Social Network Relationships Research Articles

Intra-cohort social network structure and cohort performance

We investigate the social network relationships between startups in the same accelerator. We use network theory to explain and predict peer effects in the form of social capital, leading to cohort-level performance. We hypothesize and find that higher performing cohorts have fewer unconnected startups than under-performing cohorts. Consistent with the ‘network closure’ and ‘structural holes’ arguments, we also hypothesize an inverse curvilinear relationship between cohort network density and cohort performance. We quantify the intra-cohort social network structures of 1537 startups comprising 154 Techstars cohorts using their activity on Twitter. We find that there exists an upper limit to the impact of cohort network density on performance, after which any further increase becomes negative. We contribute to theory on peer effects in accelerator cohorts by demonstrating the importance of intra-cohort social networks. Our study has implications for stakeholders in accelerators and for the startups that join them.

Evaluation of Development of Sharing Economy from the Perspective of Social Network

This article focuses on the study of the macro and interdisciplinary aspects of the sharing economy. Based on the perspective of social networks, the overall evaluation of the development of this new economic form is carried out, with a view to exploring the sound development of the sharing economy with a new perspective of sociology. First of all, the sharing economy has changed the structure and relationships of social networks. However, social networks have negative effects on trust mechanism, heterogeneous connection, social governance, individual autonomy and capital circulation in the considerable changes. Based on the concern for these negative effects, this article still launches the development strategy of the sharing economy in the aspects of traditional relations, institutional supply, lowering barriers, abandoning inertia, and identifying social capital from the perspective of social network.

Using decision tree analysis to understand the influence of social networks on disclosure of HIV infection status

ABSTRACT Disclosure of human immunodeficiency virus (HIV) infection status improves treatment adherence and HIV prevention. Social networks influence such disclosure by people living with HIV/AIDS (PLWH). This study aimed to investigate the disclosure status of Korean PLWH and determine the social network characteristics associated with disclosure. A cross-sectional study design was used, and 148 Korean PLWH answered self-report questionnaires that included items on the characteristics of social networks and disclosure. Logistic regression and decision tree analysis were performed. In total, 81 participants (54.7%) reported disclosing HIV status to the most important supporter. Five factors were found to influence disclosure: age, self-help group participation, living arrangement, social network relationship, and tie strength; three groups had higher percentages of nondisclosure. The findings suggest that healthcare practitioners should provide adequate counseling by considering the characteristics of social networks and disclosure status of PLWH. Researchers should identify high-risk populations using decision tree analysis.

RELATIONSHIP BETWEEN SOCIAL NETWORKING ADDICTION AND ACADEMIC PERFORMANCE OF UNDERGRADUATE STUDENTS DURING COVID-19 PANDEMIC

The purpose of the present study is to explore the undergraduate student's social network addiction levels and relationship with academic performance. In addition to that, this research compares the undergraduate students' social networking sites addiction levels with respect to gender, habitat, age, semester of study, type of institution they graduate, experiences in social networking environments (years), time spent in social networking sites. This study was quantitative in nature. For this current research, a descriptive survey method was adopted. Data were collected through online survey dropping a mail on a large population of undergraduate students. Using convenience sampling techniques, 125 undergraduate students responded to the survey and it was taken for research. Collected data were analysed using SPSS and the hypotheses were tested using descriptive analysis, t-test, ANOVA and correlation analysis. Results revealed 65% undergraduate students addicted to social network sites and there was a linear relationship between social networking sites addiction levels and academic performance. Also, there was no significant difference in undergraduate student's social networking sites addiction with respect to gender, habitat, age, semester of study, type of institution they graduate, experiences in social networking environments (years), but there was a significant difference in undergraduate student's addiction and time spent in social networking sites.

Geographically Dispersed Community Networks: Exploring Social Networking Site Experiences and Relationships in the Intercollegiate Forensics Community

Geographically Dispersed Community Networks: Exploring Social Networking Site Experiences and Relationships in the Intercollegiate Forensics Community

Associations between relationship quality, social network resources, appraisals, coping, and posttraumatic stress disorder symptoms.

Objective: This study aimed to explore whether posttrauma cognitions and maladaptive coping strategies mediated the association between perceived social support (availability of social network and quality of specific relationships) and posttraumatic stress disorder (PTSD) symptoms. Method: A community sample of trauma survivors (N = 67, 84% female) completed self-report measures assessing relationship quality, perceived availability of social network support, PTSD symptoms, negative posttrauma appraisals and maladaptive coping strategies. Results: Posttrauma appraisals mediated the association between quality of relationships (support, conflict and depth) and PTSD symptoms, and between availability of social network support and PTSD symptoms. Further, there was an indirect pathway between social support (quality of relationship and availability of social network) and PTSD symptoms through negative cognitive appraisals and maladaptive coping strategies (serial mediation). Conclusions: Our results are consistent with theoretical predictions that socially supportive (support, depth and social network availability) and unsupportive (conflict) relationships are associated with PTSD, through cognitive appraisal and coping processes. Clinical implications for further integrating interpersonal support into cognitive therapies were discussed. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

A national survey on COVID-19\xa0second-wave lockdowns on older adults\u2019 mental wellbeing, health-seeking behaviours and social outcomes across Australia

BackgroundThe impact of severe second lockdown measures on older adults’ wellbeing is unknown. We aimed to (i) identify the impact of the second lockdown that resulted from the second wave of COVID-19 cases on older Australians’ quality of life; (ii) compare the impact of second wave lockdowns in Victoria, Australia’s second most populous State, to those in other States and Territories not in lockdown.MethodsA national cross-sectional study of community-dwelling older adults completed online questionnaires for quality of life, social networks, healthcare access, and perceived impact of COVID-19 between July to September 2020. Tobit regression was used to measure the relationships of healthcare service access and social networks with quality of life of older adults in Victoria compared to those in the rest of Australia.ResultsA total of 2,990 respondents (mean [SD] age, 67.3 [7.0]; 66.8 % female) participated. At time of data collection, Victoria’s second COVID-19 lockdown had been in force for an average 51.7 days. Median quality of life scores were significantly higher in Victoria compared to the rest of Australia (t2,827=2.25 p = 0.025). Being female (95 % CI, -0.051–0.020), having lower educational attainment (95 % CI, -0.089–-0.018), receiving government benefits (95 % CI, -0.054–-0.024), having small social networks (95 % CI, 0.006–0.009) and self-reported physical chronic health conditions were all independent predictors of lower quality of life.ConclusionsLonger-term studies are required to provide more robust evidence of the impact as restrictions lift and normal social conventions return.

Urban geographical patterns of the relationship between mobile communication, social networks and economic development – the case of Hungary

In the post-industrial age, the transformation of urban networks and urban regions was fundamentally influenced by the rapid spread of infocommunication technologies (ICT) and the Internet. People share information in their daily lives with the help of various ICT devices and ultimately generate georeferenced data that could obtain important information about people’s use of space, spatial movement and social connections. The main aim of the study is to explore the urban geographical and spatial impacts of ICT and social media networks in Hungarian cities. We focus on drawing territorial and settlement hierarchical patterns and clusters based on the mobile communication and online social network relationship data of Hungarian cities. The paper highlights the relationship between the intensity of mobile communication and the density and expansion of intercity social relations and the settlements’ level of economic development, respectively. The methodology is based on mobile phone call detail record (CDR) analysis and intercity network analysis of social media activities. Our findings suggest that different communication networks follow divergent spatial patterns in Hungary. The traditional East–West dichotomy of the Hungarian spatial divide is still reflected in mobile communication, but intercity clusters based on social media activities are usually aligned to the borders of administrative structures. In several cases, we were able to identify strong intercity links between settlements with a similar level of economic development of the mesolevel spatial structure that traverses over different counties and regional borders. Results on social and demographic issues suggest that ‘generation Z’ could play a key role in dampening the social and economic tensions created by the digital divide in the long run. Using a multidimensional explanatory model, we could demonstrate the growing interconnectedness between digital networks and economic development.

Two-sided matching based on I-BTM and LSGDM applied to high-level overseas talent and job fit problems

With the increasing number of overseas talent tasks in China, overseas talent and job fit are significant issues that aim to improve the utilization of this key human resource. Many studies based on fuzzy sets have been conducted on this topic. Among the many fuzzy set methods, intuitionistic fuzzy sets are usually utilized to express and handle the evaluation information. In recent years, various intuitionistic fuzzy decision-making methods have been rapidly developed and used to solve evaluation problems, but none of them can be used to solve the person-job fit problem with intuitionistic best-worst method (BWM) and TOPSIS methods considering large-scale group decision making (LSGDM) and evaluator social network relations (SNRs). Therefore, to solve problems of intuitionistic fuzzy information analysis and the LSGDM for high-level overseas talent and job fit, we construct a new hybrid two-sided matching method named I-BTM and an LSGDM method considering SNRs. On the one hand, to express the decision-making information more objectively and reasonably, we combine the BWM and TOPSIS in an intuitionistic environment. Additionally, we develop the LSGDM with optimized computer algorithms, where the evaluators’ attitudes are expressed by hesitant fuzzy language. Finally, we build a model of high-level overseas talent and job fit and establish a mutual criteria system that is applied to a case study to illustrate the efficiency and reasonableness of the model.

Overcoming constraints to immigrant entrepreneurship in Croatia: the role of formal and informal institutions

ABSTRACT This article investigates the role of socio-institutional constraints to immigrant entrepreneurship in post-communist countries of the Balkans. The study focuses on Croatia, a country where the immigrant population is still limited, but due to recent EU membership and sustained economic growth, it is expected to increase soon. The article draws upon a qualitative study based on semi-structured interviews with immigrant entrepreneurs and relevant stakeholders (including NGOs and research institutes’ representatives). The findings contribute to the mixed embeddedness and institutional theories, as the study demonstrates a growing potential of immigrant entrepreneurship in Croatia, but also persistent barriers connected both with formal and informal institutions in the country. Interestingly, the informal institutions often present even a bigger obstacle for entrepreneurs originating from less developed, non-European countries than the formal ones. This finding indicates a moderating role of social and cultural capital in assessing informal institutions. As the foreign population in Croatia is still very small, immigrants cannot reap the benefits of ethnic concentration and ethnic solidarity. Therefore, for most foreigners in Croatia the embeddedness in immigrant networks of social relations is very limited. Consequently, the shortages in social and cultural capital, combined with a very limited openness towards natives make the access to informal institutions in Croatia very difficult, which in turn discourages entrepreneurial initiatives among immigrants.

“The Forest Has Become Our New Living Room” – The Critical Importance of Urban Forests During the COVID-19 Pandemic

Out of nowhere the COVID-19 pandemic has turned people’s everyday lives upside down. Public places in urban areas were closed. However, leaving the house for recreational and leisure purposes in nature was still allowed in Germany – even during lockdown in March and April of 2020. As a result, urban forests have gained unprecedented importance – not only for recreational activities, but also for maintaining social contacts and coping with psychological stress. With these diverse requirements, many people have appropriated urban forests in new and changed ways. Using the example of the forests around the southern German city of Freiburg, a team of researchers from the Department of Societal Change at the Forest Research Institute Baden-Württemberg (FVA) carried out a mixed-method study to investigate how these appropriation practices are working and to shed some light on the relevance of forests for city residents in these circumstances. In addition to the statistical analysis of an online questionnaire, ethnographic observation data and Instagram posts were analyzed. This methodological triangulation was carried out in order to purposefully combine the strengths of each method while at the same time reducing the intrinsic biases and blind spots. This resulted in a better understanding of the importance of urban forest during this extraordinary period of time. Our results show that urban forests became critically important during the lockdown. Many visitors appropriated the forest with very different motives and for different purposes. For many visitors, the forest provided the same functions during this extraordinary period that public spaces otherwise do. The forest was not only consumed as a natural space, but also constructed by visitors as a social space. We can illustrate how this social meaning was both negotiated and reproduced. To provide an abstraction of our results, we refer to the theory of spatial appropriation as well as to new approaches in sociology of space that conceptualize space as a network of social relations. These results give rise to broader questions for future research projects, recreational forest research, forest and health, and forest planning.

I have a garden on the Internet! Searching for the farmer in a remotely controlled farming enterprise

Abstract. The paper examines the conceptual implications of using Smart Farming Technologies and digitalisation in small-scale food production, exemplified by the Austrian start-up “myAcker”. The company runs a hybrid system of gamified, remote-controlled agriculture, where its customers assume the role of “online gardeners” and take care of their own vegetables. Conceptually, it combines two different logics, namely the technology focus of vertical farming and algorithm-based control over operational processes, and the participatory, values-based elements of Alternative Food Networks like connectivity, sustainability, and ownership developed by online gardeners. Consequently, the dividing lines between producers, customers, and technology, as well as between virtual and physical, become blurred. Thus, the agency of technology becomes a co-constituent of agricultural work, life, and identity, which is itself co-constituted by human actors in a network of social relations. The case study shows the new potential and pitfalls of small-scale smart farming and digitalisation, making it necessary to conceptually revisit human–environment relations in the Actor Network Theory by more explicitly including technology as a bridging element.

Better together: Harnessing social relationships in smart energy communities

Social relationships can influence individual behaviours and personal choices, foster cooperation, and build solidarity. In this Perspective, we argue that harnessing social relationships connecting people living in the same community can help improve the functioning of smart local energy systems and facilitate cooperation towards shared objectives. These shared objectives could include reducing energy poverty, investing in clean technologies, and fostering energy justice. Therefore, we propose the new concept of smart energy neighbourhoods, which we define as a local energy system sharing (i) the same local energy infrastructure, (ii) a network of social relationships and group-focused concerns, and (iii) smart adaptive mechanisms enabling participation, coordination and cooperation. The paper discusses the beneficial role that smart energy neighbourhoods could play within future energy systems, their possible design, and key challenges for their implementation.

More than Meets the Tie: Examining the Role of Interpersonal Relationships in Social Networks

Topics in conversations depend in part on the type of interpersonal relationship between speakers, such as friendship, kinship, or romance. Identifying these relationships can provide a rich description of how individuals communicate and reveal how relationships influence the way people share information. Using a dataset of more than 9.6M dyads of Twitter users, we show how relationship types influence language use, topic diversity, communication frequencies, and diurnal patterns of conversations. These differences can be used to predict the relationship between two users, with the best predictive model achieving a macro F1 score of 0.70. We also demonstrate how relationship types influence communication dynamics through the task of predicting future retweets. Adding relationships as a feature to a strong baseline model increases the F1 and recall by 1% and 2%. The results of this study suggest relationship types have the potential to provide new insights into how communication and information diffusion occur in social networks.

Very Important Person Localization in Unconstrained Conditions: A New Benchmark

This paper presents a new high-quality dataset for Very Important Person Localization (VIPLoc), named Unconstrained-7k. Generally, current datasets: 1) are limited in scale; 2) built under simple and constrained conditions, where the number of disturbing non-VIPs is not large, the scene is relatively simple, and the face of VIP is always in frontal view and salient. To tackle these problems, the proposed Unconstrained-7k dataset is featured in two aspects. First, it contains over 7,000 annotated images, making it the largest VIPLoc dataset under unconstrained conditions to date. Second, our dataset is collected freely on the Internet, including multiple scenes, where images are in unconstrained conditions. VIPs in the new dataset are in different settings, e.g., large view variation, varying sizes, occluded, and complex scenes. Meanwhile, each image has more persons (> 20), making the dataset more challenging. As a minor contribution, motivated by the observation that VIPs are highly related to not only neighbors but also iconic objects, this paper proposes a Joint Social Relation and Individual Interaction Graph Neural Networks (JSRII-GNN) for VIPLoc. Experiments show that the JSRII-GNN yields competitive accuracy on NCAA (National Collegiate Athletic Association), MS (Multi-scene), and Unconstrained-7k datasets. https://github.com/xiaowang1516/VIPLoc.

Joint blockchain service vendor-platform selection using social network relationships: A multi-provider multi-user decision perspective

Blockchain technology has been widely touted for building and supporting supply chain management capabilities. The technology has substantial potential to enhance operational effectiveness and profitability. Blockchain platform evaluation and selection still requires investigation. Blockchain platform selection and adoption decision making in a multi-organizational supply chain context is complex. Effective blockchain adoption and operations requires consideration of multiple vendors—service providers—and platforms while satisfying multiple users and stakeholders. This study introduces a managerial decision support method to assist organizations evaluate and select joint blockchain service vendor and platforms for multiple organizational functions and organizations. Using literature and practice, we introduce blockchain service vendor and platform attributes from user, vendor, and platform perspectives. A social network theory lens sets the foundation for an innovative group decision-making method—a DEMATEL-based hierarchical best-worst method—integrating characteristics from this decision environment. The technological and distributed network nature of blockchain technology requires evaluation by decision makers from various levels of a supply chain network. These decision makers will likely have varying blockchain technology knowledge and subjective preferences that need integration. The proposed method helps to operationalize social network relationships to comprehend partial and idiosyncratic expert opinions about blockchain technology. An illustrative example and various scenarios are presented to identify managerial and research implications. Methodological limitations and future research are presented for this emergent managerial and technological concern across supply chains.

Community social networks, individual social participation and dietary behavior among older Japanese adults: Examining mediation using nonlinear structural equation models for three-wave longitudinal data

Community social networks positively affect older adults' dietary behavior, but the underlying mechanisms remain uncertain. This study investigated if the relationship between community social networks and dietary behavior is mediated by social participation, and whether the influence of community social networks differs across sociodemographic groups. We conducted a cross-lagged panel mediation analysis employing nonlinear structural equation modeling using panel data from the Japan Gerontological Evaluation Study (JAGES), a longitudinal study of Japanese older adults in 2010, 2013, and 2016, which included 11,347 men and 14,105 women aged over 65. Monodirectional relationships in community social networks, individual social participation, and fruit/vegetable intake were examined. Community social networks were associated with social participation regardless of sociodemographic conditions. Individual social participation was in turn, positively associated with fruit/vegetable intake, with this association being stronger among those living alone. Analyses further showed that individuals' social participation positively mediated the relationship between community social networks and fruit/vegetable intake. For both genders, the mediating effects were stronger among people living alone than in those living with someone. However, community networks could also directly and negatively affect fruit/vegetable intake among men who live alone unless they participated in community activities. Community social networks may promote social participation, thereby facilitating healthier dietary behavior regardless of sociodemographic status. Social participation in turn may positively contribute to the dietary health of people living alone. Community-based interventions to encourage people living alone to participate in social activities may help reduce inequality in dietary behavior related to cohabitation status.

A Data Transmission Algorithm Based on Triangle Link Structure Prediction in Opportunistic Social Networks

With the popularization of 5G communications, the scale of social networks has grown rapidly, and the types of messages have become increasingly complex. The rapid increases in the number of access nodes and the amount of data have put a greater burden on the transmission of information in the networks. However, when transferring data from a large number of users, the performance of traditional opportunistic network routing algorithms is insufficient, which often leads to problems such as high energy consumption, network congestion, and data packet loss. The way in which to improve this transmission environment has become a difficult task. Therefore, in order to ensure the effective transmission of data and reduce network congestion, this paper proposed a link prediction model based on triangular relationships in opportunistic social networks (LPMBT). In the topological structure of the social network, the algorithm scores links based on the frequency of use and selects the optimal relay node based on the score. It can also efficiently track the target node and reconstruct the sub-community. The simulation experimental results showed that the algorithm had excellent performance, effectively reduced overhead, reduced the end-to-end delay, and greatly improved the data transfer rate in the opportunistic network.

Reproductive Work in the Global South: Lived Experiences and Social Relations of Commercial Surrogacy in India

This article investigates reproductive work in the Global South which thrives on the commodification of women’s reproductive bodies under local-global reproductive hierarchies, appropriating the process of reproduction for production. Through a qualitative study of commercial surrogacy in north India, it examines the lived experiences of surrogates within the capitalist social relations they are embedded in. Conceptualising surrogacy as reproductive labour which contributes to value generation, the article assesses labour relations at the workplace, for example hostels where surrogates ‘live and work’, and the mechanisms of recruitment, contracting and control which function through dense networks of social and material relations between various stakeholders. The weak bargaining power of surrogates and the immense power of fertility clinics and agents are compounded by the lack of effective regulation and the state’s prohibitionist policy. The article argues for protecting the rights of surrogates as workers rather than the recent ban on surrogacy imposed in India.

New Network Models for the Analysis of Social Contagion in Organizations: An Introduction to Autologistic Actor Attribute Models

Autologistic actor attribute models (ALAAMs) provide new analytical opportunities to advance research on how individual attitudes, cognitions, behaviors, and outcomes diffuse through networks of social relations in which individuals in organizations are embedded. ALAAMs add to available statistical models of social contagion the possibility of formulating and testing competing hypotheses about the specific mechanisms that shape patterns of adoption/diffusion. The main objective of this article is to provide an introduction and a guide to the specification, estimation, interpretation and evaluation of ALAAMs. Using original data, we demonstrate the value of ALAAMs in an analysis of academic performance and social networks in a class of graduate management students. We find evidence that both high and low performance are contagious, that is, diffuse through social contact. However, the contagion mechanisms that contribute to the diffusion of high performance and low performance differ subtly and systematically. Our results help us identify new questions that ALAAMs allow us to ask, new answers they may be able to provide, and the constraints that need to be relaxed to facilitate their more general adoption in organizational research.