Social Network Analysis Methods Research Articles

The global cross-border mergers and acquisitions network between 1990 and 2021

Abstract The literature is characterized by a lack of research analyzing cross-border mergers and acquisitions (CBM&A) as a network. This article aims to evaluate the topology properties (the geographical and sectoral structure) of the global CBM&A network in 1990–2021. A quantitative study is conducted by using the social network analysis (SNA) method. The countries’ structural power in this global system is measured by the centrality indicators. From a geographical perspective, the study shows that in 1990–2021, the United States, the United Kingdom, Germany, Canada, and France occupied the most central place in the network. From the beginning of the 21st century, there has also been a marked increase in the importance of Asian countries, with China and India receiving a large inflow of foreign capital. In turn, entities from Hong Kong, Singapore, Japan, and China invested heavily abroad through M&A. The Asian countries’ economies also played the role of important intermediaries in the global CBM&A network. From a sectoral perspective, it can be stated that in 1990–2021, mainly entities operated in the financial, industrial, basic materials, technology, and consumer cyclical sectors made transactions in the global CBM&A network. They were also the main investment targets within this network.

Exploring the food-energy-water nexus in China's national industries: Insights from network structure and production disturbances

Understanding the food-energy-water nexus (FEWN) among industries' input–output activities is vital for the management of regional strategic resources. However, identifying key nexuses and quantifying their effects within an economy-wide dimension remain a challenge. This study integrated the frameworks of social network analysis (SNA) and computable general equilibrium (CGE) methods based on input–output data, presenting a new methodology to assess inter-industrial FEWN in China. Results indicated that: (1) Agriculture and catering industries were the principal food provision industries in the national economy. They also linked production activities among the food, energy, and water (FEW) sectors. (2) Fossil energy extraction industries with high betweenness centrality were the product circulation media in the industrial network. Their increased outputs could clearly boost domestic production. For instance, the yield of most national industries was expected to expand by 0.5 %–1.5 % due to a 10 % increase in coal supply. The electricity and petroleum processing industries with the highest response coefficients were the mainstays of China's economy. They exerted wide-ranging effects on other industries through short input–output paths. (3) Water-related industries could readily use products and services from other sectors and create demand-driven effects on FEW industries. In contrast, the output scale of national industries was not sensitive to changes in water input. These findings also highlighted the importance of conducting a FEWN evaluation within a balanced macroeconomic system. The proposed SNA–CGE analytical framework showcased good applicability and accuracy in the context of China and could serve as a reference method for FEWN research in other regions.

An analysis of cooperation networks related to research projects between universities in the Chungcheong region in Korea: Suggestions for strengthening university networks

Objective: The aim of this study is to obtain information regarding how 54 universities in the Chungcheong region of Korea are conducting joint research among themselves. More specifically, the study aims to understand the network characteristics and main patterns according to which universities in the Chungcheong region are conducting joint research, and to obtain the information necessary to utilize the network structure between universities as a strategy for future regional development.
 Design/Meghodology/Appraoch: For this purpose, we investigated the number of joint research projects conducted among these 54 universities in 2022, thereby obtaining the most up-to-date information possible. Network analysis was performed based on the surveyed data.
 Result/Discussion: The research results show that a total of five clusters exist in the Chungcheong area. The universities that play a central role include KAIST, Chungnam National University, Chungbuk National University, Kongju University and Korea National University of Transportation.
 Conclusions: Because these universities constitute important bases in the region and have close links with neighbouring universities, they are expected to play an important role in future regional development.
 Originality/Value: One of the academic implications of this study is that it applied social network analysis methods to research-related partnerships between universities in the Chungcheong region to identify universities that play an important key role.

ANALISIS BIBLIOMETRIK TERHADAP TREND RISET “HALAL TOURISM” MENGGUNAKAN VOSVIEWER

The aim of bibliometric analysis is mapping research trends by processing metadata from Google Scholar. This research also wants to know the research trend on "Halal Tourism" which uses the Social Network Analysis method. Research through searching the Google Scholar database with the keywords "Halal Tourism". Retrieval of metadata using the Publish or Perish (POP) application. The resulting data from PoP is then analyzed descriptively based on the year the publication was published, publisher name, researcher productivity and journal ranking. To obtain an accurate research development map, PoP data was exported to Excel CSV file format and result as RIS, CSV data was made into a private table and RIS data was analyzed using the VOSviewer (VV) application. Article search results show that the number of research publications in 2013 - 2023 was 997 papers. This research is visualized into a network and explained into 3 visualizations, namely Network Visualization, Overlay Visualization, Density Visualization. The results of this visualization can be used as a reference or as important information for researchers to see research trends on "Halal Tourism" and opportunities related to this topic in the future.

Linguistic Characteristics and Stylisation of Korean Cinema Based on the Social Network Analysis Method

Abstract Korean movies have consistently produced exceptional works that have triggered discussions and spread on social networks in recent years. In this paper, we take the movie language dissemination characteristics in social networks as an anchor point and combine the scale and structure of social networks to improve on the IC model to obtain a movie information dissemination model. This network model and the information cascade tandem are selected as the core of density peak clustering, and improvements are made for the updating rules as well as the propagation order of the multi-strategy labeling algorithm in the DCN algorithm. The characterization of movie language propagation in social networks is completed by using an improved algorithm with a multi-labeling idea. The overall stylistic evolution of Korean movies is examined, and then different language feature styles are compared according to social propagation. In the movie Memories of Murder, at 32 minutes and 23 seconds, which shows a rainy night on a muddy land and conveys the hardship of the protagonist’s situation through visual language, the propagation heat reaches 10.52. Similar to this sentence, the movie depicts a rainy night at 63 minutes and a crime scene at 108 minutes, with the propagation heat of the visual language reaching 19.48 and 23.48, respectively. Based on the propagation analysis of the social networks, the accurate capture of the unique impression of the movie language among the audience.

Predicting online participation and adoption of autism unproven interventions: a case study of dietary interventions

ABSTRACT Family caregivers of autistic children are susceptible to unconfirmed fads and false claims regarding to the efficacy of unproven interventions. This study aims to predict family caregivers’ participation and adoption of unproven interventions in online communities. Based on the Diffusion of Innovations theory, we first divided the family caregivers’ adoption process into five stages: awareness, persuasion, decision, implementation, and confirmation. Social network analysis and natural language processing methods were subsequently utilised to characterise personal, environmental, and behavioural factors for predicting the formation of last three stage. The results indicated promising evidence for the application of machine learning algorithms in predicting family caregivers’ decision (AUC = 0.823), implementation (AUC = 0.887), and confirmation (AUC = 0.921). Furthermore, the results showed that factors such as social interaction, social persuasion, and modelling significantly contributed to family caregivers’ online community participation and facilitated the adoption process of unproven interventions. Family caregivers with stronger negative emotions expressed were more likely to adopt unproven interventions and recommend these interventions to other community members, thereby accelerating the diffusion of these interventions.

Assessment of a Person's Social Success Through the Characteristics of Interpersonal Relationships in A Virtual Environment

The sudden spread of the COVID-19 pandemic has convincingly proved the role of social networks in human life activity as an actor of interpersonal relations. The need for isolation and the limitation of face-to-face communication between people has significantly transformed the system of interpersonal connections through an extensive increase in social contacts in the virtual environment and the growing importance of online social services. In the study, we addressed the problem of diagnosing the indicator of social success of a personality, reflecting characteristics of its interpersonal relations in offline activity through the attributes of its virtual activity in social networks. The research was based on the methods of social network analysis and traditional ways of psychodiagnostics. Social networks were analyzed using social graphs - mathematical models that describe the characteristics of relationships between users in social networks through various metrics (friends, elements, edges, density, closeness centrality, degree centrality, clustering coefficient, etc.). The study aims to prove the predictive validity of social graph indicators as predictors of personality social success through correlations of graph characteristics reflecting the features of interpersonal relations of a social network user in a virtual environment with the socio-psychological hands of traditional psychodiagnostic tools. The study included 601 subjects. Data was collected using psychological questionnaires and personal profiles from the social network VKontakte. The results of the study showed correlations between several characteristics of social graphs (density, clustering coefficient, closeness centrality, etc.) and several indicators of psychodiagnostic techniques (Dominance index in relationships with others, Organizational abilities, Desire for people, Narcissism, etc.). The significant contribution of the research is to expand the methodological apparatus of psychological science and to open new methods of predicting interpersonal relations of personality through its activity in a virtual environment.

Learning Analytics in Education: A Social Network-Based Approach for Analyzing the Interaction and Influence of Collaborative Learning Communities

Collaborative learning is viewed as an increasingly important learning mode in higher vocational education these days. In this mode, students are no longer passive receivers of knowledge, but take the roles of creators and sharers, and figuring out the interactive and collaborative relationships between students is particularly important for understanding the pattern and structure of student interaction. With the help of social network analysis methods, this study investigated the social network features of collaborative learning communities, measured the parameters of these network features, analyzed the accessibility of community members, and revealed the influence of members in the community based on the Lead index. The findings of this paper give deeper understandings and new insights into the collaborative learning mode and provide useful evidences for the optimization of collaborative learning strategies.

Spatial Correlation Network Structure of and Factors Influencing Technological Progress in Citrus-Producing Regions in China

In this study, the transcendental logarithmic cost function model was used to measure the rate of technological progress in seven major mandarin-producing regions and seven major tangerine-producing regions in China from 2006 to 2021. The modified gravity model was used to establish spatial correlation networks. The social network analysis method was used to analyze the characteristics of the overall network structure and the individual network structure of the spatial correlation networks of citrus-production technology progress, and the quadratic assignment procedure was used to analyze the factors influencing the spatial network. The results show the production of Chinese mandarins and tangerines is in the stage of technological progress in general, but the rate of progress is slowing down gradually, and the rate of mandarin-production technology progress is higher than that of tangerine-production technology progress. In terms of the overall network structure characteristics, the spatial networks of technological progress related to Chinese mandarin and tangerine production are becoming increasingly dense and complex, with obvious spatial spillover effects, but the network structure is relatively loose, and the polarization of the tangerine network is more serious. In terms of individual network structure characteristics, the relatively economically developed eastern regions have a higher status in terms of the spatial correlation network and a stronger role in controlling and dominating the resource elements needed for citrus-production technology progress. Education, informatization, economic development, innovation support, and financial support are important factors influencing the formation of the spatial association network of citrus-production technology progress in China.

The shaping of social and symbolic capital during the transition to farming in the Western Mediterranean: Archaeological network analyses of pottery decorations and personal ornaments.

Storing information and circulating it between individuals and groups is a critical behaviour that signals a tipping point in our evolutionary history. Such practices enabled the preservation and consolidation of knowledge over extended periods, facilitating the accumulation of cultural innovations across generations. In this study, we used Social Network Analysis methods to explore how knowledge circulated during the transition to agriculture in the Western Mediterranean region. Previous studies have shown that specific elements of the material culture reveal distinct patterns of cultural interaction among early farming communities. Here, we investigated if two archaeological proxies, personal ornaments and pottery decorations, both with an exclusively symbolic function, reveal different network structures, and if the different degree of connexions acted equally on the transmission of styles, symbols, and network changes over time. Our results relied on cultural data recorded from 77 archaeological occupations covering Italy, France, and Spain, spanning over 1,500 years (ca. 7950~6450 cal BP). By utilizing a chronological dataset comprising 114 radiocarbon dates, we revealed that pottery decorative techniques networks exhibited stronger connexions over space and time, with nodes organized in clear cluster, when compared to personal ornaments networks. The findings highlight the regionalization and fragmentation of cultural networks during the Early Neolithic, and that the transmission of cultural traits within each category of artefact operated through varying cultural and social mechanisms. Pottery expressed a dynamic regional identity, continuously shaped by geographical and chronological proximity, while bead-type associations contributed to enduring identities shared across vast geographical scales. These networks shed light on the multifaceted shaping of social and symbolic capital among the Mediterranean's early farmers, emphasizing the strength and quality of social ties that existed between communities and the level of reciprocity and cooperation required to foster these diverse social, economic, and cultural development strategies.

Is the Indonesian Government Islamophobic? Studies Using Social Network Analysis

This study aims to map the narratives, networks, and influential figures on social media Twitter after the arrest of suspected terrorists (Farid Okbah cs and Sunardi) by Detachment 88 anti-terror in Indonesia. We use the social network and content analysis methods in collecting and analyzing research data. The results of this study show that the anti-Islamic political group with government (opposition) is currently trying to make a narrative that the Indonesian government is Islamophobic, by utilizing the momentum of suspected terrorist arrests in Farid Okbah and Sunardi by Detachment 88 by shifting the issue of terrorist arrests from the JI group who are also members of MUI with the demand for dissolving the Government Institution Detachment 88 Anti-terror. The social network map shows that there were three groups engaged in the arrest of suspected terrorists Farid Okbah and Sunardi, 1) Muslim Group Cyber Army (MCA); 2) Pro-government buzzer group through Denny Siregar’s account; 3) The provocateurs group. The arrest of Farid Okbah and Sunardi turned into political issues, Islamic groups (MUI) vs. Government (Detachment). The arrest of Farid Okbah by Detachment 88 was dominated by #saminawaathonaibhrs and #Islamophobia, while the dominant narrative after the suspected arrest of Sunardi’s is #PKItangkapulama (PKI Arrest Ulama) and #dukungMUI (Support MUI), both of these things showed an effort to accompany the issue to the political narrative of the opposition group to weaken the government with the narrative that discriminated government of Islamic groups.
 Keywords: Islamophobia, social network analysis, narrative analysis, social media

Bibliometric Analysis of Higher Education Restructuring

The spread of competitive elements and the well-being of human capital increase productivity capacities in scientific content. Research and development activities are prioritized in higher education, international trends and modern paradigms are taken into consideration. In the study, a visual map of the studies prepared on the restructuring of higher education on a global scale was prepared and it was aimed to determine the trends in the literature with bibliometric analysis. Between 2002 and 2022, a total of 585 articles in the Scopus and WoS database were identified and analyzed by keyword analysis, cooperation network analysis, social network analysis methods. The most commonly used keywords were "higher education, education, university, restructuring and neoliberalism", the largest clusters defined in the network were "higher education, humanities, education policy", and the smallest cluster was "higher education policy". Among these clusters, the largest cluster is the "higher education" cluster, the average year of the publications cited jointly is 2011, and the newest issues are "humanities and higher education policy". According to the timeline map, there was a focus on the keywords "higher education, curriculum, neoliberalism, China, student, administration". In the early days, the focus was on "higher education, curriculum", then "higher education policy, innovation, management, organizational change, university reform, savings", and after 2020, the keywords "Covid 19, pandemic, distance education, student". The keywords with the most citation explosions were initially "Eurasia", in the middle "management, higher education, student", and after 2020, "student, Covid 19, human". The highest explosion of citations occurred from the word "Eurasia" between 2005 and 2009.

The use of online interactive teaching mode in university music teaching under the background of informationization

Abstract This research method uses vocal recognition, classroom interaction analysis and social network analysis theory to cluster audio data through the process of data collection and feature extraction, active speech detection and speaker change detection, and finally quantifies and visualizes classroom data based on S-T analysis and social network analysis methods, and calculates corresponding indicators for qualitative analysis. After reforming the teaching mode, 80% of students expressed great satisfaction. The information-based teaching tools resulted in an overall upward trend in the grades of the three classes. In the middle and high score range of 80-89, Class 1 increased by 34%, Class 2 by 37%, and Class 3 by 28%, and all three classes showed a more significant increase. Regarding classroom interaction behaviors, teachers' verbal behavior rates decreased from 55.86% and 44.01% to 27.48%, while students' verbal behavior rates increased from 21.92% and 21.23% to 39.73%.

Feasibility of social network analysis to study outcomes of children with medical complexity.

Since most care for children with medical complexity (CMC) is delivered daily in communities by multiple caregiving individuals, that is, caregiving networks, tools to assess and intervene across these networks are needed. This study evaluated the feasibility of applying social network analysis (SNA) to describe caregiving networks. Because hospitalization is among the most frequently used outcomes for CMC, exploratory correlations between network characteristics and CMC hospital use were evaluated. Within 3 weeks, the goal network enrollment was achieved, and all feasibility measures were favorable. Network characteristics correlated with hospital use, that is, smaller, denser networks, with more closed-loop communication correlated with fewer hospital days. Networks with more professional caregivers also correlated with fewer hospital days. SNA is a feasible tool to study CMC caregiving networks. Preliminary data support rigorous hypothesis testing using SNA methods. Network-based interventions to improve CMC health may be an important future direction.

Spatiotemporal Pattern of Carbon Compensation Potential and Network Association in Urban Agglomerations in the Yellow River Basin

The Yellow River Basin is an important energy base and economic belt in China, but its water resources are scarce, its ecology is fragile, and the task of achieving the goal of carbon peak and carbon neutrality is arduous. Carbon compensation potential can also be used to study the path to achieving carbon neutrality, which can clarify the potential of one region’s carbon sink surplus to be compensated to the other areas. Still, there needs to be more research on the carbon compensation potential of the Yellow River Basin. Therefore, this study calculated the carbon compensation potential using the β convergence test and parameter comparison method. With the help of spatial measurement tools such as GIS, GeoDa, Stata, and social network analysis methods, the spatiotemporal pattern and network structure of the carbon compensation potential in the Yellow River Basin were studied from the perspective of urban agglomeration. The results demonstrate the following: (1) The overall carbon compensation rate of the YRB showed a downward trend from 2005 to 2019, falling by 0.94, and the specific pattern was “high in the northwest and low in the southeast”. The spatial distribution is roughly spread along the east–west axis, and the distribution axis and the center of gravity keep shifting to the northwest. It also showed a weak divergence and a bifurcation trend. (2) The carbon compensation rate in the YRB passed the spatial correlation and β convergence tests, demonstrating the existence of spatial correlation and a “catch-up effect” among cities. (3) The overall distribution pattern of the carbon compensation potential in the YRB is a “low in the west and high in the east” pattern, and its value increased by 8.86% during the sampled period. (4) The network correlation of carbon compensation potential in the YRB has been significantly enhanced, with the downstream region being more connected than the upstream region. (5) The Shandong Peninsula Urban Agglomeration has the largest network center, followed by the Central Plains Urban Agglomeration, and the Ningxia along the Yellow River Urban Agglomeration has the fewest linked conduction paths. According to the research results, accurate and efficient planning and development suggestions are proposed for urban agglomeration in the Yellow River Basin.

Exploring the Effective Path of Cultivating College Students’ English Intercultural Communication Competence Based on the Social Network Analysis Model

Abstract This paper introduces the BOPPPS teaching model integrated with flipped classrooms into the intercultural communication classroom by decomposing the BOPPPS teaching module and analyzing the differences with traditional teaching methods by combining social network analysis methods. The basic teaching model framework was built, and an effective blended teaching model was created by utilizing the third-order nonlinear expression of social networks introduced into the online platform. A 10-week teaching model experiment was conducted for two classes to explore English major students in a university. The overall average score of the experimental class improved by 23.6 points to 86.02, and the score improvement was significantly higher than that of the control class, proving that the hybrid teaching model is an effective way to cultivate talents for universities.

Does High-Speed Railway Promote the Quality of Urbanization? From a Dynamic Network Perspective

Applying the improved social-network analysis method and the idea of rolling-window regression, this paper explores the impact of an HSR network on the quality of urbanization and its dynamics. Based on a sample of 273 cities in China over the period 2009–2019, we find that the high-speed railway network has an increasingly positive effect on the quality of urbanization, which proves the existence of a network effect. The empirical results further show that this effect is closely related to the coverage rate of the high-speed rail network. In addition, heterogeneity analysis reveals that urban agglomeration cities are the main beneficiaries. Academically, our study provides a plausible explanation and evidence from network size differences for the two conflicting views of the HSR effect. Practically, we also propose some important policy implications for countries in different high-speed-rail-network construction stages.

The Study of Regional Innovation Network Structure: Evidence from the Yangtze River Delta Urban Agglomeration

As a driving force for regional development, innovation holds an increasing position in regional competitiveness, and a reasonable and coordinated innovation network structure can promote high-quality regional development. Utilizing the modified gravity model and social network analysis method, an innovation network composed of 27 cities in the Yangtze River Delta urban agglomeration from 2010 to 2021 was studied. The following conclusions were founded: (1) The innovation development level in the Yangtze River Delta urban agglomeration was constantly improving, and the innovation development level generally showed a spatial pattern of high in the southeast and low in the northwest. (2) The intensity and density of innovation network correlations in urban agglomerations were increasing, and the centrality of network nodes had an obvious hierarchical characteristic. The innovation network had a significant core–periphery spatial structure, with core cities that had higher centrality, such as Shanghai, Nanjing, and Hangzhou, playing the role of “intermediaries” and “bridges”, while cities with lower centrality, such as Anhui and cities in northern Jiangsu, generally played the role of “periphery actors” in the network. (3) The spatial correlation network of innovation of the Yangtze River Delta urban agglomeration could be divided into four blocks, namely, main benefit, broker, two-way spillover, and net spillover, and the spillover effect among them had obvious gradient characteristics of hierarchy.

Harnessing Instagram® for collaborative learning in higher education

ABSTRACT This research proposes a methodological approach to using the social network Instagram® as a tool for collaborative e-learning activities in higher education. Collaborative e-learning activities are conducted on Instagram® through challenges and quizzes. The main aim of these activities is to encourage students’ creativity, motivation for learning, and collaboration through mutual interaction in assessing responses to challenges. The collected data were analyzed using social network analysis methods. The results showed students’ positive attitudes towards e-learning on social networks and readiness to use Instagram® for collaborative e-learning. The results further showed that social network analysis could provide teachers with valuable information about the students’ interactions and group dynamics, allow teachers to identify groups of students, and adapt teaching and learning strategies accordingly.

The optimized development of China's service industry in the “Belt and Road” regional value chain: A social network analysis

AbstractThe optimized development of service industry in the value chain can inject strong impetus into economic growth. The “Belt and Road” initiative provides a new path for China's service industry. This article combines value‐added accounting method and social network analysis method to study the network environment of service trade in the “Belt and Road” region and the individual characteristics of China's service trade. At the same time, the article deeply analyzes the factors that affect the optimized development of China's service industry in the “Belt and Road” regional value chain from the perspective of trade relations and puts forward countermeasures and suggestions accordingly. The study found that the “Belt and Road” regional service trade network has high density and shows a trend of blockization. As a core node in the regional service trade network, China has strong subjective initiative, connecting link, and independence in trade relations. Moreover, the optimization of China's service trade relations can further enhance its position in the “Belt and Road” regional value chain. At the same time, it can also enhance political and cultural identity, enhance China's discourse power, and promote the process of regional economic integration. Therefore, China's service industry can use the “Belt and Road” initiative to innovate the trade relationship model and realize the optimal development.