[Purpose/significance] As“AI for Science”is increasingly viewed as the“fifth paradigm”of scientific re⁃search, Artificial Intelligence (AI) has begun to exert a profound impact on both the research processes and disciplinary boundaries of Information Resources Management (IRM). However, a comprehensive examination of AI’s applications and influences in IRM, from a holistic disciplinary perspective using systematic theoretical tools, remains lacking.Drawing upon the I-model theory, this paper investigates the key elements, underlying mechanisms, and future chal⁃lenges of AI-empowered IRM research, aiming to offer fresh perspectives for both academic inquiry and practice. [Method/process] Employing a literature review and representative case analyses, this study summarizes the core com⁃ponents and key pathways of AI-driven Information Resources Management (AI4IRM). It then utilizes the four dimen⁃sions of the I-model—information, technology, people, and organization/society—to analyze AI’s innovative applica⁃
tions in tasks such as information retrieval, knowledge discovery and management, as well as data processing and analy⁃sis. The paper also provides a comprehensive review of forthcoming trends and potential risks. [Result/conclusion]The findings reveal that AI holds substantial promise in enhancing information analysis accuracy, decision-support effi⁃ciency, and knowledge service capabilities. Nevertheless, significant challenges persist, particularly regarding data quality in large-scale datasets, algorithmic bias, privacy concerns, and ethical regulations. By illuminating the dynamic relationships and complexities inherent in AI-driven IRM, the I-model theory furnishes theoretical and practical foun⁃dations for advancing interdisciplinary research and informed decision-making in this evolving field.

[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] Artificial Intelligence (AI) has become a central issue in global technological devel⁃opment. The sociotechnical imaginaries formed in different countries, that is, the collective visions of the future of AI are profoundly shaping national policy formulation and development planning. This study conducts a comparative analy⁃sis of different region’s AI policy documents to uncover emotional orientations and policy trajectories. The findings aimto provide references for the formulation and refinement of AI policy in China. [Method/process] A total of 35 key AI policy documents published between 2016 and 2024 by China, the US, the UK, India, and the EU were selected for analysis. Using computational topic modeling and sentiment analysis, the study explores the sociotechnical imaginaries and sentiments reflected in these policy texts. [Result/conclusion] China, the US, the UK, India, and the EU placed strong emphasis on AI chip research and shared aspirations for AI to empower social development and enhance human well-being. Meanwhile, concerns about data misuse, algorithmic bias, and technical robustness and security vary in in⁃tensity. The Global South focus more on technological inclusion and economic transformation, while those in the Global North place greater emphasis on regulatory frameworks and risk mitigation. The Global North has generally exhibited a long-standing preference for a "governance-first" paradigm, while the Global South is transitioning from a "develop⁃ment-first" stance toward a more balanced approach that integrates both development and governance. Overall, the sen⁃timent expressed in AI policies has gradually shifted from optimism to a more neutral and cautious outlook.

[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.

[Purpose/significance] With the rapid development of technologies such as the Internet, cloud computing,big data and artificial intelligence, the impact of digital transformation on human happiness has gradually emerged.This paper aims to explore the conceptual connotation of digital happiness and construct a standardized evaluation in⁃dex system to provide theoretical basis and practical guidance for understanding and improving digital happiness.[Method/process] Through literature research, interview, qualitative text analysis and other methods, the evaluation in⁃dicators of digital happiness were comprehensively extracted, and the weight of each indicator was determined by the analytic hierarchy process, and a digital happiness evaluation index system was constructed. At the same time, based on this system, the digital happiness level questionnaire is designed, using the fuzzy comprehensive evaluation method to evaluate the current situation of the public's digital happiness. [Result/conclusion] Three main dimensions of digi⁃tal happiness were proposed in this paper: the positive use experience of digital products and services, the positive psy⁃chological function in the use of digital products and services, and the positive social mentality in the use of digital prod⁃
ucts and services. The public's digital happiness suffers from a lack of security, autonomy, and inclusion in digital soci⁃ety, which can be improved by strengthening digital society governance, optimizing product design, and enhancing user capabilities. This paper provides a new theoretical framework and assessment tool for evaluating and improving digital happiness, which can guide the governance of digital society and product design optimization.

[Purpose/significance] The rapid development of Generative Artificial Intelligence (GenAI) products has completely transformed the interaction patterns between humans and artificial intelligence. In-depth exploration of the motives and patterns of self-disclosure in user-GenAI interactions helps to understand the diversity and complexity of user self-disclosure in this context, providing a new perspective for exploring user information behavior in human-intel⁃ligence interaction. [Method/process] Based on the CASA paradigm, social penetration theory, and mind perception theory, systematic thematic analysis was conducted on interview data from 20 GenAI users. [Result/conclusion] The study found that the motives for self-disclosure in user-GenAI interactions can be divided into three dimensions: envi⁃ronmental, technological, and user-related. Moreover, the patterns of self-disclosure in user-GenAI interactions can be categorized into three types: increasing disclosure layer, stable disclosure layer, and decreasing disclosure layer. By ana⁃lyzing the motives and patterns of user self-disclosure, it provides references for optimizing "people-centered" GenAI design, which is helpful for more precise and effective experience optimization for different types of users.

[Purpose/significance] With the rapid advancement of generative AI technologies, prompts have transcend⁃ed their traditional role as mere human-computer interaction interfaces and have evolved into a core competency for navigating the digital age. [Method/process] This study systematically investigates the concept of prompt literacy, tak⁃ing the multifaceted nature of prompts as a logical starting point. Drawing on relevant perspectives from the school of so⁃cial informatics, it explores the theoretical underpinnings of prompt literacy in three dimensions—individual, system,and practice. It also explores practical approaches to improving prompt literacy across society from an interdisciplinary perspective. [Result/conclusion] As a crucial link between human-AI interaction and value co-creation, prompt liter⁃acy exhibits a dual character, encompassing both information practices and technological ethics. There is an urgent
need to develop a theoretical framework rooted in socio-technical practices. This study outlines several directions for future research, aiming to advance both the theoretical refinement and practical development of prompt literacy.

[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] 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] 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] 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] 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] In the digital age, with the rapid development of information and communication technology, the phenomenon of digital disconnection has been steadily emerging. This study endeavors to explore the mechanisms behind the formation and evolution of digital disconnection behavior from a dynamic perspective, thereby deepening the understanding of the interaction between technology and individuals. The findings aim to offer valuable insights for enhancing user experience and fostering digital literacy. [Method/process] We crawled 1205 posts and comments from five groups related to digital disconnection in the Douban community and combined them with the texts of 21 interviews, constructed a framework model using thematic analysis, and analyzed the relationship between various elements of the model in order to clarify the process mechanism. [Result/conclusion] In this study, we constructed a
model of the mechanism and process evolution of users’digital disconnection behavior, which dynamically represents the overall logic of“digital awakening - technology domestication-digital conflict and contradiction-evaluation and ad⁃justment”. Correspondingly, the interaction between users and technology shows an evolutionary trend of“technology domestication-technology compromise/technology resistance-technology reflection”. In addition, this study identified three evolutionary pathways of digital disconnection: the short-term relief model, the rational optimization model, and the deep trade-off model.

[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] While the digitisation of public cultural services may facilitate users' access to cul⁃tural resources, it also raises the threshold of access to public cultural services, placing a burden on elderly users. This paper is proposed to eliminate the digital burden of elderly users under the digitalisation of public cultural services, to protect the digital cultural rights and interests of elderly users, and to promote the development of equalisation of public cultural services. [Method/process] The article mainly explores the formation mechanism of digital burden of elderly users in the context of digitisation of public cultural services, and puts forward the influence hypothesis of digital bur⁃den of elderly users based on cognitive load theory. Taking the National Cultural Cloud as an example, the question⁃naire survey method is used to collect data, the hypothesised paths are tested by structural equation modelling, and the
model stability test is conducted using artificial neural network. [Result/conclusion] The results show that information overload, task complexity and system design overload significantly exacerbate the digital burden of elderly users, while prior experience can effectively alleviate users' digital burden. Meanwhile, the ranking of the influence of each variable on digital burden is task complexity>system design overload>prior experience>information overload.

[Purpose/significance] Drawing on a series of theories from behavioral economics, we aim to construct a theoretical framework for user health information search mechanisms. [Method/process] Firstly, the behavioral eco⁃nomics theories in existing information search research are reviewed, along with their theoretical contributions to the field of information search research. Subsequently, four components of users' health information search mechanisms were identified: alternatives, outcomes, likelihoods and values. Based on these, four research dimensions of health infor⁃mation search were organized: search or not to search health information, formulating health information search strate⁃gies, selecting health information (sources), continue or stop searching health information. Furthermore, a theoretical framework for users' health information search mechanisms was constructed on this foundation. [Result/conclusion]This study comprehensively addresses the uncertainty in health information search and users' bounded rationality,thereby constructing a research framework that encompasses three subprocess mechanisms: the initiation and termina⁃tion mechanisms of users' health information search, the formation mechanisms of users' health information search
strategies, and the judgment and selection mechanisms of users' health information. These three subprocess mecha⁃nisms clarify the following points, respectively: firstly, users' health information search behaviour is inherently based on the weighing of search costs and benefits; secondly, as cognitive load increases, users develop heuristic search strate⁃gies to simplify health information search; and thirdly, users' judgments and selections of health information are ofteninfluenced by heuristics and various cognitive biases.

[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] 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] 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] 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] 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 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 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] Investigating the elements and mechanisms of digital detox behavior of mobile so⁃cial media users can help to enrich the information behavior model, provide theoretical and applied guidance for the indepth analysis of the digital detox behavior of mobile social media users, and ensure a healthy balance between the us⁃ers' normal life and the time they spend on digital devices. [Method/process] Based on the CAPS theoretical model framework, we analyze the elements of the digital detox behavior of mobile social media users from the four dimensions of "context-cognitive-emotional-behavioral", and we use the key event technology method to deeply excavate the in⁃trinsic mechanism of the behavior, and construct the mechanism-relationship model of the digital detox behavior of mo⁃bile social media users. model. [Result/conclusion] The mechanism of digital detox behavior of mobile social media us⁃
ers can be divided into four sub-mechanisms: situation-driven, cognitive connection, emotional regulation and behav⁃ioral response. The management strategies for digital detox behavior of mobile social media users include four aspects:seeking alternative activities and building real-life scenarios; taking the initiative instead of being passive and enhanc⁃ing self-awareness; establishing incentive mechanisms and strengthening positive emotions; using device functions torestrain behavioral habits.

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] 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] Multi-subject interaction has emerged as a prominent characteristic and develop⁃ment model in online chronic disease communities. Exploring the relational network structure characteristics and be⁃havioral patterns of multi-subject interaction in these communities can provide valuable insights for formulating target⁃ed strategies to promote multi-subject interaction and sustainable development of online chronic disease communities.[Method/process] Based on the analysis of the conceptual characteristics, interaction behavior models and interaction relationship models of multi-subject interaction in online chronic disease communities, a multi-subject interaction re⁃lationship network was constructed using sample data from the“Lymphoma House”. Subsequently, multi-dimensional network structure characteristic indicators were introduced to analyze the resilience, dynamic evolution features, and behavioral patterns of the multi-subject interaction. [Result/conclusion] The multi-subject of online chronic disease community participates in community interaction activities with cross-agent interaction mode, key subject-led interac⁃tion mode, multi-core subject interaction mode and mediator-coordinated interaction mode. Under these interaction models, a sparse relational network with relatively weak communication interactivity, low resilience, and dynamically evolving network structures has been established.

[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.