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A structural equation modeling approach to leveraging the power of extant sentiment analysis tools

JOURNAL OF COMPUTATIONAL SOCIAL SCIENCE 2025年第1期8卷 1-21页

作者： Lebakula, Viswadeep Porter, Ben Stubbs-Richardson, Megan Ray, Taylor Cosby, Arthur Bethel, Cindy Oak Ridge Natl Lab Geospatial Sci & Human Secur Div 1 Bethel Valley Rd Oak Ridge TN 37830 USA Mississippi State Univ Dept Psychol Mississippi State MS 39762 USA Mississippi State Univ Social Sci Res Ctr Mississippi State MS 39759 USA Mississippi State Univ Comp Sci & Engn Mississippi State MS 39762 USA

Machine-derived sentiment analysis has become a pervasive and useful tool to address a wide array of issues in natural language processing. Leading technology companies such as Google now provide sentiment analysis tools (SATs) as readily accessible online products. Academic researchers develop and make available SATs to support the research enterprise. One of the major challenges with SATs is the inconsistencies in results among the various SATs. Consequently, the selection of a SAT for a specific purpose may significantly impact the application. This study addresses the foregoing problem by utilizing structural equation modeling to merge the outputs of SATs to develop a combined sentiment metric without the need for a labeled training dataset. This method is applicable to a wide range of text-based problems, is data-driven, and replicable. It was tested using three publicly available datasets and compared against seven different SATs. The results indicate that as a continous measure, the proposed method outperformed other SATs in the movie reviews and SemEval datasets, and achieved a tie for first place with IBM Watson on the Sentiment 140 dataset. Also, compared to the published major alternatives, the arithmetic mean solution, this approach performed better across these three datasets.

关键词： Sentiment analysis Sentiment tools Natural language processing Text processing Combining sentiment analysis tools structural equation modeling Amazon comprehend Text blob Vader Google nlp Ibm watson Sentiment 140 Stanford corenlp

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Exploring the Effects of Technology-Related Informal Mathematics Learning Activities: A structural equation modeling Analysis

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INTERNATIONAL JOURNAL OF SCIENCE AND MATHEMATICS EDUCATION 2025年第1期23卷 49-69页

作者： Jiang, Haozhe Chugh, Ritesh Turnbull, Darren Wang, Xiaoqin Chen, Suting Zhejiang Univ Coll Educ Hangzhou 310058 Zhejiang Peoples R China Cent Queensland Univ CML NET & CREATE Res Ctr Sch Engn & Technol North Rockhampton Qld 4702 Australia East China Normal Univ Coll Teacher Educ Fac Educ Shanghai 200062 Peoples R China Shanghai Jian Qiao Univ Shanghai 201306 Peoples R China

Despite the burgeoning adoption of informal learning in people's daily lives, the actual effects of informal learning activities, especially technology-related informal learning activities, are much less reported than those of formal learning. Furthermore, there is a notable lack of research on the effects of technology-related informal mathematics learning activities (TRLA). This study aims to propose and validate a new model which illustrates the effects of TRLA on four constructs: mathematics self-efficacy (MSE), mathematics interest (MI), self-regulation in mathematics learning (SR), and teacher-student relationship (TSR). Adopting a quantitative cross-sectional survey approach, 460 students were investigated. The data were analyzed employing two-step structural equation modeling. Our findings demonstrate the direct effects of TRLA on MI and SR as well as the indirect effects on MI, MSE, and TSR. This study advances the understanding of technology-enhanced informal learning, which is an emerging perspective of technology-enhanced learning.

关键词： Effect Informal mathematics learning structural equation modeling Technology enhanced learning Technology-related learning activities

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A Renewal of Dyadic structural equation modeling With Latent Variables: Clarifications, Methodological Advantages, and New Directions

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SOCIAL AND PERSONALITY PSYCHOLOGY COMPASS 2025年第3期19卷

作者： Sakaluk, John Kitchener Joel, Samantha Quinn-Nilas, Christopher Camanto, Omar Jordan Pevie, Noah William Tu, Eric Jorgensen-Wells, McKell A. Western Univ Dept Psychol London ON Canada Mem Univ Dept Psychol St John NF Canada York Univ Dept Psychol Toronto ON Canada

Researchers interested in the quantitative analysis of data from dyads must select a preferred statistical framework. In this review, we focus on one option that has seen relatively modest adoption: dyadic structural equation modeling with latent variables. We begin by distinguishing dyadic SEM from alternate, neighboring, and hybridized frameworks, before sharing our view on the unique-and in our opinion, considerable-value-proposition of the dyadic SEM framework. We then provide some preliminary evidence that dyadic SEM is subordinated in terms of adoption rates versus its competitors, before offering a contextual analysis of why that may have come to be the case. Finally, we conclude with a discussion of future possibilities, some near and accessible and others farther away and more technical, that researchers in the field might pursue (and benefit from) with the help of dyadic SEM with latent variables.

关键词： actor-partner interdependence model common fate model dyadic data interdependence measurement modeling multilevel modeling path analysis structural equation modeling

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A combined approach using structural equation modeling and analytic hierarchy process in hub airports selection

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JOURNAL OF AIR TRANSPORT MANAGEMENT 2025年 124卷

作者： Bordeaux, Gabriel Couto, Antonio Jimenez, Edgar Univ Porto Fac Engn Res Ctr Terr Transports & Environm Rua Dr Roberto Frias P-4200465 Porto Portugal Cranfield Univ Ctr Air Transport Management Coll Rd Cranfield MK43 0AL England

This study presents a method to assist airlines in selecting a hub airport using structural equation modeling (SEM) combined with Analytic Hierarchy Process (AHP). This approach aims to determine the most essential elements in this selection process using observed variables collected from 300 major airports worldwide. Research on key aspects for hub airport selection is still scarce in the literature. Furthermore, most studies rely on multicriteria analyses with weights obtained through expert interviews, potentially introducing subjectivity. Therefore, this paper presents a unique approach: criteria and sub-criteria values in the AHP are determined by the results achieved in the SEM, providing a reliable scale of priorities among variables in the process of choosing a hub. The SEM tested two hypotheses that were supported by comparing two latent variables related to airport and region characteristics with another latent variable referring to aspects present in the activity of the dominant airline within each facility. Subsequently, an AHP was implemented, with criteria and sub-criteria weights based on the standardized loading factors and regression coefficients from the SEM, using sets of airports for each established world region in the study. Results indicated that airport characteristics, particularly those related to the passenger terminals, have a greater influence on the main carrier activity than region characteristics. A regional analysis revealed that in the Americas, Europe, the Middle East, and Africa, this predominance is even more pronounced, whereas in Asia-Pacific region, there is a contrary trend in which the socioeconomic factors of the city appear to be more important than airport infrastructure. The weights assigned in the AHP, based on SEM values, confirmed cohesion between the two stages of the proposed model.

关键词： Hub airports structural equation modeling Analytic hierarchy process Hub selection

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Relational processes of cultural humility in counseling: A structural equation modeling study

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JOURNAL OF COUNSELING AND DEVELOPMENT 2025年第1期103卷 71-85页

作者： Zhu, Peitao Luke, Melissa M. Wang, Qiu Liu, Yanhong Northern Illinois Univ Dept Counseling & Higher Educ Graham 427C De Kalb IL 60115 USA Syracuse Univ Dept Counseling & Human Serv Syracuse NY USA Syracuse Univ Dept Higher Educ Syracuse NY USA

The relational nature of cultural humility (CH) has been evident since the beginning of its conceptual and empirical explorations in multicultural counseling. However, few studies have intentionally used a theory-driven framework to examine the relational processes of CH. In the current study, we used a structural equation modeling approach to examine the relationships between CH, empathy, therapeutic working alliance, and real relationship through a common factors framework. Using a sample of 610 adult counseling clients, we found that CH accounted for approximately 60% of the variance in the working alliance and 58% of the variance in the real relationship. Moreover, we found that empathy partially mediated the dispositional and situational effects of CH on both relational outcomes. We discussed strategies to cultivate CH in counseling relationships. We also recommended future researchers identify other theoretically related mediators and moderators.

关键词： common factors cultural humility empathy structural equation modeling therapeutical relationship

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Unpacking perceived risks and AI trust influences pre-service teachers' AI acceptance: A structural equation modeling-based multi-group analysis

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EDUCATION AND INFORMATION TECHNOLOGIES 2025年第2期30卷 2645-2672页

作者： Zhang, Chengming Hu, Min Wu, Weidong Kamran, Farrukh Wang, Xining Zhejiang Int Studies Univ German Studies Ctr 299 Liuhe Rd Hangzhou Zhejiang Peoples R China Univ Baltistan Dept Educ Dev Skardu Pakistan Univ St Andrews Sch Med St Andrews Scotland

Artificial intelligence (AI) integration in education has grown significantly recently. However, the potential risks of AI have led to educators being wary of implementing AI systems. To discover whether AI systems can be effective in the classroom in the future, it is critical to understand how risk factors (e.g., perceived safety risks, perceived privacy risks, and urban/rural differences) affect pre-service teachers' AI acceptance. Therefore, the study aimed to (1) explore the influence of perceived risks and AI trust on pre-service teachers' intentions to use AI-based educational applications, and (2) investigate possible variations in potential determinants of their intentions to use AI based on urban-rural differences. In this study, data from 483 pre-service teachers in China (262 from rural areas) were obtained by survey and analyzed using confirmatory factor analysis (CFA) and structural equation modeling-based multi-group analysis. The study's findings demonstrated that while AI trust influenced pre-service teachers' AI acceptance, the effect was less pronounced than perceived ease of use and perceived usefulness. Most notably, findings showed that perceived privacy and safety risks negatively influence AI trust among pre-service teachers from rural areas, which was a trend not observed in pre-service teachers from urban areas. As a result, to integrate AI-based applications into educational settings, pre-service teachers believed that the AI system must be functionally robust, user-friendly, and transparent. In addition, urban-rural differences considerably affect pre-service teachers' AI acceptance. This study provides further relevant recommendations for educators and policymakers.

关键词： AI acceptance AI trust Perceived risk Pre-service teachers Technology acceptance model structural equation modeling

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Conceptual structure and thematic evolution in partial least squares structural equation modeling research

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Quality and Quantity 2025年 1-46页

作者： Angelelli, Mario Ciavolino, Enrico Ringle, Christian M. Sarstedt, Marko Aria, Massimo Department of Human and Social Sciences and CAMPI – Centre of Applied Mathematics and Physics for Industry University of Salento Complesso Studium – Edificio 5 Via Di Valesio Lecce 73100 Italy WSB Merito University in Gdansk Gdansk Poland Department of Management Sciences and Technology Hamburg University of Technology Am Schwarzenberg-Campus 4 (D) Hamburg 21073 Germany College of Business Law and Governance James Cook University Townsville Australia LMU Munich School of Management Ludwig-Maximilians-University Munich Ludwigstraße 28 RG/III Munich 80539 Germany Faculty of Economics and Business Administration Babeș-Bolyai University Cluj-Napoca Romania Department of Economics and Statistics University of Napoli “Federico II” Via Vicinale Cupa Cintia 21 Naples 80126 Italy

structural equation modeling (SEM) using partial least squares (PLS) has received considerable attention in recent years. We address the increasing fragmentation of PLS-SEM-related research across multiple fields of scientific inquiry by presenting a bibliometric analysis’s results of n = 9,150 documents from the Web of Science database. We identify the main themes by using bibliometric content analysis to explore the PLS-SEM knowledge structure’s definition, its main drivers, and the interplay between the methodology and the application themes over time. Furthermore, we document the dynamics of the PLS-SEM knowledge structure over four periods spanning 1995–2022, unveiling a surge in scientific production and connections among thematic areas due to topic evolution and hybridization. Finally, we investigate the driving forces behind these trends and the relationship between methodology and application themes, providing an integrative view and insights into PLS-SEM research across disciplines. © The Author(s) 2025.

关键词： Bibliometric content analysis Bibliometrix R package Conceptual structure Network analysis Partial least squares structural equation modeling

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Pathway analysis of the impact of dysphagia on the prognosis of patients with stroke: Based on structural equation modeling

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CLINICAL NUTRITION ESPEN 2025年 66卷 1-8页

作者： Liu, Huan Hou, Yutong Shi, Jiajia Liu, Wenbo Zhang, Pingping Kunshan Rehabil Hosp Rehabil Dept 888 Yingbin East Rd Kunshan 215314 Peoples R China Weifang Med Univ Sch Rehabil Med 7166 Baotong West St Weifang Shandong Peoples R China Weifang Med Univ Clin Med Coll 1 7166 Baotong West St Weifang Shandong Peoples R China Shanghai Univ Tradit Chinese Med Shanghai Univ Med & Hlth Sci 1200 Cailun Rd Shanghai 201203 Peoples R China

Background and aims: Dysphagia is significantly correlated with prognostic outcomes in patients with stroke;however, the intrinsic mechanism of action between the two remains unclear. This study aimed to model the intrinsic mechanism of action between dysphagia and prognostic outcomes in patients with stroke based on structural equation modeling. Methods: A retrospective analysis of 900 inpatients with stroke from three large hospitals was performed. AMOS software (version 23.0) was used to construct the structural equation modeling. Results: The overall model showed a good fit (chi-square = 27.3, root mean square error of approximation = 0.01, standardized root mean square residual = 0.032, comparative fit index = 0.98, and adjusted goodness of fit = 0.94). structural equation modeling showed that the total effect of dysphagia on the prognosis of patients with stroke was 0.694, with a direct effect of 0.599, accounting for 86.31 % of the total effect. The total indirect effect was 0.095, with the mediating effects of serum albumin level and pneumonia accounting for 6.48 % and 7.35 % of the total effect, respectively. The moderating effects of sex on dysphagia and the relationship between activities of daily living, modified Rankin scale score, and length of hospital stay were insignificant (DR2 = 0.063, P = 0.145;DR2 = 0.002, P = 0.620;DR2 = 0.001, P = 0.307). Conclusions: Dysphagia can directly affect the prognostic outcomes of patients with stroke and indirectly affect prognosis by triggering pneumonia and lowering albumin levels. Sex was not found to play a moderating role in the relationship between dysphagia and prognosis. (c) 2024 European Society for Clinical Nutrition and Metabolism. Published by Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.

关键词： Dysphagia Stroke Serum albumin Mediating effect Moderating effect structural equation modeling

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Linking 'positive reactions' to utility reactions and trainee satisfaction: a structural equation modeling approach

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INTERNATIONAL JOURNAL OF TRAINING RESEARCH 2025年第1期23卷 20-46页

作者： Bhat, Zahid Hussain Rainayee, Riyaz Ahmad Univ Kashmir HKM Govt Degree Coll Bandipora Higher Educ Dept Govt J&K Srinagar India Univ Kashmir Commerce Srinagar India Univ Kashmir HKM Govt Degree Coll Bandipora Higher Educ Dept Govt J&K Srinagar 193502 J&K India

This study examines the effects of trainee reactions on perceived training utility and trainee course satisfaction and tests the effect of utility reactions on trainees' satisfaction with training. 171 civil service officers participated in this study. The responses were analyzed using the Partial Least Square Approach of structural equation modeling. The results support the proposed hypotheses, suggesting that both positive training reactions and utility reactions affect trainees' satisfaction with the training. Also, while all reaction components are predictive of utility reactions and trainee satisfaction, the perceived usefulness of training has the most significant effect. This study has implications for policymakers on both a theoretical and practical level, given their roles in designing training programs and imparting them to civil servants. This paper extends management perspectives on training evaluation by examining the relationship between trainee reactions, utility reactions, and trainees' satisfaction. Practical implications and directions for further research are also discussed. Relevance, usefulness, and consistency of training material alleviate participants' level of ***' positive reaction to training significantly predicts satisfaction with the training program/courseThe capacity and capability of trainers affect trainees' reactions.

关键词： Vocational training reaction evaluation trainee satisfaction utility reactions structural equation modeling PLS-SEM

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Exploring the impact of blended collaborative learning on deep learning outcomes: a structural equation modeling approach

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EDUCATION AND INFORMATION TECHNOLOGIES 2025年 1-27页

作者： Wu, Xiu-Yi Chinese Univ Hong Kong Dept Curriculum & Instruction Hong Kong Peoples R China ShenZhen Inst Informat Technol Shenzhen Peoples R China

Blended collaborative learning has emerged as an effective pedagogical model that integrates face-to-face and online learning environments, offering a dynamic platform for deep learning-characterized by critical thinking, knowledge synthesis, and application. However, existing research offers mixed findings on how blended collaborative learning promotes deep learning, with little focus on the integrated roles of learner engagement (LE), self-regulated learning (SRL), and group interaction (GI). This study addresses this gap by developing and testing a structural equation model to explore the interplay between LE, SRL, and GI and their collective impact on deep learning outcomes. A sample of 450 learners from higher education institutions participated in this study, which used validated survey instruments to assess these constructs. The findings indicate that LE significantly influences deep learning both directly and indirectly through SRL and GI. SRL and GI were also found to sequentially mediate the relationship between LE and deep learning, underscoring the importance of both individual self-regulation and collaborative interaction in fostering deep learning in blended collaborative learning environments. Additionally, gender differences in these relationships were explored, revealing subtle variations in learning dynamics between male and female learners. The study contributes to the theoretical understanding of blended learning environments and offers practical implications for designing educational frameworks that promote meaningful and lasting learning experiences.

关键词： Blended learning Deep learning Self-regulated learning Group interaction structural equation modeling Learner engagement

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