cognition, and the Five Big Ideas Framework to understand AI’s impact on young learners. AI-powered personalized learning platforms enhance engagement and adaptability, while robotics and gamification foster problem-solving and collaboration. Additionally, AI tools support children with disabilities, promoting inclusivity and accessibility. However, ethical concerns related to privacy, bias, and teacher preparedness pose challenges to effective AI integration. Furthermore, the long-term effects of AI on children’s social skills and emotional intelligence require further investigation. This theoretical discussion emphasizes the need for interdisciplinary collaboration to develop AI-driven educational strategies that prioritize developmental appropriateness, equity, and ethical considerations. The findings highlight AI’s potential as a transformative educational tool, provided it is implemented thoughtfully and responsibly. The paper aims to address the following research question: How can artificial intelligence (AI) be meaningfully and ethically integrated into early childhood education to enhance learning, while preserving developmental and relational values?

Does AI represent authentic intelligence, or an artificial identity? What if <em>intelligence</em> were replaced with <em>identity</em>—how would the implications change? At stake is the meaning of <em>artificial</em> itself, but most importantly, the focus here is the question: <em>What constitutes authentic identity? </em>If the objective of AI is, at least in part, to replicate human beings, then we must first ask: <em>Who are we?</em> Must this not be established before replication is possible? Even if we believe we know, how do we verify such knowledge? The Authentic Systems identity probe answers this question and further exemplifies a method that might challenge AI–s ability to replicate us. Our Universe, our context, may not be as it seems. It may range from cold and indifferent to nurturing, from infernal to heavenly—or it may not be material at all. The universe could be fundamentally abstract, perhaps even mathematical in nature. This realization destabilizes many assumptions about reality itself. Such questions return us to philosophy, recalling those “naïve” yet enduring inquiries posed by beginning students: <em>Who are we? Why are we here?</em> These questions, once smiled at, now bear urgent weight. Geoffrey Hinton, often described as the “godfather of AI,” has warned that the very systems he helped pioneer may become instruments of humanity–s self-extinction. What was once a classroom provocation has become a pressing global concern. This presentation will explore the notion of authentic identity in this context, framed also by recent discourse such as the viral video <em>“Michio Kaku”s Terrifying Warning: Quantum AI Just Made a Godlike Discovery.”</em> While the video falsely attributes such a warning to Kaku, it nevertheless articulates disturbing possibilities that resonate with ongoing research into consciousness, identity, and the future of humanity. We may ultimately be very different from who we think we are. Methodological note – My role here is as a philosopher and working in its subset, logic. Having a full technical knowledge would be ideal, but I do not claim to have such. However, what a logician can do is arrange various peer-reviewed assertions within a philosophical framework (here,authentic human identity) and draw the appropriate conclusion as to what I think our destiny very well may be. My 2023 book, <em>Managing Complexity Through Social Intelligence</em> provides the larger context for what follows.

BackgroundWisdom is an integrated cognitive and socioemotional capacity underlying everyday decision‐making. A time‐honored construct, wisdom represents superior mental functioning that may or may not be related to age, education, intelligence quotient (IQ), or brain pathologic burden in preclinical Alzheimer's disease (AD). Leveraging an ongoing cohort study of cognition and aging, we measured wisdom and its subdomains (decisiveness, emotional regulation, self‐reflection, pro‐social behavior, social advising, tolerance for divergent values, spirituality) to determine its association with demographic and clinical variables and AD neuroimaging biomarkers in preclinical AD.MethodOne‐hundred and six cognitively unimpaired (CU) older adults from the Harvard Aging Brain Study underwent assessments of self‐reported wisdom (SD‐Wise Scale), IQ (American National Adult Reading Test–Verbal), subjective and objective cognition (Cognitive Functioning Index‐Self [CFI]; Preclinical Alzheimer's Cognitive Composite [PACC]), and depression (Geriatric Depression Scale [GDS]). PiB‐PET measures of cortical Aβ were available for eighty‐three participants. Unadjusted associations between wisdom and other variables were evaluated using Pearson correlations. Separate, cross‐sectional linear models with backwards elimination estimated the associations of wisdom with each of the main predictors (PiB‐PET, CFI, or PACC). Age, sex, years of education, IQ, socioeconomic status, and GDS were included in the initial pool of predictors for each model.ResultTable 1 presents sample characteristics. Greater wisdom was correlated with female sex (t[df]=3.8[101.8], p <0.001) and lower GDS scores (r = ‐0.4, p <0.001), but not with age, socioeconomic status, years of education, or IQ. In the final linear model, greater total wisdom was associated with lower PiB‐SUVr (β=‐3.51, p= 0.017, R2 = 0.28; Figure 1), female sex, and lower GDS. In analogous models, neither CFI nor PACC was associated with wisdom. In secondary models, higher PiB‐PET was associated with lower decisiveness, self‐reflection, and social advising domains of wisdom, while higher GDS was associated with lower decisiveness, emotional regulation, pro‐social behavior, and spirituality.ConclusionWisdom, a traditional, higher‐order construct of mental functioning, was not related to education, IQ, or subjective or objective cognition in this sample of CU older adults. Wisdom encompasses qualities of decisiveness, self‐reflection and social intelligence that may be sensitive to Aβ pathologic burden and could be a measurable, unrecognized sign of preclinical AD.

Purpose: The coronavirus disease 2019 pandemic has led to significant societal changes such as a rapid shift toward online learning, including college classes moving to virtual platforms. This study investigated the relationship between face-to-face communication time, digital burnout, social intelligence, and loneliness among college students during the pandemic.Methods: This descriptive correlation study was conducted with 172 college students who participated in an online survey from July 1 to July 9, 2022. Face-to-face communication time, digital burnout, social intelligence, and loneliness were measured. Descriptive statistics, independent t-test, one-way ANOVA, Pearson’s correlation, and regression analysis were used to analyze the collected data.Results: Digital burnout (β= -.21, &lt;i&gt;p&lt;/i&gt;=.011) and loneliness (β= -.46, &lt;i&gt;p&lt;/i&gt;&lt;.001) were significantly associated with social intelligence (F=15.04, &lt;i&gt;p&lt;/i&gt;&lt;.001), whereas face-to-face communication time did not show a significant association with social intelligence (β= -.01, &lt;i&gt;p&lt;/i&gt;=.922). Digital burnout (β=.41, &lt;i&gt;p&lt;/i&gt;&lt;.001) and social intelligence (β= -.33, &lt;i&gt;p&lt;/i&gt;&lt;.001) were significantly associated with loneliness (F=18.34, &lt;i&gt;p&lt;/i&gt;&lt;.001); however, face-to-face communication was not significantly associated with loneliness (β= -.06, &lt;i&gt;p&lt;/i&gt;=.314).Conclusion: These findings suggest that digital burnout is significantly associated with both social intelligence and loneliness. This study emphasizes the need for interventions to address digital burnout and promote healthy online habits to improve the social well-being of college students.

Considering the global change towards renewable energy, the necessity to form an understanding of what the people think, believe, and debate regarding sustainable technologies is increasing. The analysis uses social intelligence and web mining to find meaning in masses of unstructured renewable energy information online. Based on 12 months of social media, forums, and news websites data, the study utilizes superior natural language processing and machine learning frameworks to estimate sentiment, determine the most prevalent themes, and predict the adoption patterns per region. It was discovered that overall feeling was (largely) positive particularly about European and North American stakeholders. The data association of ESE using the topic model shows that economic benefit and technological advances are the most prevalent subjects of renewable energy subfields. A multivariate regression equation is constructed that will relate the digital sentiment and thematic emphasis to predicted adoption rates and the model is estimated with real life regional data. Findings indicate that the organization of the public discourse is considerably linked to the readiness and engagement at the regional level, which highlights the effectiveness of digital cues to predict energy demand. The article presents a methodology that can not only gauge the online opinion, but also transform it into policy-level insights that can be used by policymakers and industry stakeholders in the energy sector. In this interdisciplinary focus, sociotechnical analysis is given importance besides the renewable energy planning and communication. The weaknesses in terms of linguistic diversity and transferability of models are identified and recommendations of future studies on how the methodological approach can be further enhanced are provided.