Suchergebnisse

Diverse online social networks are becoming increasingly interconnected by sharing information. Accordingly, emergent macro-level phenomena have been observed, such as the synchronous spread of information across different types of social media. Attempting to analyze the emergent global behavior is impossible from the examination of a single social platform, and dynamic influences between different social networks are not negligible. Furthermore, the underlying structural property of networks is important, as it drives the diffusion process in a stochastic way. In this paper, we propose a macro-level diffusion model with a probabilistic approach by combining both the heterogeneity and structural connectivity of social networks. As real-world phenomena, we explore instances of news diffusion across different social media platforms from a dataset that contains over 386 million web documents covering a one-month period in early 2011. We find that influence between different media types is varied by the context of information. News media are the most influential in the arts and economy categories, while social networking sites (SNS) and blog media are in the politics and culture categories, respectively. Furthermore, controversial topics, such as political protests and multiculturalism failure, tend to spread concurrently across social media, while entertainment topics, such as film releases and celebrities, are more likely driven by interactions within single social platforms. We expect that the proposed model applies to a wider class of diffusion phenomena in diverse fields and that it provides a way of interpreting the dynamics of diffusion in terms of the strength and directionality of influences among populations.

The article analyzes the role of political elites and the media in shaping public opinion and the direction of public attention. Focusing on the transformations in the social impact under the influence of network culture in the online communication environment, it examines how the role of traditional structures of power is transformed, and how this affects political culture, the formation of public opinion, and its participation in socio-political life. Social networks are a means of dialogue and organization, and this requires political elites and the media to consult and comply with active public opinion in the online communication environment.

Objective: We investigate the relation between having online and offline personal networks and employment for male and female migrants in the Netherlands. Background: Previous research diagnoses an alarming gender gap for migrants in their employment patterns. Although social networks are identified as being crucial for migrants' labor market participation, we know very little about how migrant men and women differ in their social networks and how these differences translate into varying employment opportunities. Method: Drawing on the Dutch Immigrant Panel of LISS (Longitudinal Internet Studies for the Social Sciences) dataset, we examined migrants' employment patters who have arrived to the Netherlands under different migration streams by conducting logistic regression models. Results: We identify two major findings. While contrary to our expectations, migrant women tend to be connected with those who are employed and with a Dutch background, less connected to men and have a rather dense network structure. Nonetheless, women's personal networks do not significantly account for their unemployment, but rather their less use of LinkedIn than migrant men. Conclusion: Our findings have implications in understanding network inequalities for female migrants in their labor market participation.

Die sozialen Netze spielen in Freizeit und Beruf eine immer größere Rolle: Auf 188 Seiten stellt ""c't extra soziale Netze"" die Social-Media-Welt vor, gibt praktische Tipps, greift Datenschutzthemen auf und zeigt, wie man beruflich davon profitiert. Das c't-Sonderheft erklärt, was die Online-Gemeinschaften antreibt und unterscheidet und wie Google und Facebook ihr Geld verdienen. Viele Praxisartikel helfen dabei, soziale Netze privat, als Verein, Freiberufler oder Unternehmen zu nutzen. Wir haben unter anderem Social-Media-Apps, Web-Hoster und Körper-Logger getestet, erklären im Detail die pa

Social capital's rise in popularity is a phenomenon many have noted (Kadushin, 2006; Warde and Tampubolon, 2002; Portes, 1998). Although the concept is a relatively old one, it is the works of Bourdieu (1986), Coleman (1988; 1990), and Putnam (1993, 2000) that often get credited for popularizing the concept. These three, while sharing a view that social networks are important for social groups and society, place differing levels of emphasis on the role of networks in building trust or the exchange of various types of resources. In this paper, I briefly revisit these three theorists, and the criticisms each have received, to provide background for discussing recent research on social capital from a social networks approach. The social network approach is then applied to my own case study looking at the relations among not-for-profits, and special attention is given to the unique context of not-for-profits, and how this context might elaborate or challenge current thoughts on social, aka 'network' capital. A final discussion is also given to some measurement problems with the network approach to social capital.

Information flow during catastrophic events is a critical aspect of disaster management. Modern communication platforms, in particular online social networks, provide an opportunity to study such flow and derive early-warning sensors, thus improving emergency preparedness and response. Performance of the social networks sensor method, based on topological and behavioral properties derived from the "friendship paradox", is studied here for over 50 million Twitter messages posted before, during, and after Hurricane Sandy. We find that differences in users' network centrality effectively translate into moderate awareness advantage (up to 26 hours); and that geo-location of users within or outside of the hurricane-affected area plays a significant role in determining the scale of such an advantage. Emotional response appears to be universal regardless of the position in the network topology, and displays characteristic, easily detectable patterns, opening a possibility to implement a simple "sentiment sensing" technique that can detect and locate disasters. ; Yury Kryvasheyeu, Haohui Chen, Pascal Van Hentenryck and Manuel Cebrian acknowledge the support of the Australian Government represented by the Department of Broadband, Communications and Digital Economy; and the Australian Research Council through the ICT Centre of Excellence program. Esteban Moro acknowledges the support of Spanish Ministry of Science and Technology under grant FIS2013-47532-C3-3-P. This research was also supported by the Army Research Laboratory under Cooperative Agreement Numbers W911NF-09-2-0053 and W911NF-11-1-0363, the National Science Foundation under grant 0905645, and DARPA/Lockheed Martin Guard Dog Programme under PO 4100149822. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Information flow during catastrophic events is a critical aspect of disaster management. Modern communication platforms, in particular online social networks, provide an opportunity to study such flow and derive early-warning sensors, thus improving emergency preparedness and response. Performance of the social networks sensor method, based on topological and behavioral properties derived from the "friendship paradox", is studied here for over 50 million Twitter messages posted before, during, and after Hurricane Sandy. We find that differences in users' network centrality effectively translate into moderate awareness advantage (up to 26 hours); and that geo-location of users within or outside of the hurricane-affected area plays a significant role in determining the scale of such an advantage. Emotional response appears to be universal regardless of the position in the network topology, and displays characteristic, easily detectable patterns, opening a possibility to implement a simple "sentiment sensing" technique that can detect and locate disasters. ; Yury Kryvasheyeu, Haohui Chen, Pascal Van Hentenryck and Manuel Cebrian acknowledge the support of the Australian Government represented by the Department of Broadband, Communications and Digital Economy; and the Australian Research Council through the ICT Centre of Excellence program. Esteban Moro acknowledges the support of Spanish Ministry of Science and Technology under grant FIS2013-47532-C3-3-P. This research was also supported by the Army Research Laboratory under Cooperative Agreement Numbers W911NF-09-2-0053 and W911NF-11-1-0363, the National Science Foundation under grant 0905645, and DARPA/Lockheed Martin Guard Dog Programme under PO 4100149822. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.