Telematics and Informatics最新文献

{"title":"AI on dating apps: links between usage frequency, self-efficacy, self-esteem, and willingness to use AI","authors":"Alice Binder,&nbsp;Anja Stevic,&nbsp;Jaroslava Kaňková,&nbsp;Jörg Matthes","doi":"10.1016/j.tele.2026.102460","DOIUrl":"10.1016/j.tele.2026.102460","url":null,"abstract":"<div><div>Artificial Intelligence (AI) plays a crucial role in dating apps. Whereas impressions of matchmaking algorithms are already well understood, studies are missing that investigate the connections of these impressions on the willingness of dating app users to use AI themselves. This cross-sectional study with <em>N</em> = 693 young adults (16–27 years) investigates the relationship of the frequency of using dating apps with the self-efficacy of controlling the algorithms used on these apps and how this relationship is associated with the willingness to use AI for a) curation and communication, and/or b) risk and fraud detection. Furthermore, the role of self-esteem is examined. Results show that frequent use of dating apps is positively associated with self-efficacy, and self-efficacy is positively associated with using AI on dating apps. Especially for users with high levels of self-esteem, the relationship between frequency of dating app use and self-efficacy is high.</div></div>","PeriodicalId":48257,"journal":{"name":"Telematics and Informatics","volume":"110 ","pages":"Article 102460"},"PeriodicalIF":9.9,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149155359","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Did generative AI narrow the digital divide for immigrants in South Korea? A difference-in-differences study, 2019–2023","authors":"Nari Yoo,&nbsp;Sou Hyun Jang","doi":"10.1016/j.tele.2026.102469","DOIUrl":"10.1016/j.tele.2026.102469","url":null,"abstract":"<div><div>Generative artificial intelligence diffused rapidly after late 2022, raising the question of whether it would widen or narrow the digital divide for marginalized populations. We analyzed the Korean Digital Divide Survey across the transition, in 2019 and 2023, comparing three groups: the native-born Korean population, marriage immigrants, and North Korean migrants. The North Korean migrants provide a comparison for the language mechanism, a similarly marginalized group without a foreign-language barrier. Using weighted difference-in-differences with continuous-age adjustment, we found that the marriage-immigrant gap in AI use with the native-born Korean population closed and reversed, with marriage immigrants surpassing native-born Koreans (logit difference-in-differences 0.25, SE 0.12, <em>p</em> = .04, about 4 percentage points), while North Korean migrants did not converge (−0.13, SE 0.12, <em>p</em> = .30); the contrast between the two groups, the central test, was significant (0.38, SE 0.17, <em>p</em> = .02) and widened under full adjustment. Both marginalized groups became more positive about AI use and gained digital competency and social capital. The North Korean migrants gained even more competency, yet only the marriage immigrants converted these resources into use. The marriage-immigrant convergence was concentrated in the language-production domains, document writing and communication, where the language affordance is most direct, but North Korean migrants did not converge there. Mediation attributed the marriage-immigrant convergence chiefly to bridging social capital and digital competency; for North Korean migrants, the same resources predicted a convergence that did not occur. The pattern is most consistent with generative AI's language capability mattering for a group that operates across languages: the convergence was not shared by an equally marginalized native-speaking group and is not explained by a general narrowing of digital inclusion. Because the two migrant groups differ in more than language and proficiency is not measured, we interpret this as the most plausible explanation rather than a proven mechanism.</div></div>","PeriodicalId":48257,"journal":{"name":"Telematics and Informatics","volume":"110 ","pages":"Article 102469"},"PeriodicalIF":9.9,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149200685","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ideological cues: Fishing photos and US flags reduce romantic interest among liberal daters on dating apps","authors":"Annika From,&nbsp;Jasmine Banks,&nbsp;Janae W. Sayler","doi":"10.1016/j.tele.2026.102468","DOIUrl":"10.1016/j.tele.2026.102468","url":null,"abstract":"<div><div>This study investigates how visual cues in dating app profiles affect perceived political ideology and romantic interest, and how these effects intersect with demographic characteristics, political ideology, and color-blind racial attitudes—a modern form of racism in which individuals believe that racism is not a significant societal issue. Using a stratified sample of 676 recent dating app users, participants viewed dating app profiles that varied in the hobby (i.e., knitting, fishing, gardening) and flag (i.e., Black Lives Matter, US, Dartmouth) displayed in the profile picture. Results show that profiles featuring fishing or US flags were perceived as more conservative by liberal participants, women, and those with lower color-blind racial attitudes. These effects were stronger for white profiles and men's profiles, indicating that visual cues may be especially salient for those dating white men. Liberal participants and those with lower color-blind racial attitudes also reported being less interested in profiles with US flags. While liberal participants were highly responsive to these signals and interpreted them as cues of political ideology, conservative participants did not, suggesting important differences in cue interpretation across political parties. The findings highlight the role of visual heuristics in partner selection on dating apps and suggest the interpretation of these cues may contribute to political homophily.</div></div>","PeriodicalId":48257,"journal":{"name":"Telematics and Informatics","volume":"110 ","pages":"Article 102468"},"PeriodicalIF":9.9,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149200645","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Privacy management in LLM-based self-diagnosis: a cross-cultural study across 25 countries","authors":"Ge Zhu,&nbsp;Yuhan Zhang,&nbsp;Di Zhang","doi":"10.1016/j.tele.2026.102465","DOIUrl":"10.1016/j.tele.2026.102465","url":null,"abstract":"<div><div>Large Language Models (LLMs) for self-diagnosis create a tension between access to medical information and the disclosure of sensitive health information. Adopting a Communication Privacy Management (CPM)-informed perspective, this study examines how perceived privacy risk and control are associated with intention to use LLM-based self-diagnosis. It further examines two forms of privacy assurance (perceived effectiveness of privacy policy and privacy-protective technology), perceived health information sensitivity, and perceived usefulness as antecedents of perceived privacy risk and control, while considering country-level individualism as a core cultural influence on privacy rule formation. Based on data from 4088 participants across 25 countries, multilevel structural equation modeling (MSEM) reveals that both perceived privacy risk and control are significantly associated with usage intention, with a larger standardized association observed for privacy risk. Perceived effectiveness of privacy policy and privacy-protective technology show negative associations with perceived privacy risk, although only the effectiveness of privacy policy is positively associated with perceived privacy control. Perceived health information sensitivity shows positive associations with both perceived privacy risk and control, whereas perceived usefulness shows negative associations with both. Country-level individualism is negatively associated with usage intention. It also strengthens both the negative association of privacy risk and the positive association of privacy control with usage intention. Theoretically, the study contextualizes CPM-informed privacy management in LLM-based healthcare and illustrates the relevance of cultural context to the behavioral implications of privacy risk and control. Empirically, it provides multilevel evidence on privacy management and usage across 25 national contexts.</div></div>","PeriodicalId":48257,"journal":{"name":"Telematics and Informatics","volume":"110 ","pages":"Article 102465"},"PeriodicalIF":9.9,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149155360","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AI hallucinations and user verification intentions: an integrative model based on the DeLone and McLean model and the theory of planned behavior","authors":"Bo Hu,&nbsp;Yu-li Liu,&nbsp;Jiayue Dai,&nbsp;Jiayi Mi","doi":"10.1016/j.tele.2026.102467","DOIUrl":"10.1016/j.tele.2026.102467","url":null,"abstract":"<div><div>Generative artificial intelligence (GenAI) has become deeply integrated into everyday life and has increasingly become a key source of information. However, the prevalence of AI hallucinations, which refer to instances in which AI systems generate inaccurate or misleading information, raises concerns about the quality and reliability of the responses. Drawing on the Information Systems Success Model and the Theory of Planned Behavior (TPB), this study examines the factors that influence users' intentions to verify information generated by GenAI. An online survey was conducted among 620 Chinese participants. The findings based on structural equation modeling analysis reveal that system quality, information quality, and service quality positively influence perceived credibility, which in turn reduces perceptions of AI hallucination potential. Perceived hallucination potential further promotes a favorable attitude toward information verification. Consistent with the TPB, verification intention is significantly affected by attitude, subjective norm, and perceived behavioral control. This study extends the literature on AI hallucinations and information verification by identifying the mechanisms through which quality perceptions and credibility shape users' verification intentions. Theoretical implications and practical recommendations are discussed.</div></div>","PeriodicalId":48257,"journal":{"name":"Telematics and Informatics","volume":"110 ","pages":"Article 102467"},"PeriodicalIF":9.9,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149200644","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Algorithmic visibility of child-directed content: Exposure and persistence dynamics in YouTube trending lists across 113 countries","authors":"Yavuz Selim Balcioğlu,&nbsp;Erkut Altindağ","doi":"10.1016/j.tele.2026.102472","DOIUrl":"10.1016/j.tele.2026.102472","url":null,"abstract":"<div><div>The algorithmic curation of content on digital platforms raises important questions about which content categories achieve systematic visibility and under what structural conditions. This study examines explicitly child-directed and child-centered content in YouTube trending lists across 113 countries. Drawing on 5,505,720 trending-video observations collected between 26 October 2023 and 5 July 2026 and aggregated into 110,847 country-day units, the analysis uses a conservative lower-bound metadata classifier and two-way fixed-effects panel models. A 256-video simple random validation yielded TP = 1, FP = 0, FN = 1, and TN = 254 (precision = 1.00, recall = 0.50, F1 = 0.67, classifier-manual κ = 0.665), but these estimates are imprecise because only two manually positive cases occurred. An additional blinded stratified challenge set of 196 videos yielded 37 true positives, 9 false positives, 15 false negatives, and 135 true negatives; positive confirmation among classifier-positive cases was 80.4%. The final classifier identified 7707 records (0.14%). Child-directed share showed strong aggregate autoregressive persistence (β = 0.768, <em>p</em> &lt; .001); this coefficient concerns persistence in the country-level share, not retention of the same videos. Exposure scale was positively associated with child-directed share, whereas approval and conversational rates provided no robust positive support. PPML and sensitivity specifications preserved the central persistence and exposure findings.</div></div>","PeriodicalId":48257,"journal":{"name":"Telematics and Informatics","volume":"110 ","pages":"Article 102472"},"PeriodicalIF":9.9,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149201223","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Being perfectly seen: Affective capture, relational risk, and the Autopticon effect in AI companion systems","authors":"Shiyi Zhang,&nbsp;Shiyu (Sharon) Zheng","doi":"10.1016/j.tele.2026.102461","DOIUrl":"10.1016/j.tele.2026.102461","url":null,"abstract":"<div><div>The rapid integration of conversational artificial intelligence into everyday life has made AI companion systems both widely used and the focus of increasing concern, particularly following publicly documented self-harm tragedies associated with intensive use of platforms such as ChatGPT and Character.AI. This article examines three such cases through a critical multi-case study, combining thematic analysis of Reddit discourse with critical discourse analysis of human-AI dialogue excerpts drawn from legal complaints and reputable news reporting. Treating the cases as extreme rather than representative, the study identifies affective capture as a relational mechanism through which engagement-oriented AI companion systems may intensify disclosure, dependency, and vulnerability. This mechanism operates through three analytically distinct but mutually reinforcing processes: engineered anthropomorphism, sycophantic validation, and persistent memory. To theorize this dynamic, the article develops the concept of the Autopticon, a mid-range concept describing subordination through the promise of being directly and intensely witnessed by a responsive artificial interlocutor. Whereas the Panopticon disciplines through the threat of being watched, the Autopticon captures through the seductive offer of perfect recognition. The article argues that AI companion risk cannot be addressed through content-level guardrails alone because the relevant harm is relational, cumulative, and embedded in engagement-oriented design. It contributes to digital technology and society research by reframing AI companion safety as a problem of how the continuing user-system relationship is designed and by proposing mechanism-specific design and governance safeguards for platforms that mediate intimate human-AI interaction.</div></div>","PeriodicalId":48257,"journal":{"name":"Telematics and Informatics","volume":"110 ","pages":"Article 102461"},"PeriodicalIF":9.9,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149200643","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Over-reliance on AI in information tasks: Unraveling the roles of reasoning visibility and task complexity","authors":"Zihan Zhu,&nbsp;Yang Li","doi":"10.1016/j.tele.2026.102464","DOIUrl":"10.1016/j.tele.2026.102464","url":null,"abstract":"<div><div>Recent large language models expose their reasoning processes to users, an interface design intended to improve explainability and support calibrated trust. Yet whether visible reasoning calibrates reliance or amplifies over-reliance remains unclear. This study examined how reasoning visibility and task complexity influence users' over-reliance on AI in information processing tasks, along with the underlying psychological mechanisms and boundary conditions. Three online experiments (total <em>N</em> = 657), spanning the health, environment, and technology domains, showed that both visible reasoning and task complexity increased over-reliance, with no interaction between them. Mediation analyses indicated that both factors increased over-reliance through perceived AI competence, while task complexity additionally did so by reducing perceived unaided self-efficacy. AI literacy, particularly awareness literacy, buffered the effect of reasoning visibility but not that of task complexity. These findings demonstrate that interface features designed to enhance transparency can backfire when their mere presence is interpreted as a cue of AI competence, amplifying over-reliance above an existing baseline. They carry implications for understanding over-reliance in human-AI collaborative information behavior and for designing responsible AI interfaces.</div></div>","PeriodicalId":48257,"journal":{"name":"Telematics and Informatics","volume":"110 ","pages":"Article 102464"},"PeriodicalIF":9.9,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149155358","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"How and when AI companionship quality enhances user mental well-being","authors":"Pengyi Shen,&nbsp;Dehui Peng,&nbsp;Jinan Xu","doi":"10.1016/j.tele.2026.102470","DOIUrl":"10.1016/j.tele.2026.102470","url":null,"abstract":"<div><div>With the rapid advancement of artificial intelligence technology, AI companions have gradually become important tools for alleviating mental health issues such as loneliness and anxiety. Grounded in social support theory, this paper employs a combination of multi-wave questionnaire surveys and experimental methods to comprehensively investigate the mechanisms and boundary conditions by which AI companionship quality affects users' mental well-being. The results reveal that the use of AI companions is associated with enhanced mental well-being, which is mediated by increased emotional clarity and reduced self-presentation concerns among users. Furthermore, mindfulness level plays a significant moderating role: specifically, high-mindfulness users are better able to enhance their emotional awareness and reduce self-evaluative burden through AI companionship, whereas low-mindfulness users, due to cognitive constraints, struggle to translate external support into effective psychological protective factors. In addition, AI anthropomorphism conditions positively moderate the pathway through which AI companionship quality enhances mental well-being via emotional clarity, but its moderating effect on the pathway via reduced self-presentation concerns is not significant, suggesting that the “non-judgmental” nature of AI companions plays a more fundamental role in providing emotional safety. This paper offers managerial implications for the design, development, marketing, and deployment of AI companion products.</div></div>","PeriodicalId":48257,"journal":{"name":"Telematics and Informatics","volume":"110 ","pages":"Article 102470"},"PeriodicalIF":9.9,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149200646","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Unveiling deceptive narratives: Interpretable machine learning for rhetorical device analysis in fake news detection","authors":"Kai Meng,&nbsp;Jiachun Wu,&nbsp;Peiliang Zhang,&nbsp;Ling Kong,&nbsp;Soobin Lee,&nbsp;Hea-Jin Kim,&nbsp;Min Song","doi":"10.1016/j.tele.2026.102466","DOIUrl":"10.1016/j.tele.2026.102466","url":null,"abstract":"<div><div>The proliferation of fake news on social media poses risks, undermining trust and exacerbating political and social polarization. Although machine learning is critical for automatic fake news detection, approaches often overlook rhetorical strategies in fake news and have limited interpretability. This study proposes an interpretable framework employing rhetorical text analysis using a four-stage method applying principles from computational linguistics and post hoc interpretability. This approach preprocesses a balanced corpus comprising verified fake and real news articles. This framework operationalizes 22 rhetorical features via systematic textual analysis, capturing syntactic structures and stylistic devices, and evaluates 12 machine learning models using cross-validation, finding extreme gradient boosting the most effective. Finally, this work employs Shapley additive explanation values and partial dependence plots to interpret the decision-making process, finding that repetitive structures exhibit a threshold effect, with diminishing marginal returns after 20 occurrences. Similes act as moderators of extreme rhetorical devices, buffering the effect of hyperbole in fake news, and real news tends to display distinctive patterns via concise syntactic constructions. This framework integrates advanced feature engineering with transparent modeling, attaining a detection accuracy of 87.385%, advancing computational methods in fake news detection and offering practical implications for content moderation and media literacy.</div></div>","PeriodicalId":48257,"journal":{"name":"Telematics and Informatics","volume":"110 ","pages":"Article 102466"},"PeriodicalIF":9.9,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149155361","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}