Pub Date : 2025-07-23DOI: 10.1016/j.teler.2025.100232
C.A. Piña-García
This study explores the application of Large Language Models (LLMs) for detecting political propaganda on Twitter, focusing on manipulative political narratives during the 2018 Mexican presidential election. Using LLaMA 3.2, we implement a few-shot prompting within an In-Context Learning framework to classify tweets as propagandist or non-propagandist. Using a dataset of over 800,000 tweets mentioning the leading candidate, our model identifies linguistic patterns, sentiment dynamics, and adversarial tactics, including emotive language, personal attacks, and the strategic use of hashtags. Results indicate that 58.4 % of the analyzed tweets exhibited propagandist characteristics, with a predominance of negative sentiment and aggressive tone, indicating a significant presence of information manipulation and polarization. Hierarchical clustering and word frequency analyses reveal coordinated messaging patterns, reinforcing the role of social media as a tool for political discourse manipulation. Our findings demonstrate the performance of LLMs in automating misleading communication detection and provide a replicable AI-driven framework for analyzing manipulative political narratives in digital environments.
{"title":"In-context learning for propaganda detection on Twitter Mexico using large language model meta AI","authors":"C.A. Piña-García","doi":"10.1016/j.teler.2025.100232","DOIUrl":"10.1016/j.teler.2025.100232","url":null,"abstract":"<div><div>This study explores the application of Large Language Models (LLMs) for detecting political propaganda on Twitter, focusing on manipulative political narratives during the 2018 Mexican presidential election. Using LLaMA 3.2, we implement a few-shot prompting within an In-Context Learning framework to classify tweets as propagandist or non-propagandist. Using a dataset of over 800,000 tweets mentioning the leading candidate, our model identifies linguistic patterns, sentiment dynamics, and adversarial tactics, including emotive language, personal attacks, and the strategic use of hashtags. Results indicate that 58.4 % of the analyzed tweets exhibited propagandist characteristics, with a predominance of negative sentiment and aggressive tone, indicating a significant presence of information manipulation and polarization. Hierarchical clustering and word frequency analyses reveal coordinated messaging patterns, reinforcing the role of social media as a tool for political discourse manipulation. Our findings demonstrate the performance of LLMs in automating misleading communication detection and provide a replicable AI-driven framework for analyzing manipulative political narratives in digital environments.</div></div>","PeriodicalId":101213,"journal":{"name":"Telematics and Informatics Reports","volume":"19 ","pages":"Article 100232"},"PeriodicalIF":4.7,"publicationDate":"2025-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144723158","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-22DOI: 10.1016/j.teler.2025.100216
Humayyun Bashir, Rongting Zhou
The study explores using an AI-driven learning tool, particularly ChatGPT, to assist employees enrolled in distance learning and weekend programs. As AI tools have been embedded in education, limited research has explored their effectiveness in non-traditional educational settings. Despite the advancement of AI-driven technologies in education, few studies have been conducted on their efficacy in non-traditional educational environments. This study investigates how employees who face mental load due to balancing work and Study utilise ChatGPT to complete academic tasks. Data was gathered from 302 employees participating in various programs at universities in Pakistan, using a quantitative study design. The study revealed that employees facing a significant mental load from work-related tasks are more likely to use ChatGPT as an assistive tool for academic assignments. The findings also demonstrate that positive assessments of ChatGPT's benefits promote behavioral intention and actual usage, highlighting its potential to enhance work-study balance. The study revealed findings with significant consequences for educational institutions and policymakers. Integrating AI tools like ChatGPT into effective educational programs helps address the specific requirements of employees. The study also provides suggestions for optimal technology use and enhances the current knowledge on the pedagogical consequences of artificial intelligence tools in adaptable education environments.
{"title":"Mental load, ChatGPT, and work-study balance: A TAM-based study of AI adoption by employees in non-traditional education","authors":"Humayyun Bashir, Rongting Zhou","doi":"10.1016/j.teler.2025.100216","DOIUrl":"10.1016/j.teler.2025.100216","url":null,"abstract":"<div><div>The study explores using an AI-driven learning tool, particularly ChatGPT, to assist employees enrolled in distance learning and weekend programs. As AI tools have been embedded in education, limited research has explored their effectiveness in non-traditional educational settings. Despite the advancement of AI-driven technologies in education, few studies have been conducted on their efficacy in non-traditional educational environments. This study investigates how employees who face mental load due to balancing work and Study utilise ChatGPT to complete academic tasks. Data was gathered from 302 employees participating in various programs at universities in Pakistan, using a quantitative study design. The study revealed that employees facing a significant mental load from work-related tasks are more likely to use ChatGPT as an assistive tool for academic assignments. The findings also demonstrate that positive assessments of ChatGPT's benefits promote behavioral intention and actual usage, highlighting its potential to enhance work-study balance. The study revealed findings with significant consequences for educational institutions and policymakers. Integrating AI tools like ChatGPT into effective educational programs helps address the specific requirements of employees. The study also provides suggestions for optimal technology use and enhances the current knowledge on the pedagogical consequences of artificial intelligence tools in adaptable education environments.</div></div>","PeriodicalId":101213,"journal":{"name":"Telematics and Informatics Reports","volume":"19 ","pages":"Article 100216"},"PeriodicalIF":0.0,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144679849","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-11DOI: 10.1016/j.teler.2025.100231
Abdelbasset Azzouz , Rachid Bouhmidi , Mohammed Chetioui , Redouane Berber , Ahmed J.A. Al-Gburi
In recent years, substantial research efforts have focused on Sierpinski fractal antennas, both in their conventional form and through hybridizations with other antenna types, as well as various modifications. However, an unexplored area of investigation remains: the application of an inverted Sierpinski fractal structure within a crossed bowtie antenna design. This article presents the design, fabrication, and measurement of a third iteration of an inverted crossed bowtie-shaped Sierpinski fractal antenna suitable for wireless multiband communication systems. The design procedure utilized a scripting technique (*.py) provided by the HFSS software due to the antenna’s complex geometry. Additionally, manually designing antennas with complex geometries, such as fractal antennas, can be time-consuming. Optimization procedures, along with a comparative study, were conducted, revealing that the proposed antenna offers more frequency bands and better impedance matching. The proposed antenna is constructed using dielectric material FR4 glass epoxy with a thickness of 1.6 mm, relative permittivity of 4.4, and a loss tangent of 0.025. The proposed antenna resonates at frequencies of 0.73, 2.75, 3.53, 5.22, and 5.64 GHz, covering various applications, including television broadcasting, satellite communication, radar systems (such as weather and air traffic control radar), long-range communication systems, wireless broadband services, and wireless networking (Wi-Fi). The simulation and experimental measurement results are in good agreement, validating the effectiveness of the antenna design for these applications.
{"title":"Performance optimization of crossed bowties of inverted Sierpinski fractal antenna for multiband wireless communication applications","authors":"Abdelbasset Azzouz , Rachid Bouhmidi , Mohammed Chetioui , Redouane Berber , Ahmed J.A. Al-Gburi","doi":"10.1016/j.teler.2025.100231","DOIUrl":"10.1016/j.teler.2025.100231","url":null,"abstract":"<div><div>In recent years, substantial research efforts have focused on Sierpinski fractal antennas, both in their conventional form and through hybridizations with other antenna types, as well as various modifications. However, an unexplored area of investigation remains: the application of an inverted Sierpinski fractal structure within a crossed bowtie antenna design. This article presents the design, fabrication, and measurement of a third iteration of an inverted crossed bowtie-shaped Sierpinski fractal antenna suitable for wireless multiband communication systems. The design procedure utilized a scripting technique (*.py) provided by the HFSS software due to the antenna’s complex geometry. Additionally, manually designing antennas with complex geometries, such as fractal antennas, can be time-consuming. Optimization procedures, along with a comparative study, were conducted, revealing that the proposed antenna offers more frequency bands and better impedance matching. The proposed antenna is constructed using dielectric material FR4 glass epoxy with a thickness of 1.6 mm, relative permittivity of 4.4, and a loss tangent of 0.025. The proposed antenna resonates at frequencies of 0.73, 2.75, 3.53, 5.22, and 5.64 GHz, covering various applications, including television broadcasting, satellite communication, radar systems (such as weather and air traffic control radar), long-range communication systems, wireless broadband services, and wireless networking (Wi-Fi). The simulation and experimental measurement results are in good agreement, validating the effectiveness of the antenna design for these applications.</div></div>","PeriodicalId":101213,"journal":{"name":"Telematics and Informatics Reports","volume":"19 ","pages":"Article 100231"},"PeriodicalIF":0.0,"publicationDate":"2025-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144633324","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-09DOI: 10.1016/j.teler.2025.100230
Marie C. Lee , Denise Breckon
The purpose of this study was to establish a new dimensional framework of factors that influence customer engagement in AI marketing. This study employed a mixed-method approach, conducting semi-structured interviews and collecting 448 fully structured surveys from consumers located in the United States. Partial least squares structural equation modeling (PLS-SEM) was employed to examine the relationships among the variables. Primary data analysis was conducted using IBM SPSS and SmartPLS software. The findings suggest that the personalized, effective, enjoyable, reliable, and simple-to-use (PEERS) factors of an AI marketing device significantly affect customer engagement. This study develops the PEERS model that helps marketers create effective AI marketing strategies in a dynamic business environment.
{"title":"Factors affecting customer engagement in AI marketing","authors":"Marie C. Lee , Denise Breckon","doi":"10.1016/j.teler.2025.100230","DOIUrl":"10.1016/j.teler.2025.100230","url":null,"abstract":"<div><div>The purpose of this study was to establish a new dimensional framework of factors that influence customer engagement in AI marketing. This study employed a mixed-method approach, conducting semi-structured interviews and collecting 448 fully structured surveys from consumers located in the United States. Partial least squares structural equation modeling (PLS-SEM) was employed to examine the relationships among the variables. Primary data analysis was conducted using IBM SPSS and SmartPLS software. The findings suggest that the personalized, effective, enjoyable, reliable, and simple-to-use (PEERS) factors of an AI marketing device significantly affect customer engagement. This study develops the PEERS model that helps marketers create effective AI marketing strategies in a dynamic business environment.</div></div>","PeriodicalId":101213,"journal":{"name":"Telematics and Informatics Reports","volume":"19 ","pages":"Article 100230"},"PeriodicalIF":0.0,"publicationDate":"2025-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144655731","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-01DOI: 10.1016/j.teler.2025.100229
Youcef Baghdadi , Supriya Pulparambil
Social media and social networks have a profound impact on business and created a new business model called social commerce (s-commerce). S-commerce is a type of electronic commerce (e-commerce) which utilizes social media platforms to facilitate commercial activities. S-commerce design deals with the structuring of online platforms that integrate social interaction and commercial interactions. S-commerce design is very significant in the transition of e-commerce to s-commerce as user preferences, social interactions, and user-generated content determine the business. This research conducts a systematic mapping study to classify s-commerce design articles published between 2015 and 2023 in online databases. A framework is proposed to analyze and categorize the existing body of knowledge on s-commerce design. The framework comprises three dimensions: design themes, design principles, and design artifacts. The results of the research show that the most prevalent design theme under s-commerce design is behavioral design (66 %), the commonly addressed design artifact is the behavior intention model (63 %), and the most emphasized design principle is usability (22 %). Among the least explored dimensions of s-commerce design are requirement design as the theme (4 %), playfulness as the design principle (6 %), and technical models and conceptual frameworks as the artifact (1 %). This indicates that human behavioral design has been well studied, while more research on technical, business, trust, and requirement design is needed for the efficient implementation of s-commerce platforms. The findings of this study guide future s-commerce research by highlighting gaps and potential directions in areas such as personalization, security, and interaction features.
{"title":"Comprehensive classification and analysis of s-commerce design research","authors":"Youcef Baghdadi , Supriya Pulparambil","doi":"10.1016/j.teler.2025.100229","DOIUrl":"10.1016/j.teler.2025.100229","url":null,"abstract":"<div><div>Social media and social networks have a profound impact on business and created a new business model called social commerce (s-commerce). S-commerce is a type of electronic commerce (e-commerce) which utilizes social media platforms to facilitate commercial activities. S-commerce design deals with the structuring of online platforms that integrate social interaction and commercial interactions. S-commerce design is very significant in the transition of e-commerce to s-commerce as user preferences, social interactions, and user-generated content determine the business. This research conducts a systematic mapping study to classify s-commerce design articles published between 2015 and 2023 in online databases. A framework is proposed to analyze and categorize the existing body of knowledge on s-commerce design. The framework comprises three dimensions: design themes, design principles, and design artifacts. The results of the research show that the most prevalent design theme under s-commerce design is behavioral design (66 %), the commonly addressed design artifact is the behavior intention model (63 %), and the most emphasized design principle is usability (22 %). Among the least explored dimensions of s-commerce design are requirement design as the theme (4 %), playfulness as the design principle (6 %), and technical models and conceptual frameworks as the artifact (1 %). This indicates that human behavioral design has been well studied, while more research on technical, business, trust, and requirement design is needed for the efficient implementation of s-commerce platforms. The findings of this study guide future s-commerce research by highlighting gaps and potential directions in areas such as personalization, security, and interaction features.</div></div>","PeriodicalId":101213,"journal":{"name":"Telematics and Informatics Reports","volume":"19 ","pages":"Article 100229"},"PeriodicalIF":0.0,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144519125","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-21DOI: 10.1016/j.teler.2025.100227
Fan Li , Xiaotian Wei , Chenyang Wang , Chenyue Zhang , Guoming Yu , Ya Yang , Yuhan Liu
This study investigates the perceived value of artificial intelligence (AI) in human-machine interactions, focusing on the distinction between augmentation and replacement. Grounded in dual-process theory, we examine how different cognitive processing pathways influence AI perception, while social cognitive theory provides insight into users’ learning motivation. Using a two-wave survey study (N = 267), we explore (1) whether users perceive AI primarily as an augmentative or substitutive tool, (2) the impact of heuristic (Type 1) vs. analytical (Type 2) processing on AI value perception, and (3) the role of self-directed vs. socially influenced learning motivation in AI engagement. The results reveal that users predominantly view AI as an augmentative tool, with Type 2 processing leading to stronger AI value perceptions. Additionally, AI’s perceived value varies by content context, with profit-driven scenarios (e.g., advertising) amplifying both augmentation and replacement perceptions compared to non-profit contexts (e.g., news). Finally, self-directed AI usage behavior significantly predicts AI learning motivation, while external social influences play a lesser role. These findings underscore the importance of cognitive and social factors in shaping AI perception and emphasize the need for AI literacy to maximize its benefits in human-machine collaboration.
{"title":"How do users perceive AI? A dual-process perspective on enhancement and replacement","authors":"Fan Li , Xiaotian Wei , Chenyang Wang , Chenyue Zhang , Guoming Yu , Ya Yang , Yuhan Liu","doi":"10.1016/j.teler.2025.100227","DOIUrl":"10.1016/j.teler.2025.100227","url":null,"abstract":"<div><div>This study investigates the perceived value of artificial intelligence (AI) in human-machine interactions, focusing on the distinction between augmentation and replacement. Grounded in dual-process theory, we examine how different cognitive processing pathways influence AI perception, while social cognitive theory provides insight into users’ learning motivation. Using a two-wave survey study (<em>N</em> = 267), we explore (1) whether users perceive AI primarily as an augmentative or substitutive tool, (2) the impact of heuristic (Type 1) vs. analytical (Type 2) processing on AI value perception, and (3) the role of self-directed vs. socially influenced learning motivation in AI engagement. The results reveal that users predominantly view AI as an augmentative tool, with Type 2 processing leading to stronger AI value perceptions. Additionally, AI’s perceived value varies by content context, with profit-driven scenarios (e.g., advertising) amplifying both augmentation and replacement perceptions compared to non-profit contexts (e.g., news). Finally, self-directed AI usage behavior significantly predicts AI learning motivation, while external social influences play a lesser role. These findings underscore the importance of cognitive and social factors in shaping AI perception and emphasize the need for AI literacy to maximize its benefits in human-machine collaboration.</div></div>","PeriodicalId":101213,"journal":{"name":"Telematics and Informatics Reports","volume":"19 ","pages":"Article 100227"},"PeriodicalIF":0.0,"publicationDate":"2025-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144557677","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-20DOI: 10.1016/j.teler.2025.100228
Elliot Mbunge , Caron Lee Jack , Maureen Nokuthula Sibiya , John Batani
Mobile health (mHealth) systems present tremendous opportunities to enhance healthcare service delivery in Africa, particularly in resource-limited settings. mHealth systems can improve access to care, bridge existing disparities in healthcare and improve communication between patients and healthcare professionals (HCPs). Despite these opportunities, various barriers hinder the effective implementation and utilization of mHealth systems in Africa. Therefore, this study analyses the utilization of mHealth systems and their implementation barriers in Africa and further proposes actionable and strategic solutions. The study applied PRISMA guidelines to search, select and analyze relevant literature from electronic databases such as Scopus, Web of Science, PubMed, CINAHL Plus and Google Scholar. A total of 17 papers were analyzed in this study. Technological barriers, digital literacy gaps, inadequate infrastructural support, economic constraints, cultural and societal resistance and lack of regional mHealth initiatives regulatory frameworks are key mHealth systems implementation barriers. Collaborative partnerships, user-centric design, government support and cultural integration are pivotal for achieving high-level technological adoption and utilization. Stakeholders and policymakers should adopt a multifaceted approach that includes investing in digital literacy and infrastructure, multisectoral engagement and collaboration, designing affordable and accessible mHealth solutions, fostering cultural acceptance through community engagement and harmonizing regulatory frameworks across African countries.
移动医疗（mHealth）系统为加强非洲的卫生保健服务提供了巨大的机会，特别是在资源有限的环境中。移动医疗系统可以改善获得医疗服务的机会，弥合医疗保健方面存在的差距，并改善患者与医疗保健专业人员（HCPs）之间的沟通。尽管有这些机会，各种障碍阻碍了移动医疗系统在非洲的有效实施和利用。因此，本研究分析了移动医疗系统的利用及其在非洲的实施障碍，并进一步提出了可操作的战略解决方案。本研究应用PRISMA指南对Scopus、Web of Science、PubMed、CINAHL Plus、谷歌Scholar等电子数据库的相关文献进行检索、选择和分析。本研究共分析了17篇论文。技术障碍、数字素养差距、基础设施支持不足、经济制约、文化和社会阻力以及缺乏区域移动卫生行动监管框架是移动卫生系统实施的主要障碍。协作伙伴关系、以用户为中心的设计、政府支持和文化融合是实现高水平技术采用和利用的关键。利益攸关方和决策者应采取多方面的方法，包括投资于数字扫盲和基础设施、多部门参与和合作、设计负担得起和可获得的移动医疗解决方案、通过社区参与促进文化接受，以及协调非洲各国的监管框架。
{"title":"Review of implementation barriers and strategic approaches for improving mHealth systems utilization in Africa: Lessons learnt from South Africa and Kenya","authors":"Elliot Mbunge , Caron Lee Jack , Maureen Nokuthula Sibiya , John Batani","doi":"10.1016/j.teler.2025.100228","DOIUrl":"10.1016/j.teler.2025.100228","url":null,"abstract":"<div><div>Mobile health (mHealth) systems present tremendous opportunities to enhance healthcare service delivery in Africa, particularly in resource-limited settings. mHealth systems can improve access to care, bridge existing disparities in healthcare and improve communication between patients and healthcare professionals (HCPs). Despite these opportunities, various barriers hinder the effective implementation and utilization of mHealth systems in Africa. Therefore, this study analyses the utilization of mHealth systems and their implementation barriers in Africa and further proposes actionable and strategic solutions. The study applied PRISMA guidelines to search, select and analyze relevant literature from electronic databases such as Scopus, Web of Science, PubMed, CINAHL Plus and Google Scholar. A total of 17 papers were analyzed in this study. Technological barriers, digital literacy gaps, inadequate infrastructural support, economic constraints, cultural and societal resistance and lack of regional mHealth initiatives regulatory frameworks are key mHealth systems implementation barriers. Collaborative partnerships, user-centric design, government support and cultural integration are pivotal for achieving high-level technological adoption and utilization. Stakeholders and policymakers should adopt a multifaceted approach that includes investing in digital literacy and infrastructure, multisectoral engagement and collaboration, designing affordable and accessible mHealth solutions, fostering cultural acceptance through community engagement and harmonizing regulatory frameworks across African countries.</div></div>","PeriodicalId":101213,"journal":{"name":"Telematics and Informatics Reports","volume":"19 ","pages":"Article 100228"},"PeriodicalIF":0.0,"publicationDate":"2025-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144502094","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-18DOI: 10.1016/j.teler.2025.100225
Christian Montag , Saifur Rahman , Johannes Thrul , Fahad AlBeyahi , Raian Ali
Electrical engineering and computer science as well as social/psychological and medical sciences have different traditions in conducting research and publishing it. These disciplines vary in the degree of focus and scrutiny they place on artifacts (e.g. software & models), knowledge, and methods, as well as the researcher's role and stance. In addition, there are differences between disciplines regarding the tools and measurements used and the subject of focus, whether human or machine. In recent years both disciplines are getting interested in studying similar research questions, whereas each party could benefit from interdisciplinary perspectives. This manuscript illustrates one relevant research area: The case of digital well-being intersects digital media design, primarily an engineering concern, with the goal of preserving and improving the well-being of users and society (the latter often being a focus of social, psychological and medical sciences). Logically, the goals of this research endeavor can be at best reached via interdisciplinary efforts, where the computer sciences meet the social/psychological/medical sciences. This will be also true for the new research area of AI well-being, and we discuss relationships between digital well-being and AI well-being on a theoretical level.
{"title":"Bringing computer and social/psychological/medical sciences together: The case of digital well-being and AI well-being","authors":"Christian Montag , Saifur Rahman , Johannes Thrul , Fahad AlBeyahi , Raian Ali","doi":"10.1016/j.teler.2025.100225","DOIUrl":"10.1016/j.teler.2025.100225","url":null,"abstract":"<div><div>Electrical engineering and computer science as well as social/psychological and medical sciences have different traditions in conducting research and publishing it. These disciplines vary in the degree of focus and scrutiny they place on artifacts (e.g. software & models), knowledge, and methods, as well as the researcher's role and stance. In addition, there are differences between disciplines regarding the tools and measurements used and the subject of focus, whether human or machine. In recent years both disciplines are getting interested in studying similar research questions, whereas each party could benefit from interdisciplinary perspectives. This manuscript illustrates one relevant research area: The case of digital well-being intersects digital media design, primarily an engineering concern, with the goal of preserving and improving the well-being of users and society (the latter often being a focus of social, psychological and medical sciences). Logically, the goals of this research endeavor can be at best reached via interdisciplinary efforts, where the computer sciences meet the social/psychological/medical sciences. This will be also true for the new research area of AI well-being, and we discuss relationships between digital well-being and AI well-being on a theoretical level.</div></div>","PeriodicalId":101213,"journal":{"name":"Telematics and Informatics Reports","volume":"19 ","pages":"Article 100225"},"PeriodicalIF":0.0,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144534827","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Even though previous studies have examined the relationship between organizational culture and successful information technology (IT) project performance globally, only a few studies have tried to examine the role of organizational culture on successful IT project performance in the Jordanian context. Therefore, the purpose of this research is to examine four factors of organizational culture namely strategic emphasis, positive work environment, leadership risk tolerance, and results orientation on the overall successful IT project performance in Jordanian organizations. To achieve the above-mentioned purpose, a quantitative research method with a questionnaire was used to collect data from 146 project managers, systems analysts, project consultants, program executives, IT managers, and project coordinators who work in Jordanian organizations. The Partial Least Squares Structural Equation Modeling (PLS-SEM) was used to analyze collected data. The results confirmed that successful IT project performance in Jordanian organizations is significantly and positively influenced by strategic emphasis and leadership risk tolerance. Contrary to what is expected, no associations could be established between a positive work environment and results orientation on successful IT project performance in Jordanian organizations, and hence the related hypotheses were rejected.
{"title":"Exploring the impact of organizational culture on the performance of information technology projects in Jordanian organizations","authors":"Ashraf Bany Mohammed , Yousef Alsafadi , Manaf Al-Okaily , Heba Al-Hyasat , Yunus Al-yahya , Ra’ed Masa’deh","doi":"10.1016/j.teler.2025.100210","DOIUrl":"10.1016/j.teler.2025.100210","url":null,"abstract":"<div><div>Even though previous studies have examined the relationship between organizational culture and successful information technology (IT) project performance globally, only a few studies have tried to examine the role of organizational culture on successful IT project performance in the Jordanian context. Therefore, the purpose of this research is to examine four factors of organizational culture namely strategic emphasis, positive work environment, leadership risk tolerance, and results orientation on the overall successful IT project performance in Jordanian organizations. To achieve the above-mentioned purpose, a quantitative research method with a questionnaire was used to collect data from 146 project managers, systems analysts, project consultants, program executives, IT managers, and project coordinators who work in Jordanian organizations. The Partial Least Squares Structural Equation Modeling (PLS-SEM) was used to analyze collected data. The results confirmed that successful IT project performance in Jordanian organizations is significantly and positively influenced by strategic emphasis and leadership risk tolerance. Contrary to what is expected, no associations could be established between a positive work environment and results orientation on successful IT project performance in Jordanian organizations, and hence the related hypotheses were rejected.</div></div>","PeriodicalId":101213,"journal":{"name":"Telematics and Informatics Reports","volume":"19 ","pages":"Article 100210"},"PeriodicalIF":0.0,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144306958","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-14DOI: 10.1016/j.teler.2025.100222
Mohammad Javad Shayegan, Nasim Kazem Shiroodi
Influencer marketing has become a critical strategy for brands, with micro-influencers playing a pivotal role in shaping consumer behavior on social media. These influencers significantly impact user decision-making; however, identifying the right micro-influencers who align with a brand’s identity and can maximize engagement remains a challenging task. This study aims to develop an effective system to predict which micro-influencers will generate the highest engagement for brands. The proposed method combines ResNet for extracting visual features from Instagram posts and BERT for extracting textual features, demonstrating a high degree of accuracy in predicting engagement rates. Three machine learning algorithms—Linear Regression, Random Forest, and Extreme Gradient Boosting—were employed for model training, with performance evaluated using Root Mean Squared Error (RMSE). Among these, the Random Forest model, enhanced through feature selection and hyperparameter tuning, achieved the lowest error with an RMSE of 1.50 %. Further evaluation using metrics such as AUC, cAUC, and MedR demonstrated that the proposed approach (ResNet + BERT) outperforms other methods across all metrics, achieving an AUC of 81 %, a cAUC of 67 %, and a MedR of 2. The proposed method improved AUC by 12 % and cAUC by 8 %, confirming its effectiveness in identifying high-engagement micro-influencers.
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