[Purpose/significance] Reveal the generation mechanism of privacy leakage risks among users of medical e-commerce platforms and propose corresponding control strategies to enhance user privacy security in the medical ecommerce sector and safeguard user privacy rights. [Method/process] In-depth interview is conducted to collect ini⁃tial data. Using thematic analysis, the MOA and SOR frameworks are integrated to extract the influencing factors of pri⁃vacy leakage risks in medical e-commerce. The interrelations among these factors are mapped out, and a model for the generation and control mechanism of these risks is constructed. [Result/conclusion] Privacy disclosure motivation, pri⁃vacy protection environment, and privacy literacy, as stimuli, all indirectly influence users' privacy risk control behav⁃iors through the mediation of perceived privacy leakage risk. Furthermore, users' privacy cognitive psychology impacts their perception of privacy leakage risk, moderating the relationship between stimuli and perceived privacy leakage risk, as well as between perceived risk and risk control behaviors. Given this, the research proposes a range of data gov⁃ernance and privacy protection strategies from the dual perspectives of government and platform, including establishing a full lifecycle privacy protection mechanism and implementing graded labeling of privacy information.

[Purpose/significance] As the frontier of data utilization, the intelligence analysis still faces challenges such as decoupling of thinking and technology, the emergence of marginal effects, and poor adaptation between tasks and technologies in the fusion of multi-source and multi-modal data. It is urgent to explore the logical thinking and technical path for data fusion and utilization under the guidance of intelligence thinking and the traction of intelligence tasks. [Method/process] This paper clarifies the ubiquity, high dimensionality, dynamicity, complementarity and re⁃dundancy characteristics of multi-source and multi-modal data, and explains the multi-source and multi-modal data fusion for intelligence analysis from the perspective of information chain and information theory; based on the principle of "data is useful, available and utility", the underlying logic is constructed to form the basic idea of organic coordina⁃tion of intelligence tasks, data characteristics and system effectiveness; by embedding digital intelligence technology in⁃to the intelligence analysis process, a three-stage progressive multi-source and multi-modal data fusion technical path of "data resource preparation, multi-dimensional feature alignment, smart intelligence generation" is proposed. [Re⁃sult/conclusion] The research results provide strategic references and methodological guidelines for the fusion of multi-source and multi-modal data to empower intelligence practice, which is helpful to promote the deep mining of da⁃ta value and the digital-intelligent transformation of intelligence work.

编者按：2025年底，中国人民大学书报资料中心信息资源管理系列刊、图情档39青年学者沙龙与黑龙江大学信息管理学院共同发起了“2025年度中国信息资源管理学界学术‘热点’与‘冷点’”评选活动。40余家专业期刊媒体联合发布了本年度信息资源管理领域的学术“热点”与“亟待加强的研究议题”（“冷点”）评选结果。该活动围绕本领域年度学术前沿动态与潜在议题展开系统梳理与评议——其中，“热点”聚焦于领域内受到集中关注的研究趋势，而“冷点”则指向那些值得深入研究，但未引起学界充分重视，或未能深入研究的涉及知识体系建构的学科基础、深层问题，或社会实践需要理论支撑、解决方案的重要议题。“热点”彰显时代关切，“冷点”关乎学科根基，“冷”“热”交融共进，共同为中国自主的信息资源管理知识体系建构注入新动能与新活力。

[Purpose/significance] The conceptual connotation of the information cocoon, which is both tangible and in⁃tangible, has led to the bottleneck of inconsistent research conclusions and inability to integrate research results in quantitative methods based on conceptual descriptions. Therefore, abstracting the concept of information cocoon and gradually improving the quantitative methodology system becomes a reasonable choice that conforms to the laws of sci⁃entific development. [Method/process] Starting from the important issue of analyzing the form of information cocoons,this article reviews and summarizes the research results at home and abroad. From the perspectives of metaphorical con⁃cept setting, the possibility of multidimensional forms, ecological fallacies and reductionism in empirical research, and the inability to track the "behavior" of social media users, the reasons for the "formal but intangible" nature of informa⁃tion cocoons and related issues in the field are sorted out, and the necessity of abstracting the concept of information co⁃coons is explained. On this basis, based on the process characteristics of information cocoon formation, a conceptual ab⁃stract model of information cocoon is constructed using complex network domain knowledge, and the method of quanti⁃fying information cocoon through complex network domain knowledge is interpreted from three levels: selection homog⁃enization, content homogenization, and group homogenization. [Result/conclusion] This conceptual abstract model aims to innovatively achieve the first abstraction of the concept of information cocoon based on the connotation of the concept of "being tangible but intangible", forming a scientific, stable, and strongly generalized quantitative method for information cocoon.

[Purpose/significance] The rapid development of Generative Artificial Intelligence (GAI) technology, cou⁃pled with intensifying technological competition between China and the United States, has posed severe challenges to user privacy and data security. The study compares the privacy policies of GAI platforms in both countries, aiming to analyze their characteristics and differences, and provide useful insights for the sustainable and healthy development of AI applications in China. [Method/process] The study selects 20 representative privacy policy texts from GAI plat⁃forms in China and the U.S., employing LDA topic modeling and the PMC index model for quantitative analysis.Through topic extraction and consistency evaluation, it compares the strengths and features of privacy policies in both countries to inform policy optimization in China. [Result/conclusion] The findings show that Chinese platform policies
emphasize government-led design and full-process regulation, while U.S. policies focus more on market orientation, us⁃er autonomy, and legal remedies. Based on this, the study suggests that Chinese AI platforms should shift from a "defen⁃sive compliance" approach to "proactive rule-making", strengthen data lifecycle management, build a sound regulatory framework, and improve mechanisms for protecting user rights and addressing complaints, thereby enhancing the effec⁃tiveness of privacy governance and platform competitiveness.

[Purpose/significance] Frequent privacy leakage incidents and increasingly complex privacy control strate⁃gies have exacerbated user privacy fatigue, and exploring the formation mechanism of social media users' privacy fa⁃tigue can provide a theoretical reference for user cognitive load relief, privacy anxiety debugging and effective privacy protection strategy formulation. [Method/process] Combining cognitive load, cognitive bias and CAC theory, the forma⁃tion mechanism model of privacy fatigue of social media users was constructed, and the partial least squares structural equation model and fuzzy set qualitative comparative analysis method were used for empirical test and configuration analysis. [Result/conclusion] In terms of cognitive factors, overconfidence positively affects optimism bias, informa⁃tion overload, social overload and system function overload all positively affect emotional exhaustion, and system func⁃tion overload also has a positive impact on negative neglect. In terms of emotional factors, emotional exhaustion, nega⁃tive neglect and optimistic bias all positively affect user privacy fatigue, and optimistic bias not only has a positive im⁃pact on emotional exhaustion and negative neglect, but also positively affects privacy fatigue under the mediating effect of the two. In terms of configuration effect, the two antecedent configurations of information overload and social over⁃load will trigger user privacy fatigue. In addition, there was no significant difference in the effect of control variables such as demographics on social media users' privacy fatigue.

[Purpose/significance] Existing studies have investigated factors affecting privacy risks in human-AI inter⁃actions, but their conclusions vary widely. This study systematically reviews relevant empirical research to identify key influencing factors and potential moderators of privacy risk perception in human-AI interaction. [Method/process] A meta-analysis was conducted, screening 64 valid studies. Key factors affecting privacy risk perception were identified across four dimensions: AI interaction characteristics, user characteristics, privacy concerns, and privacy protection en⁃vironments, totaling 19 critical factors. Potential moderators were tested to identify sources of heterogeneity in the find⁃ings. [Result/conclusion] Factors across the four dimensions influence users’privacy risk perception to varying de⁃grees. Information sensitivity, privacy concerns, perceived threats, and anxiety exhibit strong correlations with privacy risk perception. AI characteristics, long-term orientation, uncertainty avoidance, and gender demonstrate significant moderating effects.

[Purpose/significance] Promoting the construction of elderly-friendly public cultural services is of great significance for enhancing the cultural sense of achievement and happiness of the elderly, and building a Chinese style active aging society. Systematically exploring the characteristics of current policies for elderly-friendly public cultural services in China, clarifying the structure and problems of policy tools, can provide reference for future policy optimiza⁃tion. [Method/process] This study constructs a three-dimensional analysis framework of“policy tools - elderly needspolicy implementers”from the perspective of policy tools, and uses content analysis to quantitatively analyze 66 policytexts released in China. [Result/conclusion] In terms of policy tools, supply oriented policy tools tend to focus on edu⁃cation and training, environmental policy tools have insufficient binding force, and the use of demand oriented policy tools is significantly insufficient. The attention of policy tools to the middle and low-level needs of elderly people should be strengthened. Policy tools have not fully utilized the functions of policy implementers. Based on this, the fol⁃lowing optimization strategies are proposed: (1)adjusting the layout of supply oriented policy subclasses to support the development of education and training; strengthening environmental policy tools and combining soft and hard measures⁃to create an elderly-friendly environment; enriching demand driven policy tools to attract multiple stakeholders to par⁃ticipate on a regular basis；(2)following the logic of low to high to meet the needs of the elderly；(3)promoting the diver⁃sification of policy implementers to fully leverage social forces.

[Purpose/significance] The digital transformation of healthcare services has exacerbated technological ad⁃aptation challenges among older adults. While existing studies emphasize age-related disparities in the digital divide,they neglect the interplay between biologically driven capability deprivation and techno-social factors. This study pro⁃poses the concept of“Age-Related Digital Dysfunction”(ARDD) and investigates its generative mechanisms to address theoretical gaps in understanding the“aging-technology antagonism”within digital inequality frameworks. [Method/process] Using a qualitative approach, semi-structured in-depth interviews were conducted with 38 older adults from five Chinese provinces/autonomous regions. Data focused on their experiences of digital barriers across healthcare workflows, along with their causal attributions and coping strategies. Thematic analysis and contextual interpretation were employed to identify ARDD’s manifestations and generative pathways. [Result/conclusion] The findings reveal
that ARDD manifests in three dimensions: operational dysfunction, informational dysfunction, and decision-making dysfunction. ARDD’s generative mechanism follows a“bio-techno-social”interactive model: age-related cognitive and physiological decline acts as a necessary precondition, while technology-exclusionary designs and deficiencies in social support systems jointly exacerbate systemic deprivation of capabilities. ARDD is thus defined as“a state of per⁃sistent capability deprivation wherein intrinsic functional decline due to aging, compounded by techno-social exclu⁃sion, impedes older adults’effective engagement with digital technologies in healthcare.”

[Purpose/significance] It is of great value to grasp the concept of government behavior and governance ac⁃curately, based on the dictionary method to construct a fine grain analysis of Chinese policy texts suitable for the open data environment. [Method/process] The words that reflect emotional intensity in policy texts are defined as tendency words, and their structural characteristics and semantic relevance are used to construct a tendency dictionary. First, the seed words are extracted according to the interpretation opinions of domain experts and combined with the point mutual information algorithm to expand the dictionary online. Secondly, based on the theory of formal concept analysis, the top⁃ic connotation of policy texts is defined and quantified, the hierarchical relationship between policy topics is mapped to the semantic relationship between words, and the synonymous tendency words with topic similarity are screened. Final⁃ly, the credibility and validity methods are used for empirical testing. [Result/conclusion] The propensity dictionary
has high accuracy and recall rate in the task of policy text emotion recognition, which is suitable for large-scale fine grain policy text analysis, and provides a reliable and novel quantitative tool for policy research and decision-making.

[Purpose/significance] With the diversification of online platforms, users are increasingly inclined to carry out information exchange activities across multiple platforms, therefore, focusing on cross-platform users, exploring their interaction types, identifying high-value interactions and analyzing the path of their formation are of great signifi⁃cance in understanding cross-platform users' information exchange behaviors. [Method/process] By aligning bloggers who have cross-platform interactions on representative social sharing platforms and short-video platforms, and obtain⁃ing all comments under the content they posted throughout the year of 2023, we implement the division of interaction types based on the K-means method to identify high-value interactions and analyze their formation paths. [Result/con⁃clusion] Two-way interactions between cross-platform bloggers and audiences can be divided into two categories: ac⁃tive interactions and loose interactions, both of which appear more often on the social sharing platforms. Active interac⁃tions are more frequent, involve a wider range of topics, and have a more intimate relationship than loose interactions,
which helps both parties to form social capital, and can be regarded as an online extension of interpersonal relation⁃ships, and is a high-value interaction. The formation of such high-value interaction needs to go through three stages:one-way attention, surface contact and mutual involvement, and there are three main formation paths: approval-contri⁃bution type, demand-exchange type and care-sharing type, among which approval-contribution type is the type that appears most frequently on social sharing platforms, demand-exchange type is the type that occurs the most on shortvideo platforms, and care-sharing type is the type that occurs less often on both platforms.

[Purpose/significance] In the context of digital information, the social function of information resource man⁃agement has changed from information resource provider to knowledge service innovator, social problem solver and cul⁃tural ecology builder, and the user information acquisition paradigm has changed from "search - screening" to "ques⁃tion - generation". Generative artificial intelligence represented by DeepSeek, as a new channel for information acqui⁃sition, is gradually regarded by users as an information service model similar to information resource management.[Method/process] Focusing on the phenomenon of the formation and exertion of the information resource management function of generative artificial intelligence, exploring its causes from multiple dimensions such as technology, society and cognition, analyzing the social benefits of generative artificial intelligence as an information channel under techno⁃logical advantages, and clarifying the resulting technology intermediary cognition and its alienation challenges. [Result/
conclusion] Explored the construction strategies of the human-machine collaborative cognitive ecosystem, provided references for solving the challenges brought by generative artificial intelligence in performing the function of informa⁃tion resource management and developing digital intelligence-driven information services.

[Purpose/significance] After experiencing unprecedented user growth, generative AI has encountered a sig⁃nificant decline in user scale for the first time. Identifying and analyzing the key factors influencing generative AI user discontinuance behavioris of great significance for optimizing user experience, enhancing user stickiness, and promot⁃ing the healthy development of the generative AI industry. [Method/process] This study used a combination of litera⁃ture survey and Delphi methods to systematically and comprehensively distill the influencing factors on discontinuance behavior among generative AI users, and identified and analyzed the key influencing factors using the DEMATEL meth⁃od. [Result/conclusion] The research findings indicate that: the discontinuance behavior of generative AI users is in⁃fluenced by 20 influencing factors in four dimensions: user factors, information factors, platform factors, and environ⁃mental factors; algorithmic literacy, degree of intelligence, degree of anthropomorphism, competitive environment and other 10 influencing factors are all key influencing factors of generative AI users′ discontinuance behavior; generative AI platform managers should reduce the occurrence of users′discontinuance behavior by deeply understanding users′ needs, improving users′ algorithmic literacy, establishing a social interaction platform and other aspects.

[Purpose/significance] The human-AI search context has significantly reshaped behavioral interactions and learning effect in learning-related search. This study aims to provide a comprehensive evaluation of learning effect and to examine how search tools and task types jointly influence learning outcomes. [Method/process] An experimen⁃tal method was adopted to design three types of learning-related search tasks: receptive, critical, and creative. Two kinds of search tools, traditional search engines and Generative AI (GenAI), were provided. Learning effect data were collected from users who completed different tasks with these tools. The analysis of learning effect was conducted from two perspectives: subjective learning experiences and objective learning outcomes.[Result/conclusion] Users′ learn⁃ing experiences were mainly influenced by task types, while the specific effect of the search tool used remained un⁃clear. In terms of learning outcomes, traditional search engines outperformed GenAI in receptive and critical tasks, par⁃ticularly in the number, coverage, and uniqueness of knowledge points as well as the depth of knowledge facets. For cre⁃ative tasks, however, both tools provided relatively limited support, with GenAI showing a slight advantage.

[Purpose/significance] With the rapid advancement of Generative Artificial Intelligence (GenAI) technolo⁃gy, the human-machine collaborative model in smart libraries has undergone innovative enhancements. This technolog⁃ical evolution has brought significant transformations across multiple dimensions, including service quality, resource al⁃location, and application scenarios, thereby providing an advanced technical foundation for the transformation and up⁃grading of smart libraries. [Method/process] Based on the extended information system continuous use model, media system dependence theory and user habit theory, the study analyzes the influencing factors and antecedents of users’ continuous use of generative AI-enabled smart library, and builds a conceptual model of influencing factors of user’s continuous use behavior of generative AI-enabled smart library. This paper studies how generative artificial intelli⁃
gence in the construction and development of smart library affects the user’s attitude and continuous use behavior un⁃der the application scenario, so as to provide a new research perspective and a theoretical framework for the user’s con⁃tinuous use of smart library. [Result/conclusion] The empirical results show that media dependence has significant positive effects on expectation validation and perceived usefulness. The degree of expected validation and perceived usefulness have significant positive effects on user satisfaction. The degree of expected validation and perceived useful⁃ness play a partial mediating role between media dependence and user satisfaction. User satisfaction plays a partial me⁃diating role between expectation confirmation degree and user’s continuous use behavior, and the effect is significant.However, the mediating effect of user satisfaction between perceived usefulness and continued usage behavior is not sta⁃tistically significant. User habit has a significant negative moderating effect on the relationship between expectation confirmation and user’s continuous use behavior. 

[Purpose/significance] Researching the adoption of government open data user information is conducive to enhancing the readability and accessibility of data, triggering users to focus their attention, and providing theoretical references for in-depth data value mining. [Method/process] Using the SOR (Stimulus-Organism-Response) frame⁃work as the analytical structure, and integrating the theories of narrative transportation, perceived value, trust, and at⁃tention-based view, this study analyzes narrative elements such as narrative content, structure, and data presentation methods, explores the moderating effect of attention allocation concentration, constructs a theoretical hypothesis model of factors influencing the willingness of government open data user information adoption, and empirically verifies the model through a survey of 572 government open data users. [Result/conclusion] The study shows that the narrative content, structure, and presentation methods of government open data positively affect cognitive trust and perceived val⁃ue, and perceived value positively affects cognitive trust. Both cognitive trust and perceived value positively affect user
information adoption willingness and play a mediating role in the process of influencing adoption willingness through the stimulus dimension. Attention allocation concentration positively moderates the impact of cognitive trust and per⁃ceived value on user information adoption willingness.

[Purpose/significance] The phenomenon of involution alters the individual's cognition of competitive pres⁃sure, generating irrational knowledge learning behaviors. Based on the SOR model, it is significant to reveal the intrin⁃sic mechanism of knowledge disconnection and identify the paradoxical relationship between knowledge disconnection and connection, so as to understand knowledge disconnection and intervene dynamically in order to promote the sus⁃tainable development of knowledge subjects and society. [Method/process] This study proposes the concept of knowl⁃edge disconnection based on digital disconnection related research, analyzes the triggering basis, reaction process and implementation strategy of knowledge disconnection, and explores the practical paradoxes of knowledge disconnection and builds a framework for solving the paradoxes on this basis. [Result/conclusion] There are three kinds of behavioral responses, namely filtered, defensive and ambiguous knowledge disconnection, to regulate the mental state and inner perception under multi-source conditioned stimuli. There are value paradoxes, emotional paradoxes and cognitive para⁃doxes in the process of knowledge disconnection practice, which are manifested in the opposing choices of knowledge
disconnection and connection, triggering individuals' paradoxical thinking. This study also constructs a paradoxes reso⁃lution framework that includes three processes: inclusive acceptance, harmonious adaptation, and dynamic synergy, in order to promote the realization of the dynamic balance and virtuous cycle of knowledge disconnection and connection.

[Purpose/significance] Analyzing the complexity of network public opinion in the context of generative arti⁃ficial intelligence and exploring the risk factors of intelligent generation network public opinion are of great signifi⁃cance for the governance and decision-making of network public opinion risks. [Method/process] This article uses the WSR methodology to construct an indicator system for network public opinion risk elements in three dimensions: physi⁃cal, rational, and human. At the same time, it combines fuzzy DEMATEL and AHPsortⅡ methods to measure and ana⁃lyze network public opinion risk, and uses the Chengdu demolition rumor incident as an empirical case for in-depth ex⁃ploration. [Result/conclusion] Based on empirical data results, this article proposes targeted risk management strate⁃gies for network public opinion from three levels: physical, physical, and human, aiming to provide valuable references for relevant departments and the public to enhance their ability to respond to network public opinion risks.

[Purpose/significance] This article designs targeted scene governance strategies to respond to complex gov⁃ernance needs. It improves the refinement and scenarization level of the governance of deepfake events public opinion information. It breaks through the limitations of the vertical depth and adaptation accuracy of existing governance strate⁃gies. [Method/process] By integrating risk management theory and scenario theory, this article takes the perception of public opinion information risk in deepfake events as the dependent variable, and forgery technology, public aware⁃ness, media dissemination, degree of harm, scope of impact, response capability, and regulatory norms as independent variables. It has constructed a model of influencing factors and causal driving factors for the perception of public opin⁃ion information risk in the AIGC era of deepfake events. [Result/conclusion] In personal privacy events, none of the variables constitute a necessary condition for high-risk perception. This article has obtained 16 configuration paths for
high-risk perception of public opinion information in deepfake events. It has refined three governance models: risk identification scene, risk assessment scene, and risk response scene, and proposed scene governance strategies for deepfake events public opinion information.

[Purpose/significance] With the rise of generative AI, its role as a social actor is reshaping the process of in⁃formation acquisition. Against the backdrop of the uncertainty arising from human to human proxy search, exploring the influence of uncertainty on human to machine proxy search behavior from the perspectives of positive and negative emo⁃tions is of great significance for the further development of this technology. [Method/process] Based on the motivation⁃al information management theory, a research model was constructed, and a total of 13 research hypotheses were pro⁃posed. The data were collected using the questionnaire survey method and the critical incident technique. The relevant model calculations were carried out through the partial least squares structural equation modeling. [Result/conclu⁃sion] This study first reveals the correlation between the uncertainty differences, the low matching between information and tasks, and individual emotions. That is, an increase in uncertainty differences enhances individuals' negative emo⁃
tions and, correspondingly, reduces positive emotions. Under the influence of negative emotions, users lower their eval⁃uation of expected outcomes and effectiveness, thereby suppressing human to machine proxy search behavior. Although the low matching between information and tasks has no significant impact on the emotional state, it positively promotes human to machine proxy search behavior. Emotions have no significant impact on the results of human to machine proxy search behavior.

[Purpose/significance] In the era of intelligence, the decision-making function of intelligence services is becoming more and more important in national security, and the research on national security intelligence services is of great significance at the national strategic level and in the field of information science research. [Method/process]This study proposes a national security scenario-based intelligence service model centered on scenarios. This study aims to utilize security data to perceive the demand-side scenarios for intelligence services, which in turn guide the construction of supply-side resources for intelligence services. Based on the matching of supply and demand, service solutions are generated to achieve scenario-based intelligence service responses. [Result/conclusion] By establishing a theoretical framework for a data fusion-driven national security scenario-based intelligence service model, we aim to
respond to the objective requirements of the national security strategy at the macro level, while providing innovative in⁃tegration paths for national security scenario-based intelligence services at the micro level.

[Purpose/significance] The purpose of this paper is to reveal the current status of health informatics re⁃search methods in the domestic information resource management perspective, to explore the characteristics of re⁃search methods applied under different research themes, and to provide a reference basis for the selection of research design methods in this field. [Method/process] Firstly, the study obtained 2154 academic paper abstract data from 61 journals in the field of information resource management from CNKI. Secondly, it utilized BERT model with data aug⁃mentation and the ChatGPT large language model for research method entity extraction. On this basis, a method entity co-occurrence network was constructed. The method entity clusters were classified according to the Louvain communi⁃ty detection algorithm. Finally, the BERTopic model was used to mine research themes and reveal the status of applica⁃
tion of method entities under each theme. [Result/conclusion] Health informatics research methodology entities are broadly categorized into empirical research methods, qualitative research methods, data intelligence and simulation methods, data collection methods and tools, modeling research methods, and information systems analysis and design methods, with significant differences in the distribution of research methods under different research themes. The re⁃sults of the study help to adapt research methods for discipline-specific problems and promote the combined applica⁃tion of multifaceted, mixed, and interdisciplinary methods in health informatics. 

[Purpose/significance] Exploring quality improvement strategies adapted to the characteristics of data fac⁃tors from the perspective of multiple stakeholders, ensuring the circulation and application of high-quality data factors,thereby promoting the high-quality development of the data factor market. [Method/process] From the perspective of market self-governance, this study investigates the strategic choices of the data trading platforms, data suppliers, and data demanders under changing costs and benefits. By constructing an evolutionary game model, the study analyzes the interactions among the three stakeholders and their influencing factors. Finally, MATLAB software is used to simulate the dynamic process of strategy evolution under different conditions. [Result/conclusion] The active regulation of data trading platforms is influenced by both explicit and implicit benefits and regulatory costs. The decision-making of data suppliers regarding the provision of high-quality data depends on cost differentials as well as the platform's incentive and penalty mechanisms. The feedback costs and incentive intensity are key factors affecting the feedback behavior of data demanders. Effective platform regulation, a reasonable incentive and penalty mechanism, and the feedback from data demanders together contribute to a virtuous cycle that promotes the circulation of high-quality data elements.

[Purpose/significance] Cross-modality is one of the key attributes of generative artificial intelligence. This study employs a social semiotics perspective to conduct a micro-analysis of user-AI cross-modal interaction process⁃es, revealing the necessity and urgency of multimodal literacy education for users within the framework of AI literacy education. [Method/process] This study adopts mixed methods research, using questionnaires, participatory observa⁃tion, and multimodal discourse analysis to collectively demonstrate the significant roles of literary literacy, aesthetic lit⁃eracy, and other types of literacy in user-AI cross-modal interactions. [Result/conclusion] The current framework and content of AI literacy education should be deepened from four aspects: multimodal comprehension ability, cross-modal transformation ability, multimodal creation ability, and multimodal judgment ability；user-AI interactions exhibit the
characteristic of“transliteracy”, and creative interactions between users and AI require a broader and more interrelated set of literacy；the paradigm of AI literacy education should shift from“skills trainer”to“literacy architect”, the core competitiveness of future libraries will be reflected in the ability to integrate multiple types of literacy in educational practices.

[Purpose/significance] Currently, the scientific research big data is a major concern for the economic, so⁃cial, and technological development of various countries. Exploring its basic framework and correlative logic holds sig⁃nificant theoretical and practical value. [Method/process] This study grounded in a comprehensive review of the perti⁃nent theoretical foundations of the basic framework system for scientific research big data, transcends ecological and cy⁃bernetics theories and methods. Following systematic principles, it establishes the basic framework system for scientific research big data based on the concepts of "nascence-symbiosis-regeneration-parasitism". The basic framework sys⁃tem adheres to ecological principles. It considers "nascence" as the foundation, "symbiosis" as the guarantee, "regener⁃ation" as the key, and "parasitism" as a special case，employing process logic, time logic, functional logic, and formal logic as the logical domains, facilitating cyclical feedback and iterative optimization. [Result/conclusion] The theoreti⁃cal construction of the basic framework system for scientific research big data provides a novel perspective for the scien⁃tific research big data study, offering valuable guidance for the organization and management of the scientific research big data. In practical terms, the basic framework system for scientific research big data aids in the analysis, scrutiny,and mitigation of negative phenomena such as data monopolies, data fragmentation and data dormancy. This contribu⁃tion supports the establishment of a robust ecosystem of scientific research big data, fosters a sense of shared destiny within the scientific research big data community, revitalizes the vitality of research data, and establishes a firm founda⁃tion for harmonious symbiosis and mutually beneficial development among research entities at different levels.

[Purpose/significance] False short videos integrate multimodal content such as images, text, and audio,with their varying content structures potentially influencing the dissemination of short videos by manipulating user trust. Investigating the impact of multimodal content structure manipulation of false short videos on users′ sharing inten⁃sion aids in identifying false short videos and enhances platforms′ capacity to govern false information. [Method/pro⁃cess] Drawing upon SOR theory, this study constructed a research model in the context of false short videos: "informa⁃tion structure-perceived credibility-user attention-user sharing intention". Data was collected through a mixed-meth⁃ods approach combining questionnaires, eye-tracking experiments, and semi-structured interviews. [Result/conclu⁃sion] Users directed greater attention towards text areas than image areas, whilst exhibiting greater variability in atten⁃
tion distribution within image areas. Based on the structural manipulation of false short videos, this study found that the primary-secondary and parallel relationships exert a significant positive influence on perceived accuracy and consis⁃tency, while causal relationships exert a significant negative influence on perceived accuracy. Perceived accuracy ex⁃erts a significant positive influence on text fixation counts, image fixation counts, and image fixation duration. Text fixa⁃tion counts, image fixation counts, and image fixation duration exert a significant positive influence on users′ sharing in⁃tension.

[Purpose/significance] This study aims to clarify the concepts and concept relations between data manage⁃ment and data governance, address the current problems of confusion and misapplication of concepts and provide refer⁃ences for building and improving standard systems for data management and data governance in China, facilitating the adoption and appropriate application of international standards and promoting China's active participation in the formu⁃lation of international rules and standards in the digital field. [Method/process] This paper adopts the text content analysis method and analyzes the definitions of data management and data governance from online databases of ISO,IEC, and ITU-T, in accordance with principles of concept system building in ISO 704:2022. From these definitions, the concept objects, concept characteristics, and types of concept relations of data management and data governance are identified, respectively, and core concept relationship diagrams are constructed. The similarities and differences of con⁃
cepts between the two terms are compared across four dimensions: concept objects, concept characteristics, concept re⁃lations and application levels. [Result/conclusion] Data management involves micro and meso levels and encompasses comprehensive activities including data processing, processes management and value realization; data governance cov⁃ers micro, meso, and macro levels, emphasizing quality management, definition of rights and responsibilities, strategic coordination and policy formulation; both share common concerns about process elements and the realization of data value, presenting an associative relation.

[Purpose/significance] The rapid advancement of large language models（LLMs）has transformed tradition⁃al human-computer interaction. Investigating the characteristics of human-AI conversational interactions among uni⁃versity students in proactive mental health contexts can enhance our understanding of the complexity and diversity of user behaviors in such scenarios. [Method/process] Data were collected using the mobile experience sampling method (mESM). A total of 32 subjects were recruited for a two-week experiment on human-AI conversational interactions.Longitudinal data tracking was implemented through structured diary logs, while participants′ mental health status was assessed before and after the experiment using validated psychological scales. The experimental data were processed and analyzed through a combined approach of open coding and conversation analysis. [Result/conclusion] The study systematically examines the content characteristics of human-AI conversational interactions through three dimensions:user query features, AI response features, and AI interpretability features. It further analyzes behavioral characteristics through conversational structure features and "query-response" behavioral patterns, while also organizing features re⁃lated to mental health dimensions. Additionally, the study proposes three distinct modes of human-AI interaction: diag⁃nostic-consultative interaction, affective-interactive engagement, and cognitive-collaborative coordination.

[Purpose/significance] Investigating the pathway of user trust in deepfake videos can mitigate blind trust and provide theoretical support for the government and social media platforms to formulate deepfake risk governance strategies. [Method/process] The meta-analysis was used to determine the 12 elements affecting user trust in deep⁃fake videos. The fuzzy ISM and the MICMAC were combined to analyze the correlation pathways and classification rela⁃tionships of user trust in deepfake videos. [Result/conclusion] The pathways to user trust are categorized into literacydriven pathway, platform-environment dependency pathway, and information assessment pathway. Cognitive ability,awareness of deepfakes, and informational cues constitute foundational factors exerting the most profound influence. In⁃ternalization of personal literacy, optimization of the information ecosystem, and reinforcement of external cues are key dimensions for reducing user trust in deepfake videos.

[Purpose/significance] Generative AI search engines are becoming the most frequently used and most dis⁃cussed search platforms. However, there remains limited understanding regarding the effectiveness of their system de⁃sign, their ability to support diverse task types, and their capacity to enhance search outcomes for individuals with dif⁃ferent learning styles. This study addresses these gaps to supplement research on search behavior and effectiveness within generative AI search environments in the field of interactive information retrieval. [Method/process] Based on a hierarchical interaction model, we used the New Bing website as our experimental system to investigate the relation⁃ship between system interactions (information resources, page presentation, and technical characteristics) and search effectiveness. We also examined how different task types (factual and exploratory) and learning styles (divergent, con⁃vergent, assimilative, and accommodative) influence user search behavior and search outcomes. [Result/conclusion] Most system interaction metrics correlate positively with search effectiveness at the user level, while cost- benefit search effectiveness relates solely to page layout and typography. Participants demonstrated richer search behaviors and superior search outcomes during factual tasks. Furthermore, significant differences in search behaviors emerged across the four learning styles, primarily reflected in query restructuring frequency and types. Search effectiveness vari⁃ations were equally pronounced, with participants exhibiting divergent learning styles reporting superior experiences in both quality satisfaction and perceived value.