Evolution of audience duplication networks among social networking sites: Exploring the influences of preferential attachment, audience size, and niche width

2021 ◽  
pp. 146144482199304
Author(s):  
Yu Xu
Keyword(s):  
Social Networking ◽  
Social Networking Sites ◽  
Preferential Attachment ◽  
Graph Model ◽  
Structural Features ◽  
Niche Width ◽  
Random Graph Model ◽  
Exponential Random Graph ◽  
The Us ◽  
Audience Size

This study examines the evolution of social networking sites (SNSs) from a networked audience duplication perspective. Guided by social network theory, the theory of double jeopardy, and niche theory, this study proposes an integrated framework to explain the evolution of SNS choices of the US audience between 2016 and 2019. Shared traffic data were retrieved from comScore’s Media Metrix Multi-Platform database. The empirical results of the separable temporal exponential random graph model (STERGM) confirm that preferential attachment, audience size, and niche width significantly drive the likelihood of tie formation and dissolution in the evolving audience duplication network. These effects hold true even when other endogenous structural features and exogenous nodal attributes are taken into account. Theoretical implications for the networked media landscape are discussed.

scholarly journals Symptom and Age Homophilies in SARS-CoV-2 Transmission Networks during the Early Phase of the Pandemic in Japan

Biology ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 499
Author(s):  
Ali Andalibi ◽  
Naoru Koizumi ◽  
Meng-Hao Li ◽  
Abu Bakkar Siddique
Keyword(s):  
Early Stage ◽  
Graph Model ◽  
Initial Response ◽  
Contact Tracing ◽  
Pcr Analysis ◽  
Exponential Random Graph Model ◽  
Transmission Networks ◽  
Random Graph Model ◽  
Healthcare Settings ◽  
Exponential Random Graph

Kanagawa and Hokkaido were affected by COVID-19 in the early stage of the pandemic. Japan’s initial response included contact tracing and PCR analysis on anyone who was suspected of having been exposed to SARS-CoV-2. In this retrospective study, we analyzed publicly available COVID-19 registry data from Kanagawa and Hokkaido (n = 4392). Exponential random graph model (ERGM) network analysis was performed to examine demographic and symptomological homophilies. Age, symptomatic, and asymptomatic status homophilies were seen in both prefectures. Symptom homophilies suggest that nuanced genetic differences in the virus may affect its epithelial cell type range and can result in the diversity of symptoms seen in individuals infected by SARS-CoV-2. Environmental variables such as temperature and humidity may also play a role in the overall pathogenesis of the virus. A higher level of asymptomatic transmission was observed in Kanagawa. Moreover, patients who contracted the virus through secondary or tertiary contacts were shown to be asymptomatic more frequently than those who contracted it from primary cases. Additionally, most of the transmissions stopped at the primary and secondary levels. As expected, significant viral transmission was seen in healthcare settings.

Affective Ties That Bind: Investigating the Affordances of Social Networking Sites for Commemoration of Traumatic Events

2018 ◽  
Vol 37 (3) ◽  
pp. 333-354 ◽  
Author(s):  
Yunya Song ◽  
Ran Xu
Keyword(s):  
Social Networking ◽  
Social Networking Sites ◽  
Traumatic Event ◽  
Preferential Attachment ◽  
Chinese History ◽  
Geographic Proximity ◽  
Data Set ◽  
Mass Trauma ◽  
Nanjing Massacre ◽  
Negative Feelings

Social networking sites (SNSs) facilitate self-expression and promote social connections. There has been growing scholarly attention to the affect-charged collectivities created online in the aftermath of disasters and mass traumas. This study was designed to examine how individuals affiliate in SNS-based commemoration of a mass trauma, taking advantage of a large Weibo (the Chinese equivalent of Twitter) data set which captures users’ responses over 4 years to the anniversary of the Nanjing massacre, a major traumatic event in Chinese history. Machine learning–based content analysis was combined with dyadic-level network analysis to examine the content Weibo users create and the conversational structures they formed. The results reveal that homophily, geographic proximity, and preferential attachment work in tandem with displays of emotion to influence the formation of online conversational ties. Expressions of negative emotions were found to facilitate or inhibit the homophily effect. Being exposed to the display of anger amplifies the homophily effect among the users, while sadness weakens it. The findings point to the importance of examining specific emotions rather than global (positive–negative) feelings in understanding the dynamics of SNS-based interaction.

scholarly journals A Case-Control Study to Identify Community Venues Associated with Genetically-clustered, Multidrug-resistant Tuberculosis Disease in Lima, Peru

2018 ◽  
Vol 68 (9) ◽  
pp. 1547-1555
Author(s):  
David P Bui ◽  
Eyal Oren ◽  
Denise J Roe ◽  
Heidi E Brown ◽  
Robin B Harris ◽  
...  
Keyword(s):  
Graph Model ◽  
Multidrug Resistant ◽  
Random Graph Model ◽  
Tuberculosis Transmission ◽  
Resistant Tuberculosis ◽  
Multidrug Resistant Tuberculosis ◽  
Exponential Random Graph ◽  
The Social ◽  
Community Segregation ◽  
Tuberculosis Disease

Abstract Background The majority of tuberculosis transmission occurs in community settings. Our primary aim in this study was to assess the association between exposure to community venues and multidrug-resistant (MDR) tuberculosis. Our secondary aim was to describe the social networks of MDR tuberculosis cases and controls. Methods We recruited laboratory-confirmed MDR tuberculosis cases and community controls that were matched on age and sex. Whole-genome sequencing was used to identify genetically clustered cases. Venue tracing interviews (nonblinded) were conducted to enumerate community venues frequented by participants. Logistic regression was used to assess the association between MDR tuberculosis and person-time spent in community venues. A location-based social network was constructed, with respondents connected if they reported frequenting the same venue, and an exponential random graph model (ERGM) was fitted to model the network. Results We enrolled 59 cases and 65 controls. Participants reported 729 unique venues. The mean number of venues reported was similar in both groups (P = .92). Person-time in healthcare venues (adjusted odds ratio [aOR] = 1.67, P = .01), schools (aOR = 1.53, P < .01), and transportation venues (aOR = 1.25, P = .03) was associated with MDR tuberculosis. Healthcare venues, markets, cinemas, and transportation venues were commonly shared among clustered cases. The ERGM indicated significant community segregation between cases and controls. Case networks were more densely connected. Conclusions Exposure to healthcare venues, schools, and transportation venues was associated with MDR tuberculosis. Intervention across the segregated network of case venues may be necessary to effectively stem transmission.

scholarly journals The drivers of regulatory networking: policy learning between homophily and convergence

2018 ◽  
Vol 39 (3) ◽  
pp. 443-464 ◽  
Author(s):  
Francesca P. Vantaggiato
Keyword(s):  
Regulatory Networks ◽  
Graph Model ◽  
Exponential Random Graph Model ◽  
Random Graph Model ◽  
Market Structures ◽  
Exponential Random Graph ◽  
Policy Frameworks ◽  
Regulatory Coordination ◽  
Regular Network ◽  
The Eu

AbstractThe literature on transnational regulatory networks identified interdependence as their main rationale, downplaying domestic factors. Typically, relevant contributions use the word “network” only metaphorically. Yet, informal ties between regulators constitute networked structures of collaboration, which can be measured and explained. Regulators choose their frequent, regular network partners. What explains those choices? This article develops an Exponential Random Graph Model of the network of European national energy regulators to identify the drivers of informal regulatory networking. The results show that regulators tend to network with peers who regulate similarly organised market structures. Geography and European policy frameworks also play a role. Overall, the British regulator is significantly more active and influential than its peers, and a divide emerges between regulators from EU-15 and others. Therefore, formal frameworks of cooperation (i.e. a European Agency) were probably necessary to foster regulatory coordination across the EU.

VARIETIES OF INTERGOVERNMENTAL ORGANIZATION MEMBERSHIPS AND STRUCTURAL EFFECTS IN THE WORLD TRADE NETWORK

2018 ◽  
Vol 21 (02) ◽  
pp. 1850001 ◽  
Author(s):  
ZHENGQI PAN
Keyword(s):  
World Trade ◽  
Bilateral Trade ◽  
Graph Model ◽  
General Purpose ◽  
Intergovernmental Organizations ◽  
Random Graph Model ◽  
Intergovernmental Organization ◽  
Exponential Random Graph ◽  
The World ◽  
Joint Membership

To what extent does joint membership in intergovernmental organizations (IGOs) matter for bilateral trade? How and under what conditions do the various types of IGOs — economic, socio-cultural and general purpose — influence bilateral trade between their members? How do complex interdependencies in world trade matter? Existing research tends to examine aggregate joint IGO memberships and has done little to analyze how specific types of IGO membership matter in trade. Using a detailed IGO dataset and a novel network analysis approach called the temporal exponential random graph model, I assess the importance of three main IGO types — economic, socio-cultural and general purpose — in helping members to establish major trading ties. The results provide support for general purpose and socio-cultural IGOs and point to the importance of network phenomena such as popularity, activity and transitivity effects. Moreover, joint economic IGO memberships exhibit slightly more complex relations with bilateral trade. A robustness test reveals that preferential trade agreements are significant in fostering trade, while the World Trade Organization and other economic IGOs such as development banks are not. This paper presents a nuanced way of analyzing IGOs and provides the impetus for the study of complex interdependencies in international trade.

Women trafficking networks: Structure and stages of women trafficking in five Dutch small-scale networks

2021 ◽  
pp. 147737082110531
Author(s):  
Tomáš Diviák ◽  
Jan Kornelis Dijkstra ◽  
Fenna van der Wijk ◽  
Indra Oosting ◽  
Gerard Wolters
Keyword(s):  
Law Enforcement ◽  
Graph Model ◽  
Small Scale ◽  
Law Enforcement Agencies ◽  
Random Graph Model ◽  
Exponential Random Graph ◽  
A Cell ◽  
Women Trafficking ◽  
The One ◽  
Networks Structure

In this study, we investigated the relation between the different stages of women trafficking (i.e. recruitment, entrance, accommodation, labor, and finance) and the structure of five criminal networks involved in women trafficking in the Netherlands ( Ns ranging from 6 to 15). On the one hand, it could be argued that for efficiency and avoidance of being detected by law enforcement agencies, the network structure might align with the different stages, resulting in a cell-structured network with collaboration between actors within rather than across stages. On the other hand, criminal actors might prefer to collaborate and rely on a few others, whom they trust in order to circumvent the lack of formal opportunities to enforce collaboration and agreements, resulting in a core-periphery network with actors also collaborating across stages. Results indicate that three of the five networks were characterized by a core-periphery structure, whereas the two other networks exhibit a mixture of both a cell-structured and core-periphery network. Furthermore, using an Exponential Random Graph Model (ERGM), we found that actors were likely to form ties with each other in the stages of recruitment, accommodation, and exploitation, but not in the stages of transport and finance.

Engaging Consumers via Twitter

2015 ◽  
pp. 91-109
Author(s):  
Veronica Ravaglia ◽  
Eleonora Brivio ◽  
Guendalina Graffigna
Keyword(s):  
Social Networking ◽  
Social Networking Sites ◽  
Methodological Approach ◽  
Structural Features ◽  
Shared Values ◽  
Behavioral Factors ◽  
Brand Communication ◽  
Shared Reality ◽  
Brand Engagement ◽  
Interactive Nature

The interactive nature of social networking sites contributes to reinforce engagement between consumers and brands in terms of co-creation of shared values. According to Hollebeek (2011), consumer-brand engagement (CBE) implies cognitive, emotional, behavioral factors, which connect a brand with its followers. This chapter will show three successful Twitter strategies from three different brands, using a methodological approach focusing on the relational conditions that turn a brand into an engaging player on Twitter. Interviews with brand communication managers and followers were conducted. Moreover, initiatives were explored through the stream of tweets produced around the brands; pragmatic, semantic, syntactic and structural features of tweets were considered. Results show that, while the three initiatives considered here lean on a cognitive-based CBE, a full engagement in the/a brand's world is needed to build a long-lasting and successful relationship between brand and consumer, in order to co-construct a future shared reality.

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