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The era of crowd network is coming and the research of its steady-state is of great importance. This paper aims to establish a crowd network simulation platform and maintaining the relative stability of multi-source dissemination systems.

With this simulation platform, this paper studies the characteristics of “emergence,” monitors the state of the system and according to the fixed point judges the system of steady-state conditions, then uses three control conditions and control methods to control the system status to acquire general rules for maintain the stability of multi-source information dissemination systems.

This paper establishes a novel steady-state maintenance simulation framework. It will be useful for achieving controllability to the evolution of information dissemination and simulating the effectiveness of control conditions for multi-source information dissemination systems.

This paper will help researchers to solve problems of public opinion control in multi-source information dissemination in crowd network.

The purpose of this paper is to present the METAL project, a French open learning analytics (LA) project for secondary school, that aims at improving the quality of teaching. The originality of METAL is that it relies on research through exploratory activities and focuses on all the aspects of a learning analytics environment.

This work introduces the different concerns of the project: collection and storage of multi-source data owned by a variety of stakeholders, selection and promotion of standards, design of an open-source LRS, conception of dashboards with their final users, trust, usability, design of explainable multi-source data-mining algorithms.

All the dimensions of METAL are presented, as well as the way they are approached: data sources, data storage, through the implementation of an LRS, design of dashboards for secondary school, based on co-design sessions data mining algorithms and experiments, in line with privacy and ethics concerns.

The issue of a global dissemination of LA at an institution level or at a broader level such as a territory or a study level is still a hot topic in the literature, and is one of the focus and originality of this paper, associated with the large spectrum of different concerns.

The purpose of this paper is to solve the problem of information privacy and security of social users. Mobile internet and social network are more and more deeply integrated into people’s daily life, especially under the interaction of the fierce development momentum of the Internet of Things and diversified personalized services, more and more private information of social users is exposed to the network environment actively or unintentionally. In addition, a large amount of social network data not only brings more benefits to network application providers, but also provides motivation for malicious attackers. Therefore, under the social network environment, the research on the privacy protection of user information has great theoretical and practical significance.

In this study, based on the social network analysis, combined with the attribute reduction idea of rough set theory, the generalized reduction concept based on multi-level rough set from the perspectives of positive region, information entropy and knowledge granularity of rough set theory were proposed. Furthermore, it was traversed on the basis of the hierarchical compatible granularity space of the original information system and the corresponding attribute values are coarsened. The selected test data sets were tested, and the experimental results were analyzed.

The results showed that the algorithm can guarantee the anonymity requirement of data publishing and improve the effect of classification modeling on anonymous data in social network environment.

In the test and verification of privacy protection algorithm and privacy protection scheme, the efficiency of algorithm and scheme needs to be tested on a larger data scale. However, the data in this study are not enough. In the following research, more data will be used for testing and verification.

In the context of social network, the hierarchical structure of data is introduced into rough set theory as domain knowledge by referring to human granulation cognitive mechanism, and rough set modeling for complex hierarchical data is studied for hierarchical data of decision table. The theoretical research results are applied to hierarchical decision rule mining and k-anonymous privacy protection data mining research, which enriches the connotation of rough set theory and has important theoretical and practical significance for further promoting the application of this theory. In addition, combined the theory of secure multi-party computing and the theory of attribute reduction in rough set, a privacy protection feature selection algorithm for multi-source decision table is proposed, which solves the privacy protection problem of feature selection in distributed environment. It provides a set of effective rough set feature selection method for privacy protection classification mining in distributed environment, which has practical application value for promoting the development of privacy protection data mining.

In this study, the proposed algorithm and scheme can effectively protect the privacy of social network data, ensure the availability of social network graph structure and realize the need of both protection and sharing of user attributes and relational data.

Mountbatten offers a vivid description of the current‐awareness function using the analogy of a very wide conveyor‐belt, representing the information publishers, on which books, periodicals and reports appear at random: ‘The searcher is on a platform just above the belt and as the information material passes underneath he can pick up and read anything that he thinks might be of interest to him. You can imagine his frustration as he realises that for every item he takes time to examine, hundreds of others of possible interest to him have passed by’. Personality and environment will determine whether the individual can find an intelligent compromise between the extremes of neurosis induced by worrying about the material he is missing, or complacency with any system which produces one or two interesting items.

Innovativeness is crucial for industrial cluster firms to gain sustained competitive advantage. This study aims to investigate the effects of inter-firm coopetition on firm innovativeness within a cluster and examines the moderating role of institutional support.

This research adopts an empirical survey method using multi-source data from 181 industrial cluster firms. Regression is used to test the hypotheses of this study.

The results show that cooperation and constructive conflict promote firm innovativeness, while destructive conflict is detrimental to firm innovativeness. Moreover, the study also finds that cooperation interacts with both types of conflict to affect firm innovativeness, where cooperation and constructive conflict interact negatively on firm innovativeness, while cooperation and destructive conflict interact positively on firm innovativeness. In addition, institutional support weakens the effects of cooperation and destructive conflict on innovativeness, respectively, but has no significant moderating effect on the relationship between constructive conflict and innovativeness.

These findings enrich the current research on coopetition. The interaction effects of cooperation and both types of conflict on innovativeness deepen the concept of coopetition and responds to the call to further explore the interaction effects within coopetition. The moderating role of institutional support fills a gap in the empirical research on the role of institutional factors affecting coopetition on innovation and also provides valuable suggestions for firm managers and governments in industrial clusters.

The purpose of this article is to contribute to the digital development and utilization of China’s intangible cultural heritage resources, research on the theft of intangible cultural heritage resources and knowledge integration based on linked data is proposed to promote the standardized description of intangible cultural heritage knowledge and realize the digital dissemination and development of intangible cultural heritage.

In this study, firstly, the knowledge organization theory and semantic Web technology are used to describe the intangible cultural heritage digital resource objects in metadata specifications. Secondly, the ontology theory and technical methods are used to build a conceptual model of the intangible cultural resources field and determine the concept sets and hierarchical relationships in this field. Finally, the semantic Web technology is used to establish semantic associations between intangible cultural heritage resource knowledge.

The study findings indicate that the knowledge organization of intangible cultural heritage resources constructed in this study provides a solution for the digital development of intangible cultural heritage in China. It also provides semantic retrieval with better knowledge granularity and helps to visualize the knowledge content of intangible cultural heritage.

This study summarizes and provides significant theoretical and practical value for the digital development of intangible cultural heritage and the resource description and knowledge fusion of intangible cultural heritage can help to discover the semantic relationship of intangible cultural heritage in multiple dimensions and levels.

New product development team learning is important in today’s turbulent and uncertain markets and technologies. However, the literature treats team learning as a single construct, ignoring its multi‐dimensionality. In this study, we develop a multi‐dimensional team learning framework based on socio‐cognitive constructs. By studying 124 new product development projects, we show empirically that learning in new product development is best conceived as a multi‐dimensional structure with nine correlated but distinct constructs including: information acquisition, information implementation, information dissemination, unlearning, thinking, improvisation, memory, intelligence and sensemaking. Further, we demonstrate that a model based on the multi‐dimensionality of team learning provides a more robust explanation of new product success than does a unidimensional team learning model.

The Crickhowell Innovations Forum seeks to develop the concept of the Community Office as an intelligent human interface to encourage the personal, business and domestic telematic acumen of the individual, set against the background of the sustainable development of local communities within the context of a Local Agenda 21 project. The focus will be: to create a human interface to serve metropolitan, urban and rural locations that decreases the cognitive load of users and addresses the problem of potential information overload; and to extend existing and developing multimedia library services and systems as a new paradigm which enables information access in the widest sense.

To demonstrate that stakeholder analysis has a significant contribution to make as a “middle ground” research method and as a means of organisational change.

A case study of performance appraisal in UK academic institutions uses stakeholder analysis to address issues of organisation performance and development in a way that bridges the divide between theory and practice. This approach is supported by locating stakeholder theory within modes of organisation enquiry, and by positioning it more specifically within its conceptual domain.

Demonstrates the integrity and value of stakeholder analysis as a “middle ground” research method via development of a stakeholder systems model that identifies design, operation and evaluation stages of the performance management process and links these to measures of effectiveness and equity.

“Joined up thinking” in organisation analysis implies incorporation of quantitative and qualitative research methods in a holistic method of organisation enquiry. Stakeholder analysis illustrates how different research philosophies and methods can be combined in a pragmatic but robust way.

The stakeholder systems model builds on the concept of multi‐source approaches to performance appraisal. Both broaden the basis of assessment by incorporating stakeholder perspectives but, while the former seeks stakeholder consensus at the evaluation stage, the later incorporates multi‐source (stakeholder) perspectives on design, process and evaluation stages and on the system as a whole.

The paper demonstrates how stakeholder theory can draw from the conceptual clarity and intellectual rigour of “objective” epistemologies while retaining acceptance of the “soft”, unstructured and value‐based nature of organisation problems.

The increase of turbulence sources and risk points under the complex social information network has brought severe challenges. This paper discusses risk perception and intelligent decision-making under the complex social information network to maintain social security and financial security.

Cross-modal semantic fusion and social risk perception, temporal knowledge graph and analysis, complex social network intelligent decision-making methods have been studied. A big data computing platform of software and hardware integration for security combat is constructed based on the technical support.

The software and hardware integration platform driven by big data can realize joint identification of significant risks, intelligent analysis and large-scale group decision-making.

The integrated platform can monitor the abnormal operation and potential associated risks of Listed Companies in real-time, reduce information asymmetry and accounting costs and improve the capital market's ability to serve the real economy. It can also provide critical technical support and decision support in necessary public opinion monitoring and control business.

In this paper, the theory of knowledge-enhanced multi-modal multi-granularity dynamic risk analysis and intelligent group decision-making and the idea of an inference think tank (I-aid-S) is proposed. New technologies and methods, such as association analysis, time series evolution and super large-scale group decision-making, have been established. It's also applied in behavior and situation deduction, public opinion and finance and provides real-time, dynamic, fast and high-quality think tank services.