Abstract
This study examines intellectual property and copyright norms on scholarly social networks, explicates their socio-cultural implications for students’ information-seeking behavior, and proposes strategies to strengthen information ethics. A concurrent mixed-methods design was employed: 23 semi-structured interviews analyzed via grounded theory (MAXQDA 2020) informed a 68-item survey, and quantitative data from 424 graduate students were analyzed using SPSS and SmartPLS (PLS-SEM) with mediation testing. Findings indicate a positive, significant association between copyright compliance and ethical information-seeking, with “quality of virtual environment use”—comprising information literacy, critical evaluation, and attribution understanding—acting as a substantive mediator. Moreover, insufficient targeted training and ambiguous platform/institutional policies are associated with unethical behaviors. The conclusions underscore a “law–education–technology” package, balancing openness and privacy, policy transparency, Creative Commons licensing, and design nudges to enhance attribution and scholarly trust. The study’s innovation lies in developing and testing a causal model that links formal/informal IP norms of platforms to search, evaluation, version-sharing, and citation patterns, while assessing socio-cultural mediators in real-world networked contexts.
Keywords: Intellectual property norms, Copyright, Scholarly social networks, Students’ information-seeking behavior.
 
Introduction
In an increasingly digitized knowledge ecosystem, academic social networks blur boundaries of authorship, attribution, and reuse, generating uncertainty around intellectual property and copyright that shapes graduate students’ everyday information-seeking behavior. From a socio-cultural information ethics lens, the study examines how formal and informal platform norms around authors’ rights influence search, evaluation, version sharing (preprint/accepted/final), and citation practices. To bridge the gap between macro-level copyright debates and micro-level practices, a causal model is developed in which compliance with authors’ rights promotes ethical information-seeking directly and indirectly via the quality of virtual environment use. This mediator is operationalized through information literacy, critical evaluation, and attribution understanding, reflecting both skill enactment and norm internalization. Relationships are situated within socio-cultural mediators—descriptive and injunctive norms, perceived costs of violation, fairness, and reputation—as well as constraints such as policy ambiguity and training deficits. Conceptually, the work integrates ethical, legal, and behavioral perspectives; methodologically, it pairs qualitative theory-building with quantitative causal testing; practically, it informs platform and institutional governance for responsible, trustworthy scholarly communication.
 
 
Materials & Methods
A concurrent mixed-methods design was employed. The qualitative strand comprised 23 semi-structured expert interviews across information science, information ethics, AI, and information-seeking, analyzed using grounded theory (Strauss–Corbin) in MAXQDA 2020 to theoretical saturation and inter-coder agreement procedures (κ reported). Emergent categories informed a 68-item Likert instrument whose content validity was established by 10 experts (CVI = 0.92) and refined through a 50-participant pilot. The quantitative sample included 424 humanities graduate students from top-ranked national universities, selected via stratified random sampling across institutional and demographic strata. Data preprocessing and descriptive analyses preceded PLS-SEM in SmartPLS, assessing measurement quality via factor loadings (≥ 0.70), AVE (≥ 0.50), internal consistency, Fornell–Larcker discriminant validity, and SRMR (< 0.08). The structural model tested the direct effect of copyright compliance on ethical information-seeking and an indirect path via quality of virtual environment use, with exploratory links to policy clarity, targeted training, and governance signals (e.g., licensing prompts, version labeling). Reflexivity memos, reliability checks, and transparent integration procedures supported rigor and traceability across strands.
 
Discussion & Result
Results show a positive, significant relationship between compliance with authors’ rights and ethical information-seeking, indicating that copyright norms function as behavioral constraints and epistemic cues that sharpen source selection, critical appraisal, and accurate attribution. The effect is substantively mediated by quality of virtual environment use: higher information literacy, stronger critical evaluation, and clearer attribution understanding amplify ethics-promoting outcomes, suggesting complementary pathways of skill enactment and norm internalization. Conversely, ambiguous platform or institutional policies and non-targeted training correlate with elevated risks of unethical practices, including incomplete attribution, permissive reuse assumptions, and indiscriminate version sharing, revealing misalignments between formal rules and networked routines. The study’s advance is a causal model linking platform-level formal/informal IP norms to concrete behavioral phases—search, evaluation, version sharing, and citation—while gauging socio-cultural mediators in situ. Translational implications converge on a coordinated law–education–technology package: clarify policies and versioning; embed copyright and attribution within information literacy curricula; promote standardized open licenses (e.g., Creative Commons); and deploy design nudges surfacing attribution, licensing, and rights at decision points.
 
Conclusion
The evidence supports a causal pathway in which compliance with authors’ rights enhances ethical information-seeking directly and through improved quality of virtual environment use, thereby aligning IP norms with routine scholarly practice on academic social networks. A pragmatic roadmap emerges: integrate policy transparency, targeted instruction, open licensing, explicit versioning, and interface-level nudges to strengthen trust, balance openness and privacy, and sustain ethical conduct in AI-augmented scholarly ecosystems.