Egocentric Network Research Articles

Starting an undergraduate degree amid the COVID-19 pandemic: A mixed-method egocentric network study on student loneliness.

Students who began their undergraduate university studies in the midst of the COVID-19 pandemic (the 'COVID cohort'), may have been particularly at risk for experiencing increased loneliness. This study employed an exploratory egocentric network and mixed-methods approach to investigate the links between social networks and loneliness in the COVID cohort. Of sixty-one respondents meeting inclusion criteria for the study, fifty-eight first-year undergraduate students from the September 2020 intake at a large Scottish University provided egocentric network data via an online survey, as well as responses to three open-ended questions which were aimed at generating qualitative data about participants' experiences of starting university in the context of the COVID-19 pandemic. Bivariate analyses suggest that having a larger social network, and higher satisfaction with that network, was associated with reduced loneliness. We additionally explored these associations in subsamples of students living on-campus and living off-campus. Our qualitative data adds valuable insight into the impact that pandemic-related social-distancing restrictions had on limiting students' opportunities for meeting their peers and forging meaningful social connections at university. Limitations of this study include a small sample size and an exploratory approach requiring further investigation and replication. However, in the context of universities continuing to use hybrid teaching models, this study provides useful initial insights, highlighting potential avenues for institutions to support students in developing social connections in the transition to higher education.

SOCIAL NETWORK STRUCTURE AND FIRMS’ INTERNATIONALIZATION: NEW INSIGHTS FROM A WHOLE-NETWORK PERSPECTIVE

Objective: The aim of this study was to analyze the social network structure of the oil and gas (O&G) cluster in Rio de Janeiro, Brazil. We explore whether internationalized firms concentrate in specific sections of the social network, and scrutinize whether internationalization is associated with a firm’s attributes and its direct and indirect network ties. Method: This research applies social network analysis, which allows us to identify dense sections, popular nodes, and strategic position. We apply partitioning techniques to determine the extent to which a firm’s internationalization is affected by those to whom it is connected. Main results: Our findings show that internationalized firms concentrate in dense sections of the network, which are characterized by high interconnectedness. Furthermore, there is indicative evidence that interaction among firms and their attributes embedded in the social network structure is associated, at least in part, with the diffusion of internationalization. Relevance / Originality: Most studies targeting the network focus on the so-called ego network. This study applies a whole-network perspective to consider popular communities and central nodes and, ultimately, show how social behavior is diffused within the social network structure. Theoretical / Methodological Contributions: Drawing upon the network theory, we emphasize interdisciplinarity to advance international business (IB) scholarship. In particular, we qualify the Uppsala model’s assumption of network/relational capability, that is, the ability to build, sustain, and coordinate relationships by demonstrating the relevance of the social network structure to the internationalization process.

텍스트 마이닝을 활용한 한국과 일본의 ESG 경영 현황 비교

This study used text mining techniques to collect keyword data from the sustainability reports of companies listed on the Korean and Japanese securities markets, ranked 1 to 3 by market capitalization, and conducted word cloud analysis, frequency analysis, ego network, and N-gram analysis. The purpose of this study is to benchmark the ESG management of companies in Japan, which has secured a high amount of ESG investment compared to Korea, by comparing issues with Japan, which has been mentioned as a leading country in ESG management based on the amount of investment and historical aspects of ESG management in various studies. In addition, the ESG management direction of Japan is used to predict the future ESG management direction of Korea and suggest directions for Korean companies.
 In the analysis of the frequency of keywords that can identify ESG issues in Japan and Korea, Korea and Japan are similar, and among the keywords with high frequency and importance, we analyzed the keywords with high co-occurrence frequency such as management, employee, and environmental, and found that the management keyword is similar, and from the employee keyword, childcare and diversity keywords appear as co-occurrence keywords in the Japanese analysis. In Korea, the keyword supplier was found in the environment and employee management keywords. In addition, the N-gram analysis, which can check the frequency of linked keywords, showed that the frequency of governance-related keywords was higher in Japan than in Korea.
 This study has academic and practical significance in that it compares the direction of ESG management in Korea through direct comparison with large companies in developed countries through literature studies and keyword analysis, and suggests directions and complementary points for Korean companies.

텍스트 마이닝 기법을 활용한 코로나-19 펜데믹 발생 이전과 이후 스타트업 성장요인에 관한 인식변화 연구

The purpose of this study is to investigate and analyze the changes in social perceptions of startup growth factors in the period before and after the COVID-19 pandemic using text mining techniques, and to provide useful information for government agencies' policy formulation and companies' decision-making for startup growth in the post-COVID-19 era. The TEXTOM program was used to collect and analyze the data. The analysis methods used were word cloud analysis and frequency analysis through text mining, TF-IDF analysis, N-gram analysis, ego network analysis, and CONCOR analysis. The results of the analysis showed that the words that changed significantly after the outbreak of the COVID-19 pandemic were “finance” from 6th to 12th, “startup” from 10th to 20th, “scale-up” from 16th to 4th, and “innovation” from 17th to 11th. Keywords such as “big business”, “government”, and “economic growth” have not appeared in the top 30 keyword impression frequency since the outbreak of the COVID-19 pandemic. This indicates that the external environmental shocks brought by the COVID-19 pandemic require new ways of growth and innovation, and that startup growth has shifted from 'exogenous structural changes' such as government support to 'autogenous structural changes' based on the startup ecosystem. In addition, since the outbreak of the COVID-19 pandemic, words related to startup growth strategies such as “accelerator”, “power”, “growth platform”, “follow-up support”, “need”, “secure”, “technology”, “barrier”, “foundation”, “market creation”, and “economy” have appeared. Through the CONCOR analysis, we concluded that social interest in the growth of startups is increasing amidst the low growth of the Next Normal, and that internal resource capacity enhancement and the scale-up ecosystem, an environmental factor that can support it, and horizontal networks among firms are key factors as the main drivers of startup growth, and discussed theoretical, policy, and practical implications based on this. Finally, we discuss the limitations and future directions of this study.

Creativity of key inventors in the technical pre-development stage: the time effect of network content and structure

ABSTRACT Technical pre-development has become increasingly crucial for enterprises in making core technological breakthroughs. Using a cross-level analysis framework of ego and whole networks, this study comprehensively considers the network content and structure. Specifically, it introduces the dynamic characteristics of organisational network research over time to study the impact of current knowledge breadth, structural holes, degree centrality, assortativity, and transitivity on the creativity of key inventors in the pre-development stage. The study uses the 4G and 5G patent data of 10 representative telecommunication enterprises as the sample data. The results demonstrate that there is an inverted U-shaped association between the current knowledge breadth and the creativity of key inventors. At the ego-network level, although there is also an inverted U-shaped relationship between the current degree centrality and the creativity of key inventors in theory, within the value range of the sample data, this relationship indicates a monotonically increasing trend. At the whole-network level, assortativity and transitivity have U-shaped and inverted U-shaped significant effects on the creativity of key inventors, respectively. Our study offers a new perspective for the management of the creativity of key inventors in the pre-development stage.

The effect of distant connections on node anonymity in complex networks

Ensuring privacy of individuals is of paramount importance to social network analysis research. Previous work assessed anonymity in a network based on the non-uniqueness of a node’s ego network. In this work, we show that this approach does not adequately account for the strong de-anonymizing effect of distant connections. We first propose the use of d-k-anonymity, a novel measure that takes knowledge up to distance d of a considered node into account. Second, we introduce anonymity-cascade, which exploits the so-called infectiousness of uniqueness: mere information about being connected to another unique node can make a given node uniquely identifiable. These two approaches, together with relevant “twin node” processing steps in the underlying graph structure, offer practitioners flexible solutions, tunable in precision and computation time. This enables the assessment of anonymity in large-scale networks with up to millions of nodes and edges. Experiments on graph models and a wide range of real-world networks show drastic decreases in anonymity when connections at distance 2 are considered. Moreover, extending the knowledge beyond the ego network with just one extra link often already decreases overall anonymity by over 50%. These findings have important implications for privacy-aware sharing of sensitive network data.

Predicting Mood Based on the Social Context Measured Through the Experience Sampling Method, Digital Phenotyping, and Social Networks

Social interactions are essential for well-being. Therefore, researchers increasingly attempt to capture an individual's social context to predict well-being, including mood. Different tools are used to measure various aspects of the social context. Digital phenotyping is a commonly used technology to assess a person's social behavior objectively. The experience sampling method (ESM) can capture the subjective perception of specific interactions. Lastly, egocentric networks are often used to measure specific relationship characteristics. These different methods capture different aspects of the social context over different time scales that are related to well-being, and combining them may be necessary to improve the prediction of well-being. Yet, they have rarely been combined in previous research. To address this gap, our study investigates the predictive accuracy of mood based on the social context. We collected intensive within-person data from multiple passive and self-report sources over a 28–day period in a student sample (Participants: N = 11, ESM measures: N = 1313). We trained individualized random forest machine learning models, using different predictors included in each model summarized over different time scales. Our findings revealed that even when combining social interactions data using different methods, predictive accuracy of mood remained low. The average coefficient of determination over all participants was 0.06 for positive and negative affect and ranged from − 0.08 to 0.3, indicating a large amount of variance across people. Furthermore, the optimal set of predictors varied across participants; however, predicting mood using all predictors generally yielded the best predictions. While combining different predictors improved predictive accuracy of mood for most participants, our study highlights the need for further work using larger and more diverse samples to enhance the clinical utility of these predictive modeling approaches.

Academic Success at Social Costs: An Exploratory Study on Social Networks of Chinese Students under Academic Streaming.

In universities that require students to reside in dormitories, there are two types of social networks-study/classroom-based and social/dorm room-based. The academic streaming system may disrupt study/classroom connections, but its impact on students' social networks is unknown. Using self-reported surveys, this study examines ego network measures of network sizes, turnover, multiplexity, and diversity among 382 students (44% female, 56% male). Surveys were administered before and after the university employed a first-semester grade-point average to demote or promote students into an honours college. Follow-up interviews were conducted with 11 honours students staying within their track and 11 students who were re-streamed to the non-honours track. Quantitative results showed that students in the non-honours college and who remained there had increasingly overlapping friendship circles between study and social environments, along with more diverse social connections, indicating stronger networks. In contrast, honours participants experienced fewer overlapping networks across domains and less dispersed social ties, especially after the academic replacement process. Qualitative results showed that the honours students faced a trade-off between academic success and social engagement in maintaining their elite status. Re-streamed students experienced otherness in social groups and decreased psychological wellbeing. This study contributes to the application of network analysis in education and provides insights into the unintended consequences of educational practice on students' social networks.

SpreadLine: Visualizing Egocentric Dynamic Influence.

Egocentric networks, often visualized as node-link diagrams, portray the complex relationship (link) dynamics between an entity (node) and others. However, common analytics tasks are multifaceted, encompassing interactions among four key aspects: strength, function, structure, and content. Current node-link visualization designs may fall short, focusing narrowly on certain aspects and neglecting the holistic, dynamic nature of egocentric networks. To bridge this gap, we introduce SpreadLine, a novel visualization framework designed to enable the visual exploration of egocentric networks from these four aspects at the microscopic level. Leveraging the intuitive appeal of storyline visualizations, SpreadLine adopts a storyline-based design to represent entities and their evolving relationships. We further encode essential topological information in the layout and condense the contextual information in a metro map metaphor, allowing for a more engaging and effective way to explore temporal and attribute-based information. To guide our work, with a thorough review of pertinent literature, we have distilled a task taxonomy that addresses the analytical needs specific to egocentric network exploration. Acknowledging the diverse analytical requirements of users, SpreadLine offers customizable encodings to enable users to tailor the framework for their tasks. We demonstrate the efficacy and general applicability of SpreadLine through three diverse real-world case studies (disease surveillance, social media trends, and academic career evolution) and a usability study.

Social networks and HIV treatment adherence among people with HIV initiating treatment in rural Uganda and peri-urban South Africa

Timely initiation of and adherence to antiretroviral therapy (ART) is critical for improving HIV outcomes and reducing HIV transmissibility. Social networks, or the social relationships individuals have with each other, have been linked with positive health outcomes, but less is known about the extent to which social network composition and structure are associated with improved ART adherence among people living with HIV (PLWH). We conducted an ego-centric network study among 828 previously ART-naïve PLWH presenting for ART initiation at 11 clinics in Mbarara, Uganda (rural population) and Gugulethu, South Africa (peri-urban population). We collected social network data using name generator and name interpreter questions. ART adherence was monitored over 12 months using wireless monitors (Wisepill). Our primary outcome of interest was ART adherence during the 12-month follow-up period. We used generalized linear models to estimate the associations between network measures and ART adherence. PLWH at the Uganda site (compared with the South Africa site) were less isolated, had larger social networks, and had more social ties providing sufficient social support; they were also more likely to bridge different social groups whereby not all social ties were connected to each other. In Uganda, social isolation was associated with a 5.5 percentage point reduction in ART adherence (95% confidence interval [CI] −9.95 to −1.13; p = 0.014), while having more same gender social ties was associated with higher ART adherence (b = 0.13, 95% CI 0.02–0.25, p = 0.025). In South Africa, there was no association between social isolation and ART adherence, and having more friendship ties (vs. family ties) was associated with lower ART adherence (b = −2.20, 95% CI −3.56 to −0.84; p = 0.002). Identifying and supporting PLWH who are isolated may facilitate optimal adherence, but understanding how networks differentially affect ART adherence by country context is important.

The Moderating Effect of Youth Sports Coaches’ Identities on Their Professional Knowledge Orientations: A Social Network Perspective

The present study used social network analysis to investigate the moderating effect of individuals’ identities on the relationship between the structure of their networks and professional knowledge orientations (exploitation, exploration, and ambidexterity). It examined the ego networks of Israeli youth soccer coaches (N = 88) based on their vocational and personal sources of knowledge, including sportive, personal development, and friendship networks. The findings indicate that youth soccer coaches’ sportive identity embeddedness enhances their knowledge exploitation even when they have access to nonredundant, new, and versatile knowledge. But in the case of lower levels of athlete identity and nonredundant versatile networks, youth soccer coaches display ambidexterity by exploring novelty while relying on their familiar past knowledge and routines. Overall, the study describes the challenges of a single salient identity and points out the importance of cultivating diverse networks and multiple identities to facilitate effective and sustainable knowledge acquisition and utilisation for long-term professional advancement.

Unveiling Cognitive Constraints in Language Production: Extracting and Validating the Active Ego Network of Words

Unveiling Cognitive Constraints in Language Production: Extracting and Validating the <i>Active</i> Ego Network of Words

Exploring Influencer Dynamics and Network Resilience: A Deep Dive into Science-Related Subgraph of Twitter Ego Networks

This paper presents an in-depth analysis of a Twitter ego network, focusing on the scientific community. Utilizing relative network analysis techniques, the study explores community structures, influencer dynamics, and network resilience. Key methodologies include community detection, centrality analysis, predictive modeling for link prediction and influence propagation, as well as resilience analysis. Results show distinct community formations, influential nodes, varying network resilience to disruptions. This comprehensive analysis provides valuable insights into the complex dynamics of scientific discourse on social media, emphasizing the importance of influential nodes and community structures in maintaining network integrity and facilitating information flow. This study will provide theoretical, methodological, and framework references for other social network analysis.

언어 네트워크 분석기법을 통한 생태(환경)교육 기본계획 문서 분석

Objectives The main purpose of this study is to determine what the key words are in the basic plans for ecological(environmental) education created by provincial offices of education and what the relationships are between those words. In addition, this study was conducted to determine whether the documents of the provincial office of education contain the value of ecological transformation in education.&#x0D; Methods The research method used in this study is semantic network analysis. The words included in the basic plans for ecological(environmental) education created by the provincial offices of education in 13 regions were corrected, controlled, and removed to extract key words, and the frequencies of the words were analyzed. Additionally, basic attribute analysis, centrality analysis, sub-network analysis, and ego network analysis were performed using Gephi 0.10.1, a network analysis program.&#x0D; Results The results of this study are as follows. First, as a result of analyzing the frequency of use and centrality of each key words, ‘practice’ and ‘carbon neutrality’ appeared most frequently and have the highest influence in the documents. Second, as a result of clustering key words according to their similarity, these words formed four sub-networks. Third, as a result of examining the connection structure between ‘ecological transformation education’ and ‘ecological environment education’ through ego network analysis, the two words shared a lot of related words.&#x0D; Conclusions The conclusions of this study are as follows. First, The use of ‘practice’ and ‘carbon neutrality’ as key words in the basic plans for ecological (environment) education should be maintained in the future. At this time, educational activities at the cognitive and affective levels should also be treated with great importance in the document. Second, since ecological transformation education and ecological environment education form different clusters, each documents must establish a mutually cooperative and complementary relationship. Third, many words are shared between the ecological transformation ego network and the ecological environment education ego network, and since there is ongoing discussion about what term to replace the existing environmental education with, so provincial offices of education should be cautious in using the terms.&#x0D;

Regional Comprehensive Economic Partnership (RCEP): Evaluation of Trade Relations Between Member Countries Using the Social Network Analysis Method

The Regional Comprehensive Economic Partnership (RCEP) agreement was signed in 2020 as a giant free trade agreement signed by 15 countries, including China. In this context, the RCEP agreement is the world's largest free trade agreement in terms of GDP and trade volume. In this study, commercial relations between RCEP countries between 2012 (the year when negotiations of the RCEP agreement began) and 2021 were examined using social network analysis. In the analyses, export values of RCEP countries to each other were used and the data were obtained from Trade Map. In the study, social network analyzes for the years 2012, 2015, 2018 and 2021 were analyzed using the Ucinet program, while trade networks were visualized with the Gephi program. For social network analyses, basic ego network indicators, degree centrality values, hub and authority centrality values and eigenvector values were calculated. As a result of the analysis, it is seen that the hub and authority country in trade between RCEP countries is China for all four years (2012, 2015, 2018 and 2021). On the other hand, it has been determined that China's most important trade partners are Japan and South Korea. Additionally, the development in Vietnam's trade level during this period is remarkable.

The Social Fabric of Watershed Management: Comparison of Citizen-Based and Agency-Based Organizations

This research offers an exploration of the social networks within two distinct watershed groups in the Hudson River, New York State, USA: citizen-based and agency-based organizations. Through a social network analysis of their operations and interactions, this study unveils the complex dynamics and roles of individual nodes in facilitating nine types of connections, such as political and financial, within these networks. The citizen-based organization demonstrated denser and more cohesive networks, suggesting robust relationships and enhanced resilience and adaptability. In contrast, the agency-based organization exhibited more hierarchical networks. This study employs both network-level and node-level analyses to examine the social networks within watershed groups. Our network-level analysis focuses on metrics such as density, average degree, and hierarchy, while our node-level analysis examines clustering coefficients and influence. It also explores ego networks through an analysis of their density and the effective size of structural holes. Our finding is that the social networks of the two groups are quite distinct, and there is limited exchange of information and resources between them. However, we discovered that effective communication among a few well-connected individuals (e.g., those with high influence values) within each group can enhance the effectiveness and resilience of these networks. These analyses aim to provide a detailed understanding of the social dynamics within regional watershed groups.

Gambling as Work: A Study of German Poker Players

The study addresses the question whether professional gamblers can be considered an occupational group from a sociological perspective. It combines survey data on poker players from the German state North Rhine-Westphalia with sociological theory in order to explain the oxymoron of professional gambling. The descriptive analysis of the survey data is supplemented by ego-centric network data of the poker players to analyze whether hobby and professional players maintain different forms of social relationships. Even when semiprofessionals and professional players are grouped together for the purpose of comparative analysis, they fulfill the criteria of occupational groups according to Salaman’s major work on the topic. The study points to the fact that more research on occupational groups outside of the common fields is needed and bridges the gap between the literature on serious leisure and sociological research on professions and professionalization.

SOCIAL BRIDGING NETWORKS AND COGNITIVE AGING AMONG OLDER ADULTS: ORIGINS IN SOCIAL CONTEXTS, ROLES, AND ACTIVITIES

Abstract There is a strong link between social connectedness and cognitive aging, with recent research pointing to social bridging being a primary underlying mechanism. Social bridging may provide cognitive enrichment through interactions with expansive, heterogeneous, and loosely interconnected social networks of weaker, peripheral ties. Drawing on egocentric social network data and cognitive assessments of 436 older adults from the Social Networks and Alzheimer’s Disease (SNAD) study, this paper explores where social bridging networks come from. We used multivariate regression to examine whether a latent social bridging factor comprised of six structural variables (network size, density, effective size, diversity, strength of weakest tie, and sole bridging status) was associated with cognitive function and social conditions. Results indicate that social bridging is significantly associated with global cognitive function (B= 0.19; p&amp;lt;.0001), verbal memory (B=0.26; p&amp;lt;.0001), and episodic memory (B=0.21; p&amp;lt;.0001), consistent with prior studies. Older adults who are women (b=0.40; p&amp;lt;.001) and have more years of education (b=0.05; p&amp;lt;.05) have more access to social bridging. Among community and housing characteristics, only perceived community integration is significantly correlated with higher bridging (b=0.22; p&amp;lt;.05). With respect to social roles, being currently married (b=0.39; p&amp;lt;.001) and being a volunteer (b=0.58; p&amp;lt;.0001) were positively associated with bridging, while being a veteran predicted lower bridging (b=-0.86; p&amp;lt;.0001). Among indicators of social engagement, only number of contacts in one’s phone (in 100’s) was associated with bridging (b=.16; p&amp;lt;.0001). Findings provide insight into social roles and activities that can be leveraged to expand bridging and improve cognitive aging outcomes.

SOCIAL CONNECTEDNESS ACROSS THE LIFE COURSE: CORE NETWORKS AND EVERYDAY SOCIAL INTERACTIONS OF AMERICAN ADULTS

Abstract Scholars have been monitoring the signs of social isolation and weakening of family ties among Americans. This paper asks: (1) Do Americans socially disengage from society as they age? (2) Are family ties replaced by work or friends as Americans grow out of their original family? Using a state representative sample of egocentric network data (Person to Person Study: P2P) and a national representative sample of time dairy data (American Time Use Survey: ATUS) during 2018-2021, we found that although people spent less social time with others as they age, they maintained a stable sized core network of confidants for discussing important and health matters. This refutes the view that old age has a universal negative influence on social connectedness. We found little evidence that family ties are replaced by non-kins at any age in both core network and daily social contact. By combining core network and time dairy data, we found that although people spent substantial time with coworkers daily when they enter the workforce, they rarely included even a single coworker into their core network. This suggests that people’s core network is less influenced by current daily social interactions than many theories on social contact would predict. We speculate that people may organize their core network based on cumulative time they spend with a particular person over the life course rather than current time. The roles of life events and age in shaping changes in daily interactions and core network over the life course are further discussed.

Ego-centered network analysis of ethnic-racial socialization in families

ABSTRACT Ethnic-racial socialization refers to the implicit and explicit ways individuals learn about race and ethnicity from family, media, community, and peers (Hughes et al., 2016). Ethnic-racial socialization is a central part of familial conversations for Black, Indigenous, and families of color. This research uses ego-centered network analysis to explore the different patterns and meaning-making in families when discussing issues of race and ethnicity. Overall, four family map types emerged from the data: expansive, concentrated, condensed, and balanced. In addition, participants described different themes according to their map type, overall demonstrating the multitude of ways ethnic-racial socialization manifests in families.