28 August 2026, Volume 11 Issue 4

    

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  Design and Practice of an AI-Generated Text Detection System for Chinese Academic Contexts: A Case Study of the ScholarGuard Platform

  Liu Wei Chen Xiao yang Jin Jiaqin Liu Peng

  Journal of Information and Management. 2026, 11(4): 1-14.

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  Generative artificial intelligence is reshaping the production of academic texts. Conventional plagiarism detection based on textual similarity is increasingly insufficient for identifying AI-generated texts with original expressions. In Chinese academic contexts, the key issue is not merely whether the source of the text can be determined, but how uncertain detection signals can be transformed into interpretable and reviewable risk clues for human academic review. Taking the ScholarGuard platform as a case, this study develops a multi-source evidence fusion framework for Chinese academic text detection by integrating perplexity perturbation, statistical features, and BERT-based semantic discrimination. The detection results are represented through RiskScore, risk levels, and paragraph-level prompts. Based on an exploratory test set of 120 Chinese academic texts covering law, political science, economics, and sociology, the study evaluates the system in terms of overall performance, disciplinary differences, baseline comparison, and ablation results. Under controlled test conditions, ScholarGuard achieves an accuracy of 82.5%, a precision of 86.3%, a recall of 78.3%, an F1 score of 82.1%,and an AUROC of 0.89. The results suggest that multi-source evidence fusion can improve the stability of AI-generated text risk identification in Chinese academic contexts. However, detection results should not be used as an automatic basis for assigning responsibility. AI-generated text detection is more appropriately positioned as a risk-indication tool in academic information quality governance, supporting source transparency, human verification, editorial review, and academic integrity management.
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  Memory of the Information Civilization: Theoretical Construction and Practical Pathways for Digital Artifact Classification Standards

  Zhang Xiaopeng

  Journal of Information and Management. 2026, 11(4): 15-23.

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  Information products are entering historical heritage at an unprecedented pace. Yet the traditional museum classification system, grounded in tangible artifacts, materiality, antiquity, and scarcity, has proven inadequate when confronted with information civilization legacies—infinitely reproducible, immaterial entities whose core value derives from intellectual paradigms. From the perspective of living archaeology, this paper proposes a bipartite framework for digital artifacts, distinguishing between intangible paradigm legacies and tangible product legacies, and constructs a unified five-level classification system (Grade I–III Valuable Objects, General Objects, and Reference Objects). Through case studies of the von Neumann architecture, ENIAC, the TCP/IP protocol, original UNIX, and the first-generation iPhone, it demonstrates the theoretical validity of novel criteria including paradigm-shifting significance, historical milestone significance, and irreplaceability. This standard represents a rare systematic exploration globally, providing crucial theoretical support for expanding museum collection systems from industrial civilization to information civilization, with practical implications for collection expansion, exhibition narrative renewal, and digital heritage protection policy formulation.
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  Divergence and Convergence: A Theoretical Rethinking of the Library–Museum Relationship

  Zhang Qilin Li Chenxi

  Journal of Information and Management. 2026, 11(4): 24-34.

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  Library–Museum convergence has become a prominent topic in contemporary library and museum studies. Existing research often interprets digital technology as the primary driving factor behind such convergence, while overlooking the inherent force in the evolution of library–museum relations. Following the line of thought developed by Foucault and Bennett, this article proposes that shifts in the legitimacy demands of the existing social order constitute the core framework for explaining the separation and convergence of libraries and museums. The historical foundation of the library–museum unity is substantial, yet their subsequent separation resulted from differentiated demands for capacity legitimacy and narrative legitimacy, and was reinforced by professionalization across three dimensions: epistemology, institution, and spatial practices. The fundamental driving force behind contemporary library–museum convergence lies in the rise of cultural legitimacy demands. Libraries and museums will move toward convergence partially and conditionally beyond the boundaries of professionalization.
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  Constructing a Digital Literacy Framework for College Students in the AI Era

  Sheng Xiaoping Ge Qiao Lu Liyang Sheng Jiahao

  Journal of Information and Management. 2026, 11(4): 35-49.

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  The rapid development and widespread application of artificial intelligence (AI) have driven transformations in college students’ digital literacy, making it urgent to enhance their digital literacy in the AI era. Based on a review of typical domestic and international digital literacy frameworks, this paper defines the concept of college students’ digital literacy in the AI era. From a competency perspective, it puts forward seven research hypotheses and 46 sub-propositions concerning this digital literacy. These hypotheses and sub-propositions are verified using data collected from 492 valid questionnaires. On the basis of the verified results, this study ultimately constructs the Framework for College Students’Digital Literacy in the AI Era, which consists of 7 competency domains and 42 specific competencies. Adopting the core “competency domain-competency item” architecture from previous digital literacy frameworks, this framework systematically clarifies the connotation of each competency and integrates elements including data, information, artificial intelligence and information technology. It addresses the deficiency of traditional digital literacy frameworks that overlook AI-related skills, and breaks the limitation of existing AI literacy frameworks that focus merely on AI knowledge and skills. Furthermore,it realizes the integration and innovative development of AI literacy, data literacy, information literacy and computer literacy. The framework can serve as an effective guide for fostering and improving college students’ digital literacy in the AI era, and also facilitate the formulation of corresponding evaluation criteria and the implementation of relevant literacy assessments.
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  Contest Mechanisms for Cultivating Generative AI Literacy: A Case Study of the AIGC Track of the Shanghai Library Open Data Contest

  Chen Liqin Xiao Zheng Huang Guofan Zhang Chunjing Zhang Zheyu

  Journal of Information and Management. 2026, 11(4): 50-59.

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  The rapid proliferation of generative artificial intelligence (AI) is reshaping how the public acquires, produces,and organizes information, necessitating the construction of practical, contextualized, and evaluative AI literacy cultivation paths within libraries. Taking the AIGC track of the Shanghai Library Open Data Contest as a case study, this paper examines the correlations between contest mechanisms, work generation, and capability representation to deepen research on library AI literacy education. Based on 166 valid entries and public contest materials from the 2024 and 2025 contests, this studyutilizes case analysis, content analysis, descriptive statistics, and structured coding to analyze capability representations.The analysis focuses on four dimensions: prompt design maturity, tool orchestration and workflow complexity, task alignment, and evidence of reflection and governance awareness. The results demonstrate that library AIGC contests effectively activate explicit capabilities in tool recognition, task adaptation, prompt construction, multi-tool collaboration,and multimodal organization, serving as critical practical arenas for cultivating generative AI literacy. However, the advancement of implicit literacies—including principle understanding, ethical evaluation, and deep reflection—remains insufficient. Consequently, this paper proposes pathways such as deepening theoretical integration, optimizing contest mechanisms, and establishing long-term evaluation systems to enhance the educational efficacy and research interpretability of library-hosted contests.
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  Research on Knowledge Reorganization and Semantic Enhancement Paths for Chronicle Historical Materials Based on GraphRAG: A Case Study of the Chronicle of Soong Ching Ling

  Liu Peizhong Ruan Yijia Wang Xinyun

  Journal of Information and Management. 2026, 11(4): 60-74.

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  This study addresses the fragmentation of information caused by the linear narrative of chronicle historical materials, as well as the limitations of retrieval-augmented generation (RAG) technology in handling context severance and weak reasoning in long-term historical attribution. A path for knowledge reorganization and semantic enhancement of chronicle materials based on GraphRAG is proposed. A dual mechanism of “graph index + vector retrieval” is constructed. The method firstly achieves structured semantic stabilization through entry-level summarization and entity mapping.Secondly, it utilizes the topological structure of the knowledge graph to constrain the context generation of large language models (LLMs), designing multi-hop reasoning paths to connect discrete historical evidences. Taking the Chronicle of Soong Ching Ling as an empirical object, experimental results demonstrate that this method significantly improves the logical reasoning and interpretability of the system in addressing historical attribution issues spanning long periods, while ensuring the traceability of historical materials. This study provides a new methodological reference for the in-depth development of historical sources in the field of digital humanities.
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  Altmetrics Research from the Perspective of Open Science

  Li Jiachen Han Yi

  Journal of Information and Management. 2026, 11(4): 75-89.

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  From the perspective of open science, this study systematically looks at the background, development stages of Altmetrics and its intrinsic connection with open science; deeply explores its core issues, including data generation mechanism, data usability testing methods, and functional value model; further summarizes the shortcomings of current research and puts forward targeted future research directions. The research reveals the development context and key characteristics of Altmetrics, providing preliminary theoretical exploration and practical reference for its core issues. In the future, it is necessary to continuously deepen the research on the generation mechanism, functional and usability testing of Altmetrics to better balance the interests of all parties and promote the improvement and implementation of the Altmetrics science and technology evaluation system.
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  Research Progress and Review on Value Creation Driven by Data Elements

  Wu Dongdong

  Journal of Information and Management. 2026, 11(4): 90-100.

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  Against the backdrop of data being formally recognized as a novel factor of production and deeply embedded in socio-economic systems, systematically reviewing the research on value creation driven by data as a factor of production can provide scholarly support for the synergistic development of the digital economy and new quality productive forces. Based on CSSCI-indexed journal articles from CNKI, this study integrates bibliometric analysis (using CiteSpace and VOSviewer) with qualitative content analysis to conduct a systematic review of the value connotation, mechanisms,implementation pathways, and governance frameworks associated with data as a factor of production, examined through dual lenses: macro-level institutional evolution and micro-level corporate practice. This study reveals that a relatively comprehensive theoretical framework has emerged at the macro level, encompassing policy development, operational mechanisms, and governance architectures. At the micro level, while empirical studies preliminarily confirm the positive effects of data as a factor of production on firm-level value proxies—such as total factor productivity and innovation performance—research remains underdeveloped regarding multidimensional value creation mechanisms, heterogeneous implementation pathways, and the latent value embedded in unstructured data. This study contributes an integrated macromicro analytical framework that elucidates the dynamic interplay between policy evolution and academic discourse on data elements.