Regional differences in teaching and research exchange based on social network analysis: a case study of geography teachers in city A and county B of Jiangsu province

The study of logistics network of Yangtze River Delta city group can enable us to understand the logistics integration status. There are 25 cities in Yangtze River Delta Urban Agglomerations selected as the study object of this paper. The values of logistics links to those cities are calculated on the basis of the gravity model. Then, social network analysis method is used to analyze the logistics network density, centrality, cohesive subgroup and core–periphery structure. The research finds that the logistics connection between those cities is low; a few nodes have high degree of centrality and most of these nodes have little difference; there exists subgroup in the network, and the link density inside and between those subgroup are weak; the network has the core–periphery structure; both links inside the marginal area and links between the core area and the edge area are weak, so the network has vulnerabilities. Therefore, some measures need to be taken in in order to realize coordinative development of logistics in Silk Road Economic belt, including breaking the administrative constraints, taking the lead on the core nodes and strengthening the interaction between the edge region and the core region.

Dockless sharing bikes play an increasingly significant role in transit transfer, especially for the first/last mile. However, it is not always accessible for users to find sharing bicycles. The objective of this paper is to assess the accessibility of dockless sharing bikes from a network perspective, which would provide a decision-making basis not only for potential bike users but also for urban planners, policymakers, and bicycle suppliers to optimize sharing-bike systems. Considering bicycle travel characteristics, a hierarchical clustering algorithm was applied to construct the dockless sharing-bike network. The social network analysis (SNA) method was adopted to assess the accessibility of the bike network. Then, a spatial interaction model was chosen to conduct a correlation analysis to compare the accessibility obtained from the SNA approach. The case study of Shanghai indicates a strong connection between the accessibility and the SNA indicators with the correlation coefficient of 0.779, which demonstrates the feasibility of the proposed method. This paper contributes to a deep understanding of dockless sharing-bike network accessibility since the SNA approach considers both the interaction barriers and the network structure of a bicycle network. The developed methodology requires fewer data and is easy to operate. Thus, it can serve as a tool to facilitate the smart management of sharing bikes for improving a sustainable transportation system.

This paper is a case study on scientific research funds in colleges and universities in China and it introduces social network analysis to explore the structure of scientific research funds network. It analyses network’s degree, coreperiphery structure and cohesive subgroups, based on the data from http://www.people.com.cn. The analysis reveals that the scientific research funds network is in the stage of the formation, although there have been some influential members, but generally speaking, the network is more dispersed, with less subgroups. And the communication between the actors in the network is not frequent, even if in the subgroups. Keywordsnetwork public opinion; network structure; social network analysis; cohesive subgroup

Social network analysis and visualization is an active area of study but good organizations of social network information are lacking. This paper proposes a domain ontology model focusing on social network information, which abstracts the impersonal existences in social network information domain into some primary ontologies. According to the requirements of social network structure analysis, we propose a Subgroup Analysis Layout (SAL) algorithm based on domain ontology model. SAL algorithm analyzes the subgroups through the analysis of roles and key attributes. Then the results of subgroup analysis are used to improve the force directed layout algorithm in analyzing and visualizing the structure of social network. Results with the case of terrorist information demonstrate its advantages. A fine solution is to organize the social network data with domain ontology, and then develop layout algorithms based on it. Ontology is a formal explicit specification of a shared conce- ptualization(2). With the help of domain Ontology, we can organize the information and standardize the definitions fine in the field of social network analysis and visualization. Therefore, methods of social network analysis and new needs of social network visualization or analysis can be defined easily. In this paper, we propose a domain ontology model for field of social network visualization and analysis which abstract the imper- sonal existences in the field into some primary ontologies. To overcome the disadvantages of traditional force directed layout algorithms in analyzing and visualizing the structure of social network, we propose the Subgroup Analysis Layout (SAL) algorithm based on our domain ontology model.

The social network analysis has been actively applied in various tourist destinations, with a few studies on the tourism economic network structure of national parks. Taking the national parks in the Central Region of China as research objects, this study applies the modified gravity model to measure the strength of tourism economic connection. The social network analysis method (SNA) is used to analyze the network structure of tourism economic connection among national parks from the perspectives of overall network density, network centrality, and cohesive subgroups. The results show that the intensity of the tourism relationships among national parks in Central China is unbalanced in spatial distribution. The structure of tourism economic network presents a multi-core model. Lushan Mountain, Shaoshan, Wudang Mountain, and other national parks play a necessary role in the transmission of regional tourism economic elements. There are cohesive subgroups of connections among national parks, which are closely related to administrative divisions and regional cultural background. The subgroups of interior scenes in the same province are more closely related, and the degree of tourism integration still needs to be improved. The study advances the understanding of tourism economic network relationships among tourist attractions in a destination.

基于社会网络分析法的生态工业园典型案例研究

Since the 1970s, communication researchers have utilized social network analysis to understand mass, health, organizational, and interpersonal communication. This article introduces communication researchers to a new class of social network analysis methods, exponential random graph (p*) models. This new method represents the latest advancement in social network methodology and will enhance the trajectory of social network research in the communication discipline. The benefits of this class of models include allowing for the simultaneous estimation of attribute and structural parameters, accounting for the interdependent nature of network data, and retaining the complexity of network observations throughout the analysis. An example analysis using data from Shumate, Fulk, and Monge (2005) is provided to illustrate the potentials of exponential random graph modeling. Five different social network software programs capable of the analysis discussed in this article are introduced with regard to their respective benefits. Finally, a brief tutorial based on data from Palazzolo (2005) is given on how to conduct an ERGM analysis using the PNET software program.

The diplomatic relations with neighboring countries are critical for the regional stability and economic development for a country. China has considered neighboring countries as strategic partners and implemented diplomatic policies to promote harmony, prosperity and security of neighboring countries. Binational trade between countries is one driving factor that may influence the national relationship in the globalization era. Therefore, the trade relations between China and its neighboring countries are critical to understand China's geopolitical environment. This paper analyzes the trade relations between China and its neighboring countries using social network analysis(SNA) method. Drawing on the trade data between China and its neighbors in the years of 2001, 2006 and 2011, we analyze the economic dependence between China and its neighboring countries. Based on SNA method, we conduct the centrality analysis and structure equivalence analysis aiming to explore the trade network of China and its neighbors in various aspects. The results suggest that the trade dependence is unequal between China and its neighbors. The neighboring countries are more dependent on the trade with China, and the trade dependence of these countries on China was significantly increased from 2001 to2011. The trade network has an obvious core- periphery structure with China and Japan at the core positions. From 2001 to 2011, the degree centrality of China and its neighbors presents a power-law distribution pattern, which means China is at the center of the trade networks. Moreover, the degree centrality of China has grown fast and became the largest in 2011. The results suggest that China plays a leading role in the trade networks and has great economic influence over its neighboring countries. This research shows that SNA method has a great potential in further geopolitical research.

Spatial association of coastal towns and villages in Funing District, Qinhuangdao: A study using social network analysis

This study aims to explore the dynamics of the network of short-term study abroad (STSA) programs among Chinese 985 Project universities by employing the method of social network analysis (SNA). With the application of a two-mode network framework (comprising Chinese universities and foreign partner institutions), archival data from 39 official university websites were collected and analyzed to map the patterns of STSA program collaborations. Key metrics include network centrality, clustering, and core-periphery structure. The results show that the STSA programs among Chinese 985 Project universities are generally rich in number and diversity. It displays a centralized structure in regard to the collection of foreign universities: the network is highly connected in general, with an apparent sign of core and periphery members in the network. Its short average path length and high clustering coefficient align with the character of small-world network in the academic community. It also indicates that when Chinese 985 universities are choosing their foreign STSA program partners, there is a high similarity among their choices since English-speaking countries are in the dominant position.

This article focuses on the basic concepts, questions and the organization development oriented applications of the Social Network Analysis (SNA) method which has started to be used increasingly by different academicians and practitioners in the fields ranging from medical science to anthropology, from business management to human rights. In the application part of the research, intra-organizational networks of work-related information, advice, critical support and communication among employees in a bank branch were analyzed and mapped with Social Network Analysis method. By this way, potential fields of intervention in terms of organization development were identified and evaluated.

In order to improve the ability of planning, design and health evaluation of infrastructure, such as power, urban traffic and water supply and drainage, and to reduce the urban global risk caused by its failure. Give an example of Chongqing, Wanzhou electric power infrastructure, use social network analysis (SNA) theory and method, build power infrastructure status and network planning respectively, propose the network health evaluation system composed of network complete index and so on, use the network calculation models such as density to assess the health of network topology and its operating state. The empirical study shows, social network analysis method (SNA) can evaluate the network topology and the operation stability of the network objectively.

The purpose of this research is to examine activities carried out on Twitter, which is a social media platform, on April 2 Autism Awareness Day; network structure in Turkey and in a global context, interaction patterns, the important nodes, user profiles, hashtag usage, and social mode within the context of the Twitter messages and discourses. In the research, mixed research method was adopted, and social network analysis and content analysis methods were used. The sample constitutes a total of 16565 people with 2790 people from Turkey and 13775 people from all over the world. According to the findings in the sample and Turkey as well as the global clustered-community group structures has been observed that the structure of the network. When compared with global examples of effective institutions related to the ASD in Turkey in the global context, the process of institutions and corporate entities has been determined to be more effective. It is seen that especially famous people who are known in the global context are involved in the process in order to reach more audiences. It is found that hashtag use in Turkey is limited, for example, on the other hand, in a global context hashtag use is more diverse to reach different target groups Comparative concept maps revealed that fewer themes were issued in Turkey while there was a wide range of themes in the global context. Social mode is positive in both samples.

Models and Methods in Social Network Analysis, first published in 2005, presents the most important developments in quantitative models and methods for analyzing social network data that have appeared during the 1990s. Intended as a complement to Wasserman and Faust's Social Network Analysis: Methods and Applications, it is a collection of articles by leading methodologists reviewing advances in their particular areas of network methods. Reviewed are advances in network measurement, network sampling, the analysis of centrality, positional analysis or blockmodelling, the analysis of diffusion through networks, the analysis of affiliation or 'two-mode' networks, the theory of random graphs, dependence graphs, exponential families of random graphs, the analysis of longitudinal network data, graphical techniques for exploring network data, and software for the analysis of social networks.

In order to study the spatial structure characteristics and optimal layout of regional air logistics networks, a quantitative analysis system for the spatial structure of directed multivalued networks is constructed based on relational data using the social network analysis (SNA) method. Core-edge structure, cohesive subgroups, Burt’s structure hole, and topological analysis models were used. Characteristics of logistics spatial linkages of cities in the Yangtze River Economic Zone, the identification of logistics centre cities, and the construction of hub-and-spoke networks are explored, and the driving forces for the formation of logistics spatial linkage patterns are analysed using the Durbin model. The complexity of the designed model algorithm is investigated, and it is found that the comprehensive logistics capacity of the Yangtze River Economic Belt region is increasing year by year, and the strength of interregional linkages is also growing, showing a spatially divergent trend of “strong in the east and weak in the west”; the multicore network linkage pattern is obvious, and the structure of the spatial linkage network is gradually becoming more complex.