This paper provides a comprehensive overview of evolution and innovation in social network analysis to the paradigm of social networking. It explains how the development of sociological theory and the structural prope...This paper provides a comprehensive overview of evolution and innovation in social network analysis to the paradigm of social networking. It explains how the development of sociological theory and the structural properties of social groups matter to computer science and communications. Authors such as Moreno, John Barnes and Harrison C. White provide evidence of a growing body of literature addressing the networking of people, organizations and communities to explain the structure of society. This perspective has passed from sociology to other fields, changing understandings of social phenomena. Social networks remain a potent concept for analyzing computer science and communications. This paper shows how and why this has occurred and examines substantive areas in which social network analysis has been applied—mainly how the advantages of graphic visualization and computer software packages have influenced SNA in different audiences and publics leading to the unfolding of social networking to different audiences and publics.展开更多
Purpose:This paper examines factors of payment decision as well as the role each factor plays in casual configurations leading to high payment intention under systematic and heuristic information processing routes.Des...Purpose:This paper examines factors of payment decision as well as the role each factor plays in casual configurations leading to high payment intention under systematic and heuristic information processing routes.Design/methodology/approach:Based on heuristic-systematic model(HSM),we propose a configurational analytic framework to investigate complex casual relationships between influencing factors and payment decision.In line with this approach,we use fuzzy-set qualitative comparative analysis(fsQCA)to analyze data crawled from Zhihu.com.Findings:The number of previous consultations is a necessary element in all five equivalent configurations which lead to high intention in payment decision.The heuristic processing route plays a core role while the systematic processing route plays a peripheral role in payment decision-making process.Research limitations:Research is limited in that moderating effect of professional fields has not been considered in the framework.Practical implications:Configurations in results can assist managers of knowledge communities and paid Q&A service providers in the management of information elements to motivate more payment decision.Originality/value:This paper is one of the few studies to apply HSM theory and fsQCA method with respect to the payment decision in paid Q&A.展开更多
Functional magnetic resonance imaging (fMRI) has been used to lateralize and localize lan-guage areas for pre-operative planning pur-poses. To identify the essential language areas from this kind of observation method...Functional magnetic resonance imaging (fMRI) has been used to lateralize and localize lan-guage areas for pre-operative planning pur-poses. To identify the essential language areas from this kind of observation method, we pro-pose an analysis strategy to combine fMRI data from two different tasks using probabilistic in-dependent component analysis (PICA). The assumption is that the independent compo-nents separated by PICA identify the networks activated by both tasks. The results from a study of twelve normal subjects showed that a language-specific component was consistently identified, with the participating networks sepa-rated into different components. Compared with a model-based method, PICA’s ability to capture the neural networks whose temporal activity may deviate from the task timing suggests that PICA may be more appropriate for analyzing language fMRI data with complex event-related paradigms, and may be particularly helpful for patient studies. This proposed strategy has the potential to improve the correlation between fMRI and invasive techniques which can dem-onstrate essential areas and which remain the clinical gold standard.展开更多
. In this article, we describe the characteristics of large-scale modeling of the theme text of this site data and important progress in recent years. Topic modeling approach has attracted wide interest in the world, .... In this article, we describe the characteristics of large-scale modeling of the theme text of this site data and important progress in recent years. Topic modeling approach has attracted wide interest in the world, and promote a number of important data mining, development of computer vision and computational biology applications, including automatic text summaries, information retrieval, information recommendation, topic detection and tracking, natural scene understanding human action recognition and gene expression analysis. The main features of the model and the corresponding theme paper focuses on the text of this site data. Data with dynamic, high-end, multi-channel and distributed structure and the structure of the model is only part of the theme before modeling. The paper discussed in the framework of the unity of the three-dimensional Markov model of four structural features of the text of this site data modeling, and analysis of distributed computing and word combination of three-dimensional modeling topics Markov model and type fuzzy systems the possibility of applications. In addition to structural modeling for this site text data, also we discuss some of the three-dimensional Markov model energy minimization of machine learning algorithms.展开更多
文摘This paper provides a comprehensive overview of evolution and innovation in social network analysis to the paradigm of social networking. It explains how the development of sociological theory and the structural properties of social groups matter to computer science and communications. Authors such as Moreno, John Barnes and Harrison C. White provide evidence of a growing body of literature addressing the networking of people, organizations and communities to explain the structure of society. This perspective has passed from sociology to other fields, changing understandings of social phenomena. Social networks remain a potent concept for analyzing computer science and communications. This paper shows how and why this has occurred and examines substantive areas in which social network analysis has been applied—mainly how the advantages of graphic visualization and computer software packages have influenced SNA in different audiences and publics leading to the unfolding of social networking to different audiences and publics.
基金National Natural Science Foundation of China(Grant No.71271087)。
文摘Purpose:This paper examines factors of payment decision as well as the role each factor plays in casual configurations leading to high payment intention under systematic and heuristic information processing routes.Design/methodology/approach:Based on heuristic-systematic model(HSM),we propose a configurational analytic framework to investigate complex casual relationships between influencing factors and payment decision.In line with this approach,we use fuzzy-set qualitative comparative analysis(fsQCA)to analyze data crawled from Zhihu.com.Findings:The number of previous consultations is a necessary element in all five equivalent configurations which lead to high intention in payment decision.The heuristic processing route plays a core role while the systematic processing route plays a peripheral role in payment decision-making process.Research limitations:Research is limited in that moderating effect of professional fields has not been considered in the framework.Practical implications:Configurations in results can assist managers of knowledge communities and paid Q&A service providers in the management of information elements to motivate more payment decision.Originality/value:This paper is one of the few studies to apply HSM theory and fsQCA method with respect to the payment decision in paid Q&A.
文摘Functional magnetic resonance imaging (fMRI) has been used to lateralize and localize lan-guage areas for pre-operative planning pur-poses. To identify the essential language areas from this kind of observation method, we pro-pose an analysis strategy to combine fMRI data from two different tasks using probabilistic in-dependent component analysis (PICA). The assumption is that the independent compo-nents separated by PICA identify the networks activated by both tasks. The results from a study of twelve normal subjects showed that a language-specific component was consistently identified, with the participating networks sepa-rated into different components. Compared with a model-based method, PICA’s ability to capture the neural networks whose temporal activity may deviate from the task timing suggests that PICA may be more appropriate for analyzing language fMRI data with complex event-related paradigms, and may be particularly helpful for patient studies. This proposed strategy has the potential to improve the correlation between fMRI and invasive techniques which can dem-onstrate essential areas and which remain the clinical gold standard.
文摘. In this article, we describe the characteristics of large-scale modeling of the theme text of this site data and important progress in recent years. Topic modeling approach has attracted wide interest in the world, and promote a number of important data mining, development of computer vision and computational biology applications, including automatic text summaries, information retrieval, information recommendation, topic detection and tracking, natural scene understanding human action recognition and gene expression analysis. The main features of the model and the corresponding theme paper focuses on the text of this site data. Data with dynamic, high-end, multi-channel and distributed structure and the structure of the model is only part of the theme before modeling. The paper discussed in the framework of the unity of the three-dimensional Markov model of four structural features of the text of this site data modeling, and analysis of distributed computing and word combination of three-dimensional modeling topics Markov model and type fuzzy systems the possibility of applications. In addition to structural modeling for this site text data, also we discuss some of the three-dimensional Markov model energy minimization of machine learning algorithms.
