Social Network Analysis Theory Research Articles

A Novel Influence Analysis-Based University Major Similarity Study

In the field of education, investigating the relationships between different majors in universities is an important topic in current educational research. The application of social networks from informatics provides new opportunities and potentials for the field of education. Due to the complexity of social interactions, the social network connections surrounding individuals exert a significant influence on their daily decision-making processes. This paper aims to introduce the social network and influence analysis theories from informatics into the field of education, regarding major as a variable, and comparing and analyzing the influence relationships between majors. An empirical study was conducted, involving the collection of questionnaire data on graduates’ evaluations of various aspects of their university experiences across different majors. The evolution of this model follows the DeGroot opinion dynamics with the inclusion of stubborn nodes. By defining leader majors and general majors based on the data and modeling the questionnaire data as the outcome of a discrete random process, an influence matrix is ultimately generated through the opinion dynamic model. Through this modeling approach, we revealed the underlying influence relationships between different disciplines (majors). These findings provide schools with insights to adjust the directions of discipline cultivation, and offer new perspectives and methods for the study of majors in higher education.

A network analysis-based framework to understand the representation dynamics of graph neural networks

In this paper, we propose a framework that uses the theory and techniques of (Social) Network Analysis to investigate the learned representations of a Graph Neural Network (GNN, for short). Our framework receives a graph as input and passes it to the GNN to be investigated, which returns suitable node embeddings. These are used to derive insights on the behavior of the GNN through the application of (Social) Network Analysis theory and techniques. The insights thus obtained are employed to define a new training loss function, which takes into account the differences between the graph received as input by the GNN and the one reconstructed from the node embeddings returned by it. This measure is finally used to improve the performance of the GNN. In addition to describe the framework in detail and compare it with related literature, we present an extensive experimental campaign that we conducted to validate the quality of the results obtained.

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%.

Hubs of embodied business services in a GVC world

This paper explores the phenomenon of functional upgrading in Global Value Chains (GVCs) by applying empirical techniques of Social Network Analysis and graph theory to data from the TiVA database for the period from 1995 to 2018. Specifically, we focus on two (from less to more complex) stages of GVC participation: the global supply of manufacturing inputs and the global supply of business services to be embodied in other countries’ exports. We identify which countries are the leading specialized global providers in each stage, analysing their evolutions over time and the relationship between both progressions. It highlights the trajectory of China that has increased its role as a hub in both stages to reach top positions. Using a dynamic panel data model, we find that the role of a country as a specialized global supplier of manufacturing inputs is associate with becoming a prominent global supplier of embodied business services, suggesting a path to functional upgrading in GVCs.

Mobilizing the Digital Opinion Movement #OraSudiSumbangIKN on Twitter

This study examines the role of #OraSudiSumbangIKN in shaping digital opinion support mobilization movements, measuring the effectiveness of digital networks, actors, and opinions on social media. The hashtag #OraSudiSumbangIKN emerged after the government's plan to form a crowdfunding scheme from the community to construct the National Capital City (Ibu Kota Negara/IKN) Nusantara. Using social media network (SMNA) analysis and Digital Opinion Movement theory, this study examines how these hashtags mobilize the digital opinion support of social media users. The study included 10,000 tweets on Twitter that were taken and analyzed using the Netlytic and Gephi web. The study found that conversations on #OraSudiSumbangIKN hashtags were not dominated by dominant actors. This finding confirms that the hashtag meets the Digital Movement of Opinion (DMO) characteristics, which are spontaneous and not organized by social media users. This hashtag also has other DMO characteristics, which are short-lived, and comments are homogeneous. In addition, the high number of tweets on hashtags can also be explained because they have a strong narrative and emotional side. This research has implications for the selection of interesting narratives and hashtags that need to be considered by social media activists or individuals to be able to create opinion mobilization on social media. In addition, the findings can be an illustration for the government and academics or experts in the field of public policy in determining the next policy so as not to provoke negative public opinion.

Unintended consequences of state action: how the kingpin strategy transformed the structure of violence in Mexico’s organized crime

AbstractThis paper builds on social network analysis and structural balance theory to analyze, with a novel approach, some of the unintended consequences of Mexico’s kingpin strategy on the network of criminal organizations. I use data on violent conflicts between Mexico’s criminal organizations, between 2004 and 2020, from the Uppsala Conflict Data Program (UCDP), and a combination of statistics, social network analysis, GIS, and archival methods to understand the patterns and geography of violent conflicts and alliances before and after the war on drugs. The goal of this paper is threefold: first, to show that the kingpin strategy is associated with the fragmentation of criminal organizations in Mexico; second, to show that criminal organizations developed a set of structurally balanced arrangements before the government waged a war against them and that the kingpin strategy disrupted such arrangements, which led to an increase in the number of violent conflicts; third, I will argue that the fragmentation of criminal organizations also produced a process of clustering of violence, where sets of organizations started fighting each other in specific regions of the country, increasing the levels of violence in those geographical spaces.

Online News Media Analysis on Information Management of “G20 Summit” Based on Social Network Analysis

This paper contributes to the Special Issue on Communication for the Digital Media Age by investigating the factors that influence the management of political information on online news media platforms, specifically Twitter and Weibo. Using the recent “G20 Summit” as a case study, this study employs a mixed-methods approach that incorporates both deductive and inductive reasoning. Social network analysis (SNA) and graph theory are used to evaluate specific social relationships in the context of the G20 summit, while a combination of structured and content (semantic) analysis is performed. The findings indicate that individual power is becoming increasingly important in the age of online news media. Individuals contribute significantly to the diffusion of information and may play a decisive role in the future. The study also finds that the frequency of retweets increases as the reciprocity ratio increases, and mentions may be the most effective method for delivering political news on online news media platforms. Practical implications suggest strategies for managing information diffusion effectively. Additionally, this study provides insights into effective information diffusion on online news media platforms that can be utilized in health communication management during the COVID-19 era. This study expands theoretical understanding by investigating the role of individual power in the age of online news media and enriching the literature on online news media through the use of structured and content analysis based on social network analysis.

Lineages as Network: A Study of Chan Genealogy in the Zutang ji 祖堂集 Using Social Network Analysis

This paper attempts to examine the genealogical framework of “lamp records” (denglu 燈錄) of the Chan Buddhist tradition using analytical tools and methods of Historical Social Network Analysis (HSNA) and graph theory. As an exploratory study, the primary objectives are to investigate the possibilities offered by HSNA and visualization tools for research on Chan genealogy in lamp records, explore the benefits of this approach over traditional lineage charts, and reflect on its limitations. The essay focuses on the Chan community portrayed in the Goryeo 高麗 edition of the Zutang ji 祖堂集 (Collection of the Patriarchal Hall; K.1503). It shows that the lineage reportedly stemming from Qingyuan Xingsi 青原行思 (d. ca. 740) and Shitou Xiqian 石頭希遷 (701–791), as well as the branch descending from Tianhuang Daowu 天皇道悟 (748–807) to Xuefeng Yicun 雪峰義存 (822–908) and his successors, play a crucial role within the structure of the Zutang ji’s genealogical network. The study further highlights possible irregularities in lineage claims by contrasting metrics of degree and betweenness centrality with features of the text (e.g., number of hagiographic entries, length of the entries).

Peran Peran aktor Twitter pada gerakan tagar #unsubscribepodcastcorbuzier

The #CloseTheDoor Corbuzier Podcast caused controversy by uploading content featuring LGBT (Lesbian, Gay, Bisexual, and Transgender). As a form of rejection, the public used the hashtag #UnsubscribePodcastCorbuzier on Twitter to spawn a New Social Movement. The research reveals the question of how the Twitter actor role is formed by the hashtag communication network #UnsubscribePodcastCorbuzier. This study uses qualitative Social Network Analysis and Graph Theory. Based on network system analysis, @youtube became a very striking actor in the network. Relation has the property of the direction of the relationship or directed graph. Based on the results of the actor centrality research, YouTube actors in this study have high centrality. The #UnsubscribePodcastCorbuzier hashtag movement aligns with Jenkins' theory of Participatory Media Culture. People connect with each other through social media, sharing thoughts and tagging other accounts related to specific topics discussed.

Assessment of Conductivity-Temperature-Depth via multi-criteria approach: Regret theory based model on the pythagorean fuzzy environment

Sustainable development of marine economy requires strengthening the marine environmental monitoring and management. Conductivity-Temperature-Depth (CTD) realises multi-dimensional monitoring of marine environment by measuring the traits of seawater. To further promote real-time online marine monitoring, conducting a robust assessment of CTD equipment is a primary task for capacity building. In this paper, to evaluate several equipment options, a multiple-criteria decision-making model, based on regret theory and squared-confidence Pythagorean fuzzy hybrid weighted arithmetic and geometric aggregation (SCPFHWAGA) operator is proposed. The SCPFHWAGA operator takes into account the confidence level, which enhances the comprehensiveness of information aggregation. In addition, considering the differences in subjective confidence in equipment use, social network analysis and regret theory are introduced. The evaluation criteria are then designed with the concerns raised before, during and after using the equipment, which reflects the whole process of CTD equipment evaluation more objectively. The case of Zhejiang (China) is analysed. The robustness and validity of the proposed framework are verified by comparing the results with those obtained using other methods.

Transnational think tank networks: Multipliers of political power or a new form of expertise monopolies at the European level

This article examines the involvement of European think tanks (TTs) in transnational TT networks as a particular form of their social capital based on empirical data from website materials and semi-structured interviews with representatives of TTs from Brussels, London, Paris and Ljubljana, their networks and European institutions. This paper built on Bourdieu’s field theory and elements of social network analysis (SNA) contributes to a theory of the relation between fields and social networks. This study shows that positions of field members can be derived from network ties between them using different elements of SNA and Gephi software for the visualization of the TT social capital. Overall, this article argues that transnational TT networks contribute to establishing social boundaries of the transnational field of European TTs horizontally differentiating the TT field from other social fields and vertically transposing it from national to European level. Furthermore, TT social capital manifested in interaction of European TTs in these transnational TT networks determines the relational structure of their transnational TT field due to democratic deficit of the EU transnational administration which incites TTs to establish formally representative groups.

The effects of online reviews on the popularity of user-generated design ideas within the Lego community

PurposeThis study aims to explore how online reviews and users’ social network centrality interact to influence idea popularity in open innovation communities (OICs).Design/methodology/approachThis study used Python to obtain data from the LEGO Innovation Community. In total, 285,849 reviews across 4,475 user designs between March 2019 and March 2021 were extracted to test this study’s hypotheses.FindingsThe ordinary least square regression analysis results show that review volume, review valence, review variance and review length all positively influence idea popularity. In addition, users’ in-degree centrality positively interacts with review valence, review variance and review length to influence idea popularity, while their out-degree centrality negatively interacts with such effects.Research limitations/implicationsDrawing on the interactive marketing perspective, this study employs a large sample from the LEGO community and examines user design and idea popularity from a community member’s point of view. Moreover, this study is the first to confirm the role of online reviews and user network centrality in influencing idea popularity in OICs from a social network perspective. Furthermore, by integrating social network analysis and persuasion theories, this study confirms the interaction effects of review characteristics and users’ social network centrality on idea popularity.Practical implicationsThis study’s results highlight that users should actively interact and share with reviewers their professional product design knowledge and/or the journey of their design to improve the volume of reviews on their user designs. Moreover, users could also draw more attention from other users by actively responding to heterogeneous reviews. In addition, users should be cautious with the number of people they follow and ensure that they improve their in-degree rather than out-degree centrality in their social networks.Originality/valueThis study integrates social network analysis and persuasion theories to explore the effects of online reviews and users’ centrality on idea popularity in OICs, a vital research issue that has been overlooked.

How do local actors coordinate to implement a successful biogas project?

Anaerobic digestion has recently gained interest in contributing to territorial strategy regarding the deployment of the circular economy and energy transition. Most projects bring together multiple actors from a wide variety of backgrounds. The article analyzes the evolution of synergies and cooperative behaviors between local stakeholders over the period 2010–2020 in an anaerobic digestion cluster in France. The study draws on social network analysis and proximity theory, which have recently been used for analyzing regional innovation systems, local clusters, territorial governance, and rural development. We reveal that local stakeholders develop dense relational networks that vary and evolve throughout the project. Different groups exist and behave in a semi-autonomous manner. All the actors are located in close geographical proximity. Still, their links in terms of organized proximities are related to various types of relations, resulting from cognitive resemblances or common origins. This explains the persistence and resilience of local relationships and how they maintain a collaborative dynamic over time.

Factors Affecting the Evolution of Technical Cooperation among “Belt and Road Initiative” Countries Based on TERGMs and ERGMs

The Belt and Road Initiative (B&R), was initiated by China in 2013, and it covers over 60% and 30% of the world’s population and GDP, respectively. The initiative has directed a great deal of investment in energy, transportation, and 5G. Whilst much attention has been focused on cooperation in international trade, technological cooperation in the form of patents has been largely ignored. This paper investigates the formation of technological cooperative relationships among B&R countries within a technical cooperation network. Comprehensive consideration of various factors between participating countries was undertaken, using statistical methods from social network analysis theory. The node attributes and relations between countries and the network structure were studied in a sequence of network analyses using temporal exponential random graph models (TERGMs) and static exponential random graph models (ERGMs). The main findings suggest that research ability, financial ability, technological innovation ability, technological spillover proximity, geographical proximity, and technical proximity have an impact on participation in technical cooperation between B&R countries. Research ability, technological spillover proximity, geographical proximity, and technical proximity have a positive influence on the development of cooperation. However, the financial and technological innovation ability of a country does not actively promote the development of cooperation. The entire cooperation network structure does not have a greater aggregation effect compared with a random network, and intermediary multi-path cooperation is not obvious. This paper analyzes the driving factors for technological cooperation through a systematic study of the characteristics and relationships of B&R countries, and also of the network characteristics among B&R countries. The results of our analysis show that the characteristics of technical cooperation in the B&R region provide a reference for the study of international technical cooperation.

Impact of corporate network position on strategic risk and company’s performance – evidence from Poland

PurposeThe purpose of this study is to investigate the links between a company’s position in a corporate network with its financial performance and strategic risk in the context of the largest Central European stock market.Design/methodology/approachThis study integrates the theory of social network analysis (SNA) with corporate governance theory with a special focus on resource dependence theory. Using the framework of network social analysis, the authors use network measures of social capital and embeddedness.FindingsThe results of studying companies listed on the Polish stock exchange indicate that a company’s corporate network position has a significant negative impact on strategic risk while having no influence on its financial performance. The research also highlights the importance of a firm’s corporate governance model for both performance and strategic risk.Research limitations/implicationsThe data collected, and SNA measures used made it possible to conduct a cross-sectional study. Compared to longitudinal studies, this type of study has a couple of disadvantages addressed in the paper. In the future, the dependencies observed in this study should be tested using longer-term data.Originality/valueTo the best of the author’s knowledge, this is the first paper integrating the corporate personal and capital networks to test risk and performance dependencies in the context of Poland’s corporate governance model. The findings and conclusions can also be applied to analyzing Central and Eastern Europe stock markets.

Spread of Online Public Opinion of Animal Epidemic Emergency: A Case Study of the H7N9 Incident Based on Healthcare Data Analytics.

Qualitative and quantitative analysis of online public opinion of the H7N9 animal epidemic incident in 2013 were conducted based on social network analysis (SNA) theories, SNA method, and life cycle theories. Trend and features of evolution of online public opinion of animal epidemic emergency were explored and structural characteristics of key nodes in these public opinion spreading networks were identified. The stages of spreading of public opinion of animal epidemics were investigated. This study provides references for the government to cope with online public opinion of animal epidemic emergencies in the future.

Identifying information security opinion leaders in organizations: Insights from the theory of social power bases and social network analysis

Organizations are increasingly prioritizing the management of information security (InfoSec) to facilitate their data-driven business. There are densely connected organizational networks in modern organizations, where both formal and informal leaders influence other employees’ InfoSec behaviors. We analyzed the organizational networks in a large organization and investigated the interactions that made employees appear as influential InfoSec opinion leaders to their colleagues. The findings indicate that influential InfoSec opinion leaders were perceived by colleagues as knowledgeable in InfoSec and capable of rewarding and sanctioning InfoSec behaviors. Other traits such as formal seniority, age, tenure, and department membership were also found to increase InfoSec leadership.

‘Fake news’ discourses

Abstract This article explores the strategic use of ‘fake news’ discourses in non-democratic contexts using a mixed-methods approach grounded in social network analysis and discourse theory. In contexts such as Russia and Iran, where the opposition generally does not have unrestricted access to the political public sphere, social media platforms serve to influence discourses. Given the prevalence of fake news discourses, previous studies have already focused extensively on the political elite and their use of this discourse within Western or Anglo-American contexts, and on the typologies of ‘fake news’. Our findings address this research gap and suggest that ordinary users in non-Western and non-democratic settings do not differentiate between ‘fake news’ types. Rather, they employ the discourse as a means to strategically delegitimise and discredit their opponents.

Social Network Analysis and Literary Studies

사회 연결망 분석(social network analysis)은 20세기 내내 사회과학 분야에서 지속적으로 발전해온 사회구조 분석 이론이자 방법으로서 개체, 조직, 인간, 사물 사이의 복잡다기한 연결을 거시적, 미시적으로 분석하기 위해 관계형 데이터를 구축하고 이를 연결망으로 시각화하여 유동적이면서도 구조화된 전체 장을 파악하고자 하는 분야이다. 이러한 사회 연결망 분석은 최근 인문학 연구 분야에서, 특히 2000년대 이후 디지털인문학이 각광을 받기 시작하면서 그 방법 중 하나로 주목받고 있다. 영미문학 연구 분야에서도 사회 연결망 분석의 이론과 기법을 영문학 자료에 적용하여 그 동안 전통적인 연구 방법으로 파악하기 어려웠던 특정 국면의 문학 관계망을 복원한 성과들이 나타나고 있다. 한국의 국문학 연구 분야 역시 사회 연결망 분석 기법을 적용한 사례가 드물지만 꾸준히 등장하고 있다. 본 논문은 사회 연결망 분석 이론 및 방법이 문학 연구에 지닌 함의와 가능성에 주목하고 이를 체계적으로 소개하여 한국 학계의 디지털인문학적 문학 연구를 활성화하는 데 기여하고자 한다. 먼저 사회 연결망 이론을 소개하며 그 의미와 역사를 되짚어 본다. 그리고 이것이 인문학, 그 중에서도 문학 연구에 어떻게 활용될 수 있는지, 그 가능성은 무엇인지 등을 점검하기 위해 영미문학 분야 연구 성과들을 비판적으로 점검한다. 나아가서 사회 연결망 분석이 국문학계에서는 어떤 성과들을 축적하고 있는지 검토하여 한국에서의 사회 연결망 분석 기법을 활용한 문학 연구의 가능성을 모색한다.Social network analysis has been evolving as a social structure analysis theory and methodology in the social science discipline throughout the 20th century. It strives to understand the complex networked relationships among entities such as objects, individuals, social groups, organizations, etc. by preparing and visualizing their relational data so as to grasp the fluid dynamics of any given field. Many humanities scholars have also paid close attention to social network analysis as a new research method as digital humanities emerges as a formidable discourse in the new millennium. There are quite a few remarkable cases that apply social network analysis concepts and techniques to English literary data and thus manage to delineate literary networks at the particular junctures in literary history, which might have remained opaque otherwise. A similar trend can be observed in Korean literary studies though only a small number of researchers are interested in the method. This paper introduces social network analysis, focusing on its possibilities as a new literary research method and hence facilitating digital humanities approaches to literature in Korean academia. First, it briefly presents social network analysis theory, its history and concepts, and its methodological significance. And then, it goes on to critically review the actual research cases in the fields of English and Korean literature to examine how social network analysis can be employed in literary scholarship and what potentials it contains as a research method. Finally, this paper suggests that social network analysis helps deepen our knowledge and appreciation of literature by engaging literary history with a fresh look.

Identifying Project Corporate Behavioral Risks to Support Long-Term Sustainable Cooperative Partnerships

Projects are considered crucial building blocks whereby organizations execute and implement their short-, mid-, and long-term strategic visions. Projects are thought, developed, and implemented to solve problems, drive change, satisfy unique needs, add value, and exploit opportunities, just to name a few objectives. Although existing project management tools and techniques aim to deliver projects with success, according to the latest reviewed literature, projects still keep failing at an impressive pace. Among the extensive list of factors that may threaten project success, several articles from the research literature place particular importance on a still underexplored factor that may strongly lead to unsuccessful project delivery. This factor—usually known as corporate behavioral risks—usually emerges and evolves as organizations work together to deliver projects across a bounded period of time, and is characterized by the mix of formal and informal dynamic interactions between the different stakeholders that constitute the different organizations. Furthermore, several articles from the research literature also point out the lack of proper models to efficiently manage corporate behavioral risks as one of the major factors that may lead to projects failing. To efficiently identify and measure how such corporate behaviors may contribute to a project’s outcomes (success or failure), a heuristic model is proposed in this work, developed based on four fundamental fields ((1) project management, (2) risk management, (3) corporate behavior, and (4) social network analysis), to quantitatively analyze four critical project social networks ((1) communication, (2) problem-solving, (3) advice, and (4) trust), by applying the theory of social network analysis (SNA). The proposed model in this work is supported with a case study to illustrate its implementation and application across a project lifecycle, and how organizations can benefit from its application.