A Fuzzy Social Network Analysis Method and a Case Study on Tianya

Social networking service (SNS) has become online service platforms that focus on facilitating the building of social networks among people who share interests, activities, backgrounds, or real-life connections and has had a rapid development in China in the past few years. This paper aims to develop a fuzzy social network service analysis method, which combines graph theory with related fuzzy approach, to analyze the social network structural features and the distribution characteristics of interpersonal nodes in SNS community. A case study on a very famous Chinese tourism BBS-Tianya-is conducted to illustrate and validate the proposed approach. The research findings are as follows: (1) The attraction degrees of various areas in the forum are significantly different; (2) interpersonal nodes in the forum are concentrated relatively; (3) the fuzzy out-degrees and the fuzzy in-degrees of interpersonal nodes in the forum conflict each other; and (4) the distribution of interpersonal nodes is influenced by geographical relations. These findings can directly support social network service management and particularly tourism online service developments. © Springer-Verlag Berlin Heidelberg 2014

Spillovers and proximity in perspective: a network approach to improving the operationalisation of proximity

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A Fuzzy Social Network Analysis Method and a Case Study on Tianya Tourism Forum in China

Abstract. Social networking service (SNS) has become online service platforms that focus on facilitating the building of social networks among people who share interests, activities, backgrounds or real-life connections, and has had a rapid development in China in the past few years. This paper aims to develop a fuzzy social network service analysis method, which combines graph-theory with related fuzzy approach, to analyze the social network structural features and the distribution characteristics of interpersonal nodes in SNS community. A case study on a very famous Chinese tourism BBS -Tianya is conducted to illustrate and validate the proposed approach. The research findings are: 1) the attraction degrees of various areas in the forum are significantly different; 2) interpersonal nodes in the forum are concentrated relatively; 3) the fuzzy out-degrees and the fuzzy indegrees of interpersonal nodes in the forum conflict with each other; 4) the distribution of interpersonal nodes is influenced by geographical relations. These findings can directly support social network service management and particularly tourism online service developments

A model for simulating spreading processes based on social interactions in complex networks: case studies on online social networks and epidemics

Tese (doutorado) - Universidade Federal de Santa Catarina, Centro Tecnológico, Programa de Pós-Graduação em Engenharia de Automação e Sistemas, Florianópolis, 2023.Esta tese foi motivada por dois problemas relacionados aos processos de espalhamento: a desinformação sendo disseminada em Redes Sociais Online (OSNs) e as doenças infecciosas sendo transmitidas em uma população suscetível. O principal objetivo do presente trabalho é desenvolver um modelo para simular processos de espalhamento baseado em interações sociais e que permita abordar tanto a estrutura complexa das redes, como os comportamentos evolutivos dos agentes em um nível microscópico. Para tanto, é fornecido um modelo genérico para interações sociais assíncronas entre agentes, o qual é estendido tanto para a troca de informações como para os casos de transmissão de doenças. Um modelo de evolução da infecção é construído, dispondo de transições probabilísticas entre os estágios, permitindo o uso de dados do mundo real de forma direta. Esse modelo de troca de informações pode tratar conjuntos finitos de informações, diferentemente dos modelos da literatura de dinâmica de opinião. Também, neste último estudo de caso, outros fatores que impactam a disseminação são considerados, como a autoestima da pessoa e a confiabilidade da informação. Ambos os fatores são modelados como uma extensão do modelo anterior, porém, admitindo matrizes dinâmicas para as probabilidades das interações. Métricas para capturar informações relevantes sobre a estrutura de redes complexas grandes são estudadas, concluindo que a centralidade de autovetor está intimamente relacionada à velocidade de propagação e à probabilidade de uma determinada informação prevalecer sobre as demais no modelo proposto. Estruturas de rede estáticas e dinâmicas são construídas para representar cenários relevantes em ambos os estudos de caso, as quais são baseadas em modelos de redes complexas encontrados na literatura. Além disso, um algoritmo de clusterização é modificado para identificar comunidades em redes sociais. Este algoritmo alterado é capaz de evitar erros que foram identificados na utilização de algoritmos da literatura. Por fim, conhecer como se dá a divisão em comunidades de uma rede social, e alguma métrica de centralidade sobre os agentes, permite que políticas para controlar a disseminação de informações nas OSNs sejam propostas.Abstract: This thesis is motivated by two problems related to spreading processes: misinformation being disseminated in Online Social Networks (OSNs), and infectious diseases being transmitted in a susceptible population. The main objective of the present work is developing a model for simulating spreading processes based on social interactions, which address both the networks' complex structure and the evolving behaviors of the agents on a microscopic level. To this purpose, we provide a generic model for asynchronous social interactions between agents, which is extended for both the information exchange and the disease transmission cases. We build a model for infection evolution with probabilistic transitions between stages, allowing the usage of real-world data in a straightforward way. Our information exchange model can handle finite sets of information, differently from the models in the opinion dynamics literature. Also, in this last case study, we considered other factors that impact the spreading, like the person's self-esteem and the information's reliability. We model both factors as an extension from the previous one, by admitting dynamic matrices for the interactions' probabilities. We study metrics for capturing relevant information on the structure of large and complex networks, concluding that eigenvector centrality is intimately related to the spreading speed and the probability of a given information prevailing over the others in our model. We construct static and dynamic network structures representing meaningful scenarios for both case studies, which rely on complex network models from the literature. Further, we present the modification for a clustering algorithm to identify communities in social networks. This amended algorithm can avoid errors in the clustering that we have identified while using algorithms from the literature. Finally, we show that knowing how a social network is divided into communities, and some centrality metrics about the agents, enable us for proposing policies to control the spreading of information in OSNs

Teams as Complex Adaptive Systems: Reviewing 17 Years of Research

At the turn of the century Arrow, McGrath, and Berdahl (2000) portrayed teams as complex adaptive systems (CAS). And yet, despite broad agreement that this approach facilitates a better understanding of teams, it has only now been timidly incorporated into team research. To help fully incorporate the logic of teams as CAS in the science of teams, we review extant research on teams' approached from a nonlinear dynamical system theory. Using a systematic review approach, we selected 92 articles published over the last 17 years, in order to integrate what we know about teams as CAS. Our review reveals the evidence supporting teams as CAS, and the set of analytical techniques to analyze team data from this perspective. Our work contributes to teams' theory and practice by offering ways to identify both research methods and managing techniques that scholars and practitioners may apply to study and manage teams as CAS

Teams as Complex Adaptive Systems: Reviewing 17 Years of Research

At the turn of the century, Arrow, McGrath, and Berdahl portrayed teams as complex adaptive systems (CAS). And yet, despite broad agreement that this approach facilitates a better understanding of teams, it has only now been timidly incorporated into team research. To help fully incorporate the logic of teams as CAS in the science of teams, we review extant research on teams approached from a nonlinear dynamical system theory. Using a systematic review approach, we selected 92 articles published over the last 17 years to integrate what we know about teams as CAS. Our review reveals the evidence supporting teams as CAS, and the set of analytical techniques to analyze team data from this perspective. This review contributes to teams’ theory and practice by offering ways to identify both research methods and managing techniques that scholars and practitioners may apply to study and manage teams as CAS

Achieving high international market performance via simple vs complex configuration of international managerial network ties: A set theoretic approach across two countries

This study investigates the configuration of entrepreneurial capabilities, international managerial network ties and its performance effect among international ventures located in institutionally different contexts (Austria and Hungary). The study introduces and defines the concept of simple vs complex configuration of international managerial network ties and uses a set theoretic approach to assess the configuration of the above factors. The results of the fuzzy set analysis demonstrate that international ventures can fully capitalize on their entrepreneurial capabilities when they rely on a complex configuration of international managerial network ties. The findings also show that international ventures seek a balance between institutionally different contexts which may result in behaviors that are normally unacceptable by home country-related cultural and institutional norms. Finally, the results reveal that integrating exploration and exploitation strategies requires a complex configuration of international managerial network ties, which in turn leads to high IMP