Jorge Cruz-Cárdenas

Since X-Twitter suppressed public access to engagement metrics in February 2023, classical models for detecting coordinated operations lost viability. Astroturfing is one modality among several, alongside narrative saturation and targeted amplification, requiring frameworks that use the structural and behavioral signals still available. This article proposes the Digital Polarization Index (DPI; in Spanish, Índice de Polarización Digital), a six-stage operational framework classifying each unique account into four categories (Trolls, Activists, Public opinion, Neutral), reporting four inauthenticity dimensions (D1–D4) and assigning typological labels with scale and intensity qualifiers. The framework applies to political conversation directed at an identifiable actor that has reached trending status on X. Validation covers ten political cases in Ecuador, the Dominican Republic and Mexico (28,007 accounts; 56,623 mentions), with two external contrasts: Botometer-Lite, kappa = 0.368, and Platform Sentiment, kappa = −0.015, the latter supporting a Stance variable directional toward the target actor. The three modalities are differentially activated, though not separable beyond chance. Stance agreement with independent human annotation reaches kappa = 0.411 against kappa = 0.752 between annotators. Four prespecified non-political trending corpora fall outside that scope and receive at least one operational label in three of four, bounding the attribution the framework supports.

Today, there is a growing anxiety about artificial intelligence in the educational space, which greatly affects the willingness to make technological decisions and plan for one’s professional future. In empirical studies, AI anxiety is defined as a complex phenomenon including a range of negative emotional responses that shapes in people due to development and potential impact of artificial intelligence on various spheres of life. Given the impact of AI anxiety on learning, career choices, participation in the digital economy, and mental well-being, there is a need for its holistic conceptual description and reliable diagnosis. The aim of the study is to present a reliable and valid Russian-language tool for diagnosing AI anxiety in students. The adopted basis and modified for a student sample (N = 521) “Artificial Intelligence Anxiety Scale” (M.H. Alkhaibani et al.) showed an acceptable level of the external and internal validity as well as reliability on internal consistency. The factor analysis confirmed the five-factor structure of the questionnaire: concerns related to AI accuracy and reliability; concerns related to academic integrity (plagiarism); and concerns stemming from regulatory uncertainty (guidelines), fears of loss of learning and cognitive skills, as well as a decrease in motivation. External validity is confirmed by the correlations with neuroticism and conscientiousness as personality traits, image of the future, attitude towards artificial intelligence, and some socio-demographic characteristics. Adapted and modified psychodiagnostic tool for studying AI anxiety opens up opportunities for research on a Russian-speaking student sample.

El presente estudio se centra en el análisis del clima organizacional en el sector panadero de Ambato, Ecuador, buscando diagnosticar la dinámica laboral y proponer un modelo de gestión optimizado. Utiliza un método cuantitativo y un estudio censal, con 110 colaboradores, para evaluar las dimensiones críticas de la comunicación, el liderazgo, el trabajo en equipo y las condiciones de trabajo. Los resultados indican una percepción "neutral" común, aunque las condiciones físicas y los niveles aceptables de compromiso presentan debilidades estructurales en la gestión del talento. El factor más importante es el liderazgo, que es un factor muy heterogéneo porque no existe un estilo de gestión uniforme que aporte estabilidad al entorno laboral. Además, hay una gran división generacional con los niveles más bajos de satisfacción entre los trabajadores más jóvenes. Se concluye que la variación en la percepción del clima organizacional está intrínsecamente ligada a la falta de competencias gerenciales y la ausencia de estrategias de fidelización segmentadas.

Purpose: This study undertook a systematic literature review of consumers’ information and knowledge sharing (I&KS) in digital scenarios, as it is an expanding thematic area that differs from other consumer behavior and has been underexplored. Design/methodology/approach: Following the PRISMA philosophy, we identified I&KS-related studies in the Scopus database based on a search term chain determined through an exploratory study. Additional inclusion and exclusion criteria were applied, and studies were manually filtered. An input–process–output type model was used to manually review and systematize the literature. Then, a second content analysis was conducted using artificial intelligence (AI) tools. Findings: Based on 51 relevant articles, this study characterized the I&KS research field as multidisciplinary through quantitative methods. Based on an input–process–output consumer behavior model and content analysis, this study systematized existing knowledge and revealed that most knowledge encompassed the influence of personal and psychological consumer characteristics. Additionally, based on AI tools applied to the full texts of the relevant articles, five thematic clusters emerged, largely coinciding with the input–process–output model used. Finally, future research avenues and recommendations for business and organizational practices were identified. Originality/value: This study fills the gap in consumer studies by systematically reviewing I&KS, a developing field, as no prior research has addressed this topic systematically.