Social Network Visualization Research Articles

Identifying Representative Textual Sources in Blog Networks

We apply methods from social network analysis and visualization to facilitate a study of the Irish blogosphere from a cultural studies perspective.We focus on solving the practical issues that arise when the goal is to perform textual analysis of the corpus produced by a network of bloggers. Previous studies into blogging networks have noted difficulties arising when trying to identify the extent and boundaries of these networks. As a response to calls for increasingly data-led approaches in media and cultural studies, we discuss a variety of social network analysis methods that can be used to identify which blogs can be seen as members of a posited “Irish blogging network” (and hence sources of textual material). We identify hub blogs, communities of sites corresponding to different topics, and representative bloggers within these communities. Based on this study, we propose a set of guidelines for researchers who wish to map out blogging networks.

Effect of three network visualizations on students' social‐cognitive engagement in online discussions

AbstractSocial learning analytics (SLA) tools are designed to visually demonstrate online discussions with a goal to foster student engagement. However, empirical studies indicate controversial results of the effect of SLA tools on student engagement. This design‐based research designs a student‐facing SLA tool to demonstrate discussions from three perspectives and further uses mixed methods to investigate the effects of the tool. Results indicate the tools have positive influences on increasing student social‐cognitive engagement. The social network visualization has positive influences on both socially active and inactive students; it particularly increases peripheral students' social engagement. The topic network visualization improves all students' perspective expressions, indicating that demonstrating students' interested topics may increase cognitive engagement. The cognitive network visualization triggers students' information sharing, which is considered as the beginning of online engagement development. Based on the results, this research proposes integrated implications by considering learning theory, pedagogical supports and tool development. Practitioner notesWhat is already known about this topic SLA tools are designed to turn learning data into actionable insights of student engagement. Network‐oriented, content‐oriented and process‐oriented analytics are three major approaches. Extant empirical studies indicate controversial results of the effect of SLA tools on student engagement. What this paper adds This research designs a SLA tool to demonstrate student engagement via three network visualizations. This research uses mixed methods to examine students' social‐cognitive engagement. Results show that the designed SLA tools have positive influences on increasing students' engagement. Implications for practice and/or policy Design of SLA tools needs to consider learner agency, disposition and characteristic in the local context. Instructors should deliberately guide students reflect on the information demonstrated in the SLA tool. Future SLA design should make integrate multiple analytic results to reflect engagement in varied ways.

Outbreak investigation of SARS-CoV-2 transmission in an emergency childcare centre.

ObjectiveTo characterize SARS-CoV-2 transmission following a COVID-19 outbreak in an emergency childcare centre (ECCC) in April 2020 in Quebec, Canada.MethodsThe study population consisted of all the children and employees who attended the ECCC as well as household contacts of the confirmed COVID-19 cases. Of the 120 individuals in the study, five cases were confirmed by epidemiological link and 25 were identified as COVID-19 by RT-PCR among which 19 were analyzed by viral whole genome sequencing. Descriptive epidemiology, social network visualization, and phylogenetic analysis were used to characterize viral transmission.ResultsPhylogenetic analysis identified two separate introductions of distinct lineages of SARS-CoV-2 and estimated an average effective reproductive number of Re = 1.9 (range 0.9–4.9) with a mean doubling time of 3.2 days (range 2.1–5.2). The first and most prevalent lineage was introduced by two asymptomatic children who were likely infected by their parent, a confirmed COVID-19 case working in a long-term care centre. Among infected household adults, attack rates were significantly higher in mothers than in fathers (risk ratio = 4.5; 95% CI 1.1–18.7). The extent of transmission makes it one of the largest documented outbreaks in a daycare in Canada.ConclusionThe analyses carried out showed the probable origin and direction of the transmission of the infection (adult-child, child-adult, and child-child), thus highlighting how asymptomatic children can efficiently transmit SARS-CoV-2.Supplementary InformationThe online version contains supplementary material available at 10.17269/s41997-021-00544-1.

A randomized wait-list controlled trial of a social support intervention for caregivers of patients with primary malignant brain tumor

BackgroundInformal family caregivers constitute an important and increasingly demanding role in the cancer healthcare system. This is especially true for caregivers of patients with primary malignant brain tumors based on the rapid progression of disease, including physical and cognitive debilitation. Informal social network resources such as friends and family can provide social support to caregivers, which lowers caregiver burden and improves overall quality of life. However, barriers to obtaining needed social support exist for caregivers. To address this need, our team developed and is assessing a multi-component caregiver support intervention that uses a blend of technology and personal contact to improve caregiver social support.MethodsWe are currently conducting a prospective, longitudinal 2-group randomized controlled trial which compares caregivers who receive the intervention to a wait-list control group. Only caregivers directly receive the intervention, but the patient-caregiver dyads are enrolled so we can assess outcomes in both. The 8-week intervention consists of two components: (1) The electronic Social Network Assessment Program, a web-based tool to visualize existing social support resources and provide a tailored list of additional resources; and (2) Caregiver Navigation, including weekly phone sessions with a Caregiver Navigator to address caregiver social support needs. Outcomes are assessed by questionnaires completed by the caregiver (baseline, 4-week, 8-week) and the cancer patient (baseline, and 8-week). At 8 weeks, caregivers in the wait-list condition may opt into the intervention. Our primary outcome is caregiver well-being; we also explore patient well-being and caregiver and patient health care utilization.DiscussionThis protocol describes a study testing a novel social support intervention that pairs a web-based social network visualization tool and resource list (eSNAP) with personalized caregiver navigation. This intervention is responsive to a family-centered model of care and calls for clinical and research priorities focused on informal caregiving research.Trial registrationclinicaltrials.gov, Registration number: NCT04268979; Date of registration: February 10, 2020, retrospectively registered.

The Health Crisis on Instagram: How the Media Are Building Their Agenda on the Visual Social Network During the COVID-19 Pandemic

Over the last decade social networks have become important channels for the media to publish information and communicate with their younger audi­ences, with Instagram recently becom­ing the most popular platform for this purpose. This article is an investigation into news production on this social net­work in the context of the international crisis generated by the COVID-19 pan­demic, by means of a content analysis of 552 posts published by the two most widely read Spanish newspapers. The results suggest that despite there being a large quantity of soft content and hu­man-interest stories, as found in previ­ous research, Instagram is also used as a platform to distribute information of public interest about the management of the crisis (such as political decisions and health content). Keywords: social networks, Instagram, journalism, COVID-19, agenda.

Picture perfect? Examining associations between relationship quality, attention to alternatives, and couples’ activities on Instagram

What do couples’ activities and behaviors on Instagram reveal about the quality of their relationships? To answer this question, we surveyed couples ( N = 178) about their perceptions of their relationships and analyzed 3,270 of their recent Instagram posts. Actor and partner effects were found between relational quality and engagement with the relationship on Instagram (i.e., the number of couple pictures and partner-initiated likes and comments). There were also actor effects of attention to Instagram alternatives on the perceived quality and actual pursuit of alternative partners, as well as a partner effect on alternative quality. The findings contribute to extending the investment model to the digital age and have methodological implications for understanding relationship dynamics on visual social network sites.

Social Network Analysis and Visualization of Arabic Tweets During the COVID-19 Pandemic

Twitter data have been used widely in times of pandemics and crises. Currently, the world is suffering from the outbreak of new coronavirus disease 2019 (COVID-19), in which the COVID-19 virus has infected more than one hundred and twenty million people worldwide with more than two million deaths. Consequently, people tend to share COVID-19-related content on social media extensively. As a new pandemic, only a small number of studies have been conducted to analyze COVID-19-related tweets, and even fewer were meant for Arabic tweets. This research explores the influence of the COVID-19 pandemic on Saudi users’ tweeting behavior. In particular, the research adopts a social network analysis (SNA) for COVID-19 Arabic tweets. This approach is interesting, as it is based on analysis of social structures, such as Twitter users and the relationships among them, through the use of networks and graph theory without the contents of the tweets themselves. Based on 8905 collected Arabic tweets, this research resulted in three main contributions: 1) a visualization of the social network for COVID-19 tweets of Saudi users, 2) an identification of information sources that Twitter users employ during the COVID-19 pandemic, and 3) an identification of the most popular influencers among users of COVID-19 tweets. The results of this study may help identify the most popular Twitter influencers and those who deliver the information to Twitter users, utilizing them to increase awareness and deliver information and instructions to overcome the COVID-19 pandemic.

Mapping the Topics and Evolutions of Chinese Children’s Bestsellers

Abstract Children’s books involve a large number of topics. Research on them has been paid much attention to by both scholars and practitioners. However, the existing achievements do not focus on China, which is the fastest growing market for children’s books in the world. Studies using quantitative analysis are low in number, especially on the intellectual structure, evolution patterns, and development trends of topics of children’s bestsellers in China. Dangdang.com, the biggest Chinese online bookstore, was chosen as a data source to obtain children’s bestsellers, and topic words in them were extracted from brief introductions. With the aid of co-occurrence theory and tools of social network analysis and visualization, the distribution, correlation structures, and evolution patterns of topics were revealed and visualized. This study shows that topics of Chinese children’s bestsellers are broad and relatively concentrated, but their distribution is unbalanced. There are four distinguished topic communities (Living, Animal, World, and Child) in terms of centrality and maturity, and they all establish their individual systems and tend to be mature. The evolution of these communities tends to be stable with powerful continuity.

The role of facial expression and tie strength in sender presence effects on consumers’ brand responses towards visual brand-related user generated content

The popularity of visual social network site Instagram has led to an increase of visual brand-related user-generated content (Br-UGC), which has the potential to affect brand outcomes. Previous research identified sender presence as an important content characteristic that can influence consumer's brand responses. However, the effect of sender presence in visual Br-UGC seems to be different from that of traditional advertising. The current research extends this sender presence scholarship by examining two explanations for the effects of sender presence: sender facial expression, and tie strength between sender and receiver. We expect that the effects of sender presence will be stronger for happy-as compared to neutral-looking senders, and that these effects are stronger when there is a stronger tie between sender and receiver. The current research adopts a two-step approach to examine sender presence effects in various levels of tie strength. Results show that a happy facial expression significantly increases like intention and brand attitude. Moreover, there is a moderating effect of tie strength on sender presence for comment intention: stronger levels of tie strength result in stronger effects of the presence of the sender. Theoretical and practical implications are discussed.

Supporting Youth Activists? Strategic Use of Social Media

Social Networking Sites (SNS) provide a platform for engaging youth in activism (e.g., by helping mobilize civic action). While youth typically employ casual approaches to online activism (i.e., quick actions, such as broadcast posts to advertise social justice events), more strategic practices (i.e., those that are more creative and informed) can increase the likelihood of successful online campaigns. However, little work has examined how youth activists can be supported to use SNS more strategically. To address this research gap, we conducted interviews with youth activists, exploring how youth made sense of social network visualizations and their perspectives on how such tools could support their activism efforts. Our findings characterize how participants made inferences about followers? identities based on their hashtag use, and how they used those inferences in outreach decisions. We conclude with design implications for future research in this area.

Who talks to whom: an evaluation of a call log visualization

Adding temporal information to social network visualizations is still a challenging task despite previous research efforts. Visualizing call logs on an event-based level can show various attributes of a connection. The dimension time is of great interest to analysts as it offers insights into trends and patterns such as changing relationships between different actors or economic opportunities for businesses. Yet current approaches suffer from limitations that can be improved with the visualization design presented in this work. Our presented visualization was developed considering aesthetic criteria and characteristics of adjacency matrices and node-link diagrams. A heuristic evaluation according to these criteria was conducted. In a formative evaluation process, an artificial dataset was specifically created to examine dynamic social networks. A qualitative user study with observation and think-aloud protocols was conducted and analyzed with regard to the user’s strategies, limitations of the visualization and potential additional features. The visualization appears to be suitable for all of the evaluated network tasks; however, path-related tasks were more challenging than other tasks.Graphical abstract

Digital humanities research: interdisciplinary collaborations, themes and implications to library and information science

PurposeThe purpose of this paper is to examine the structure, patterns and themes of interdisciplinary collaborations in the digital humanities (DH) research through the application of social network analysis and visualization tools.Design/methodology/approachThe sample includes articles containing DH research in the Web of Science Core Collection as of December 2018. First, co-occurrence data representing collaborations among disciplinary were extracted from the subject category. Second, the descriptive statistics, network indicators and interdisciplinary communities were calculated. Third, the research topics of different interdisciplinary collaboration communities based on system keywords, author keywords, title and abstracts were detected.FindingsThe findings reveal that while the scope of disciplines involved in DH research is broad and evolving over time, most interdisciplinary collaborations are concentrated among several disciplines, including computer science, library and information science, linguistics and literature. The study further uncovers some communities based on closely collaborating disciplines and the evolving nature of such interdisciplinary collaboration communities over time. To better understand the close collaboration ties, the study traces and analyzes the research topics and themes of the interdisciplinary communities. Finally, the implications of the findings for DH research are discussed.Originality/valueThis study applied various informetric methods and tools to reveal the collaboration structure, patterns and themes among disciplinaries in DH research.

Method of social network analysis and visualisation based on reviews

With the development of e-commerce platforms, the huge amount of transaction volume produces a lot of commentary information. To study the relationship between users and user comments and corresponding products, a social network analysis method based on user comments is proposed. The authors regard the network connection between goods and user comments as a problem on the network and use the spectral clustering algorithm to maintain the structural characteristics of the network. This method can visualise the network structure features such as user clustering and distribution, which can help to understand the network from a macro perspective and be directly applied to the visualisation of other comment-based networks. It is significant for analysing the relationship between users and user comments and corresponding products. The comparative visualisation experiments are also discussed, to validate the effectiveness of the proposed method.

Behaviour of young Czechs on the digital network with a special focus on YouTube. An analytical study

With the advent of the Internet, young people make up the largest percentage of the Czech population who spend the most time interacting with the digital network and the various tools it offers. In order to find out what activity they carry out within the digital network, this research was undertaken, which aims to find out how young Czechs spend their time when they are using the digital network. To this end, 27,177 young Czechs between the ages of 7 and 18 were sampled. (n = 27,177). Specifically, the aim was to find out which websites they spent the most time on, the types of social networks they used, the nature of the content they viewed, as well as whether they had suffered any kind of ill-treatment through the digital network. The results of the descriptive analyses allowed to elucidate that: (1): the young participants make use of visual social networks, such as Youtube; (2) most of the content they consume is linked to funny videos, challenges or gameplays; (3) It is of great concern that a large part of the sample has been the victim of verbal insults or cases of personal account theft or has been the victim of distribution of personal images without prior consent. Based on these results, it is intended to establish the focus on the possible consequences of these findings, especially in establishing prevention measures that confront the cyberbullyng in view of the possible consequences.

The centrality of immigrant students within teacher-student interaction networks: A relational approach to educational inclusion

The conceptualizations of educational inclusion, previously restricted to securing access to formal education, recently highlight the promotion of equitable social and academic relations as well. This study investigates the inclusion of students with immigrant background within their class’ teacher-student interaction networks, while distinguishing by the initiator and content of interactions. Data from 38 Chilean mathematics teachers/classrooms and 933 seventh graders were collected and analyzed using systematic observation, social network visualization and multilevel models. Results show that the inclusion of students depends significantly on their country of origin. There is also significant variation in teacher-immigrant student interactions across classrooms.

Peasant micropower in an agrifood supply system of the Sierra Madre of Chiapas, Mexico

In recent years, rural studies have transitioned from analyzing internal agrarian dynamics within peasant societies to exploring contractual relationships in a vertical manner between agribusiness and peasants with respect to food production and marketing. The present study follows the tradition of classical agrarian research in order to develop an ascendant Foucauldian analysis that is both genealogical (historical) and critical (addressing current effects) of peasant micropower that domestic groups reproduce in their local agrifood supply system in six ejidos of the Sierra Madre region of Chiapas, Mexico. This study used a mixed methodology consisting of a regional ethnography, surveys regarding the peasant economy with 120 domestic groups, interviews with founders of the rural communities and directors of local peasant organizations, factorial statistical and cluster analyses, and visualization of social networks. As a result of the study, we (a) elucidate sociohistorical conditions that have resulted in differentiation among different types of peasants within the micro-region, (b) analyze contemporary social dynamics that have led to polarization between two principal sets of domestic groups based on their means of production, and (c) show how the fact that the majority of domestic groups of the micro-region experience seasonal food scarcity and lack formal employment has led to low rural wages and monopolization of the internal agrifood supply system by those peasants who have greater means of production. We conclude by reflecting on peasant micropower as a phenomenon that can be found in social relations of many agrarian regions around the world, in which the challenge would be to understand its processes of reproduction, analyze effects of this micropower, and propose alternative academic approaches that may contribute to generating public policy and political action to counteract rural inequality. • Peasant micropower is reproduced in many rural regions around the world. • Studying peasant micropower requires ascendant rather than vertical analyses. • Many rural social programs disregard peasant micropower and thereby reinforce it. • Academic research should contribute to counteract inequality reproduced by peasant micropower.

Cross-national digital humanities research collaborations: structure, patterns and themes

PurposeThe purpose of this paper is to examine the structure, patterns and themes of cross-national collaborations in Digital Humanities research through the application of social network analysis and visualization tools.Design/methodology/approachThe sample includes articles containing Digital Humanities research in the Web of Science Core Collection as of December 2018. First, co-occurrence data representing collaborations among nations were extracted from author affiliations. Second, the descriptive statistics, network indicators and international communities were calculated. Third, the research topics of different cross-national collaboration communities based on ISI keywords, author keywords, title and abstracts were detected.FindingsThe results show that the scope of international collaborations in Digital Humanities research is broad, but the distribution among nations is unbalanced. The USA, Germany and England were identified as the major contributors. Five research communities are identified, led by the USA, Germany, England, Belgium and France. The communities share common research topics such as history, GIS, text mining, visualization, while each has its own research emphasis.Originality/valueThis study applied various informetric methods and tools to reveal the collaboration structure, patterns and themes among nations in Digital Humanities research.

Public Reactions to the Cigarette Control Regulation on a Chinese Microblogging Platform: Empirical Analysis.

BackgroundOn January 1, 2019, a new regulation on the control of smoking in public places was officially implemented in Hangzhou, China. On the day of the implementation, a large number of Chinese media reported the contents of the regulation on the microblog platform Weibo, causing a strong response from and heated discussion among netizens.ObjectiveThis study aimed to conduct a content and network analysis to examine topics and patterns in the social media response to the new regulation.MethodsWe analyzed all microblogs on Weibo that mentioned and explained the regulation in the first 8 days following the implementation. We conducted a content analysis on these microblogs and used social network visualization and descriptive statistics to identify key users and key microblogs.ResultsOf 7924 microblogs, 12.85% (1018/7924) were in support of the smoking control regulation, 84.12% (6666/7924) were neutral, and 1.31% (104/7924) were opposed to the smoking regulation control. For the negative posts, the public had doubts about the intentions of the policy, its implementation, and the regulations on electronic cigarettes. In addition, 1.72% (136/7924) were irrelevant to the smoking regulation control. Among the 1043 users who explicitly expressed their positive or negative attitude toward the policy, a large proportion of users showed supportive attitudes (956/1043, 91.66%). A total of 5 topics and 11 subtopics were identified.ConclusionsThis study used a content and network analysis to examine topics and patterns in the social media response to the new smoking regulation. We found that the number of posts with a positive attitude toward the regulation was considerably higher than that of the posts with a negative attitude toward the regulation. Our findings may assist public health policy makers to better understand the policy’s intentions, scope, and potential effects on public interest and support evidence-based public health regulations in the future.

Intellectual Structure and Evolutionary Trends of Precision Medicine Research: Coword Analysis.

BackgroundPrecision medicine (PM) is playing a more and more important role in clinical practice. In recent years, the scale of PM research has been growing rapidly. Many reviews have been published to facilitate a better understanding of the status of PM research. However, there is still a lack of research on the intellectual structure in terms of topics.ObjectiveThis study aimed to identify the intellectual structure and evolutionary trends of PM research through the application of various social network analysis and visualization methods.MethodsThe bibliographies of papers published between 2009 and 2018 were extracted from the Web of Science database. Based on the statistics of keywords in the papers, a coword network was generated and used to calculate network indicators of both the entire network and local networks. Communities were then detected to identify subdirections of PM research. Topological maps of networks, including networks between communities and within each community, were drawn to reveal the correlation structure. An evolutionary graph and a strategic graph were finally produced to reveal research venation and trends in discipline communities.ResultsThe results showed that PM research involves extensive themes and, overall, is not balanced. A minority of themes with a high frequency and network indicators, such as Biomarkers, Genomics, Cancer, Therapy, Genetics, Drug, Target Therapy, Pharmacogenomics, Pharmacogenetics, and Molecular, can be considered the core areas of PM research. However, there were five balanced theme directions with distinguished status and tendencies: Cancer, Biomarkers, Genomics, Drug, and Therapy. These were shown to be the main branches that were both focused and well developed. Therapy, though, was shown to be isolated and undeveloped.ConclusionsThe hotspots, structures, evolutions, and development trends of PM research in the past ten years were revealed using social network analysis and visualization. In general, PM research is unbalanced, but its subdirections are balanced. The clear evolutionary and developmental trend indicates that PM research has matured in recent years. The implications of this study involving PM research will provide reasonable and effective support for researchers, funders, policymakers, and clinicians.

МОДЕЛЮВАННЯ І ВІЗУАЛІЗАЦІЯ СОЦІАЛЬНИХ МЕРЕЖ

МОДЕЛЮВАННЯ І ВІЗУАЛІЗАЦІЯ СОЦІАЛЬНИХ МЕРЕЖ