Measuring social dynamics in a massive multiplayer online game

Quantification of human group-behavior has so far defied an empirical, falsifiable approach. This is due to tremendous difficulties in data acquisition of social systems. Massive multiplayer online games (MMOG) provide a fascinating new way of observing hundreds of thousands of simultaneously socially interacting individuals engaged in virtual economic activities. We have compiled a data set consisting of practically all actions of all players over a period of 3 years from a MMOG played by 300,000 people. This large-scale data set of a socio-economic unit contains all social and economic data from a single and coherent source. Players have to generate a virtual income through economic activities to ‘survive’ and are typically engaged in a multitude of social activities offered within the game. Our analysis of high-frequency log files focuses on three types of social networks, and tests a series of social-dynamics hypotheses. In particular we study the structure and dynamics of friend-, enemy- and communication networks. We find striking differences in topological structure between positive (friend) and negative (enemy) tie networks. All networks confirm the recently observed phenomenon of network densification. We propose two approximate social laws in communication networks, the first expressing betweenness centrality as the inverse square of the overlap, the second relating communication strength to the cube of the overlap. These empirical laws provide strong quantitative evidence for the Weak ties hypothesis of Granovetter. Further, the analysis of triad significance profiles validates well-established assertions from social balance theory. We find overrepresentation (underrepresentation) of complete (incomplete) triads in networks of positive ties, and vice versa for networks of negative ties. Empirical transition probabilities between triad classes provide evidence for triadic closure with extraordinarily high precision. For the first time we provide empirical results for large-scale networks of negative social ties. Whenever possible we compare our findings with data from non-virtual human groups and provide further evidence that online game communities serve as a valid model for a wide class of human societies. With this setup we demonstrate the feasibility for establishing a ‘socio-economic laboratory’ which allows to operate at levels of precision approaching those of the natural sciences.All data used in this study is fully anonymized; the authors have the written consent to publish from the legal department of the Medical University of Vienna.     

Perspective-taking and memory capacity predict social network size

Human social networks typically consist of a hierarchically organized series of grouping levels. There is, however, considerable variation between individuals in the sizes of any given network layer. We test between two possible factors (memory capacity and theory of mind) that might limit the size of two different levels within human social networks (support cliques and sympathy groups). We show that the size of an individual's support clique (the number of individual's in the innermost circle of friends) is better explained by individual differences in social cognition (mentalising skills). However, the size of the sympathy group (the most frequent social partners) is better explained by individual's performance on memory tasks.     

What is gained and what is left to be done when content analysis is added to network analysis in the study of a social movement: Twitter use during Gezi Park

As social movements relying on the weak ties found in social networks have spread around the world, researchers have taken several approaches to understanding how networks function in such instances as the Arab Spring. While social scientists have primarily relied on survey or content analysis methodology, network scientists have used social network analysis. This research combines content analysis with the automated techniques of network analysis to determine the roles played by those using Twitter to communicate during the Turkish Gezi Park uprising. Based on a network analysis of nearly 2.4 million tweets and a content analysis of a subset of 5126 of those tweets, we found that information sharing was by far the most common use of the tweets and retweets, while tweets that indicated leadership of the movement constituted a small percentage of the overall number of tweets. Using automated techniques, we experimented with coded variables from content analysis to compute the most discriminative tokens and to predict values for each variable using only textual information. We achieved 0.61 precision on identifying types of shared information. Our results on detecting the position of user in the protest and purpose of the tweets achieved 0.42 and 0.33 precision, respectively, illustrating the necessity of user cooperation and the shortcomings of automated techniques. Based on annotated values of user tweets, we computed similarities between users considering their information production and consumption. User similarities are used to compute clusters of individuals with similar behaviors, and we interpreted average activities for those groups.     

Strategies for Measuring and Promoting Mothers' Social Support Networks

ABSTRACT

This chapter recommends respondent-driven sampling (RDS) and peer-driven intervention (PDI) as new strategies for improving safe motherhood and women's health in countries where women have limited access to information and communication technology. Strategies for measuring and promoting mothers' social support networks could be applied to enrich communication about reproductive health and safe motherhood, especially in countries where women's low social status leads to child marriage, low educational attainment/illiteracy, and limited access to modern information and communication technology. By using RDS to study communities and social network structures, outreach workers can educate women via women's social support groups, enhancing and broadening the use of modern information and communication technologies. RDS is a strategy that allows researchers to identify and focus on distinct groups within a community. PDI uses a two-step intervention where respondents are educated by outreach workers and previous participants (members of social support groups). Limitations of these approaches are also discussed.     

Mobility types,transnational ties and personal networks in four highly skilled immigrant communities in Seville (Spain)

In this study, we explore how different mobility patterns influence the composition and structure of the transnational social support networks and how personal networks allow us to elicit insightful data of mobile individuals. Ninety-five mobile individuals were selected from four distinct communities based in Seville (Spain), namely: Erasmus students, Flamenco artists, musicians from the symphonic orchestra and partners of European Commission researchers. Data were collected through an electronic survey sent by email with multiple name generators and a structured face-to-face interview utilizing a network visualization tool, VennMaker. Two distinct methods, namely qualitative case studies and cluster analysis were used to characterize mobility types. Findings reveal a heterogeneous foreign population, in which different forms of mobility are reflected in the personal networks of mobile individuals. Respondents who were settled in the city were more likely to have networks in which social support was mainly derived by hosts and people in the host location and with whom they communicated predominantly through face-to-face communication. Those who were in the host location for a study exchange, knowing that return to the county of origin is imminent were more likely to have networks linked to the home location. They relied heavily on strong transnational ties in the home country using social media to sustain their relationship. Respondents with an itinerant mobility profile, also had networks dominated by strong transnational ties, however, such ties had a higher degree of geographical spread due to previous international mobility. Participants who had a high number of hosts in the network but low connection between the ties were more likely to be linked to a specific subculture in the host society. The integration in the host location follows a different pattern to other settled individuals, mainly because their connection in the city tends to be community specific.     

Echo chambers and social mediators in public advocacy issue networks

The growing trend of politically motivated consumer boycotts and buycotts on social media not only impacts a company’s financial bottom line, but more fundamentally disrupts relationships between the firm and its publics, the cornerstone of public relations (Ferguson, 1984; Sommerfeldt, & Kent, 2015). On a broader level, such politically motivated advocacy is a critical facet of civil society with important implications on the societal role of public relations (Taylor, 2010). In light of the significance of politically motivated consumer advocacy to public relations, a multi-phase, exploratory study was conducted. Study 1 applies content analysis and social network analysis to examine how different interactive mechanisms on social media—retweet, mention, and reply—may affect communication within and between communities of different ideological views surrounding the boycott and buycott issues. Study 2 further explores the challenges and opportunities of fostering exchange of diverse viewpoints by identifying new social mediators—the “echoers” who propel information flow among in-group members, and the “bridgers” who initiate communication with political out-group members—and assess the key network characteristics of these social mediators. The findings of these two studies advance public relations theories on networks, intergroup communication, and civil society by illustrating how social media structure and social mediators shape the networked public discourse to facilitate or inhibit conversations between publics of different ideological orientations.     

The contribution of the intervention in social networks and community social work at the local level to social and human development

ABSTRACT

The primary task of community social work is building social networks by reinforcing people's resources and those of the different environmental and social contexts from three dimensions: personal development, social development and organisational development. The new information technologies today establish a relationship of communication with local communities and citizens that promotes proximity to social networks. Social intervention is supported by a set of methods from human geography that can be used as tools to create maps of the territory and the networks for planning, diagnosing and classifying the management of community network intervention. In this discussion we set out to analyse the contribution of the intervention in social networks as a means of achieving a new configuration of social networks at the local level. This information is obtained from semi-structured interviews with social workers and other professionals in the social sphere in municipalities with over 100,000 inhabitants in the Madrid region (Spain). The research results show that intervention in social networks locally multiplies the opportunities to enhance the quality of people's social relationships, thus expanding their social support by strengthening their bonds, their personal network and support systems; secondly, it increases empowerment to facilitate a type of intervention to strengthen human potential and to gain autonomy and full citizenship.     

Time as a limited resource: Communication strategy in mobile phone networks

We used a large database of 9 billion calls from 20 million mobile users to examine the relationships between aggregated time spent on the phone, personal network size, tie strength and the way in which users distributed their limited time across their network (disparity). Compared to those with smaller networks, those with large networks did not devote proportionally more time to communication and had on average weaker ties (as measured by time spent communicating). Further, there were not substantially different levels of disparity between individuals, in that mobile users tend to distribute their time very unevenly across their network, with a large proportion of calls going to a small number of individuals. Together, these results suggest that there are time constraints which limit tie strength in large personal networks, and that even high levels of mobile communication do not fundamentally alter the disparity of time allocation across networks.     

Unless you go online you are on your own: blogging as a bridge in para-sport

Since its inception, the Web has been described as a liberating technology permitting individuals with disabilities to surmount barriers that otherwise prevent full societal engagement. Subsequent studies of Web-based communication have instead reported that disabling conditions are reproduced rather than challenged online. This paper uses interviews with 25 para-sport participants to provide an empirical account of how the affordances of the Web are leveraged in disability sport networks. Our findings suggest that individuals with disabilities are using blogs, Facebook, Twitter, and other forms of online communication to find information, engage in advocacy and outreach projects, and form strong networks that extend online and offline. We discuss our findings in light of Putnam’s conceptualization of bridging and bonding social capital, and describe how individuals and groups use weak ties to disseminate information and strong ties to foster a sense of belonging.     

Comparing Networks Across Space and Time, Size and Species

We describe and illustrate methodology for comparing networks from diverse settings. Our empirical base consists of 42 networks from four kinds of species (humans, nonhuman primates, nonprimate mammals, and birds) and covering distinct types of relations such as influence, grooming, and agonistic encounters. The general problem is to determine whether networks are similarly structured despite their surface differences. The methodology we propose is generally applicable to the characterization and comparison of network–level social structures across multiple settings, such as different organizations, communities, or social groups, and to the examination of sources of variability in network structure. We first fit a p^* model (Wasserman and Pattison 1996) to each network to obtain estimates for effects of six structural properties on the probability of the graph. We then calculate predicted tie probabilities for each network, using both its own parameter estimates and the estimates from every other network in the collection. Comparison is based on the similarity between sets of predicted tie probabilities. We then use correspondence analysis to represent the similarities among all 42 networks and interpret the resulting configuration using information about the species and relations involved. Results show that similarities among the networks are due more to the kind of relation than to the kind of animal.     

Dynamic social media affiliations among UK politicians

Inter-personal affiliations and coalitions are an important part of politicians’ behaviour, but are often difficult to observe. Since an increasing amount of political communication now occurs online, data from online interactions may offer a new toolkit to study ties between politicians; however, the methods by which robust insights can be derived from online data require further development, especially around the dynamics of political social networks. We develop a novel method for tracking the evolution of community structures, referred to as ‘multiplex community affiliation clustering’ (MCAC), and use it to study the online social networks of Members of Parliament (MPs) and Members of the European Parliament (MEPs) in the United Kingdom. Social interaction networks are derived from social media (Twitter) communication over an eventful 17-month period spanning the UK General Election in 2015 and the UK Referendum on membership of the European Union in 2016. We find that the social network structure linking MPs and MEPs evolves over time, with distinct communities forming and re-forming, driven by party affiliations and political events. Without including any information about time in our model, we nevertheless find that the evolving social network structure shows multiple persistent and recurring states of affiliation between politicians, which align with content states derived from topic analysis of tweet text. These findings show that the dominant state of partisan segregation can be challenged by major political events, ideology, and intra-party tension that transcend party affiliations.     

Réseaux épistémiques : formaliser la cognition distribuée

Knowledge-based communities bring together persons who collaborate and interact in order to produce knowledge. The tasks involved in this production are usually described in terms of “epistemic communities”: groups of individuals working on shared topics in pursuit of a common goal of knowledge production. Focus is thus placed on the formation, evolution and interactions of these communities – in general, on processes of collaboration. The objective is twofold: on one hand, describe how epistemic communities emerge and overlap at various hierarchical levels and, on the other, expose the determinants of collaboration between members of these communities. In an attempt to formalize the analysis of distributed cognition, an epistemic community is defined as the largest set of agents sharing and, working on, the same set of concepts. This formal definition helps us describe the distributed structure of knowledge production; understand the impact of this structure on the perception and arrangement of activities related to distributed cognition and appraise dynamically the stability over time of the distribution of tasks within the network, in spite of a continuous turnover among members. An empirical study of a community of embryologists illustrates this approach.     

Overlapping crime: Stability and specialization of co-offending relationships

Dyadic analyses of relationships between criminals have mostly ignored the multiplex nature of criminal ties. This study attempts to provide a more complete assessment of co-offending networks by incorporating the different types of crime that relate individuals with each other. Drawing on a large dataset of arrests in Quebec between 2003 and 2009, we focus on co-offending stability and specialization and illustrate how co-offending networks based on different types of criminal activities overlap. We portray a pattern of co-offending, which extends debate of criminal specialization/versatility to the dyadic level. Our study illustrates the ways in which the frequency and spectrum of crime include a relational component. More generally, the article emphasizes the need to consider the semantics of network ties, and further, the association between different types of networks, which ultimately offers a reassessment of social structure.     

Spousal Network Overlap as a Basis for Spousal Support

The role social network structure plays in facilitating flows of support between spouses is often overlooked. This study examined whether levels of support between spouses depended on the degree of overlap between spouses' networks. Network overlap may enhance spouses' support capacities by increasing their understanding of each other's support needs and their ability to coordinate support for each other. Data on 1,490 married older adults from the National Social Life, Health, and Aging Project were examined. Analyses revealed that when one's spouse had more contact with one's other network members, one was more likely to (a) view the spouse as a reliable source of support, (b) open up to the spouse, and (c) discuss health issues with the spouse. These results suggest that spousal support is not only a function of relationship quality or obligations-it also is a structural phenomenon that depends on spouses' connectedness to each other's networks.     

The Networked Household

The authors argue that individuals, rather than family solidarities, have become the primary unit of household connectivity. Many households do not operate as traditional densely knit groups but as more sparsely knit social networks where individuals juggle their somewhat separate agendas and schedules. At a time when many people enact multiple, individual roles at home, in the community and at work, the authors ask: how do adult household members communicate with each other? How do adult household members use information and communication technologies (ICTs) to organize, communicate and coordinate their leisure and social behavior both inside and outside the home? Interviews and surveys conducted in 2004-2005 in the Toronto, Canada area of East York show that households remain connected - but as networks rather than solidary groups. The authors describe how networked individuals bridge their relationships and connect with each other inside and outside the home. ICTs have afforded household members the ability to go about on their separate ways while staying more connected - by mobile phone, email and IM - as well as by traditional landlines. In such ways, rather than pulling families apart, ICTs often facilitate communication, kinship and functional integration.     

Who benefits from network intervention programs? TERGM analysis across ten Philippine low-income communities

Building social capital and strengthening social networks among members of low-income communities has been recommended as a potential pathway out of poverty. However, it is not clear how network-strengthening interventions and community-based programs interact with pre-existing networks and power structures. We examine the impact of one such intervention in ten low income communities in the Philippines. The intervention is a standardized program of a faith-based organization implemented in thousands of communities in multiple countries. It brings together low-income individuals in each community for 16 weekly sessions about health, income generation, and Christian values. An important but yet unmeasured goal of the intervention is the strengthening of social networks among the participants. We measured the social networks before and after the intervention and analysed their changes both separately and jointly for all ten communities with temporal exponential random graph models (TERGM). We modelled the post-intervention network structures conditioning on the pre-intervention networks, pre-intervention node attributes, and attribute changes through the intervention. We found social engagement (measured by social visits to others) to moderate most consistently the effects of the intervention across the ten communities. Those who were more socially engaged consistently strengthened their networks through the intervention. By contrast, some network mechanisms strongly diverged between the communities. In particular, religiosity was positively associated with gaining social links through this faith-based intervention in some communities and negatively in others. Similar communities may in some aspects react to the same intervention in opposite ways—a phenomenon that should be further explored through studies of larger numbers of comparable networks.     

Neighborhoods in the Network Society the e-Neighbors study

This study examines whether the Internet is increasingly a part of everyday neighborhood interactions, and in what specific contexts Internet use affords the formation of local social ties. Studies of Internet and community have found that information and communication technologies provide new opportunities for social interaction, but that they may also increase privatism by isolating people in their homes. This paper argues that while the Internet may encourage communication across great distances, it may also facilitate interactions near the home. Unlike traditional community networking studies, which focus on bridging the digital divide, this study focuses on bridging the divide between the electronic and parochial realms. Detailed, longitudinal social network surveys were completed with the residents of four contrasting neighborhoods over a period of three years. Three of the four neighborhoods were provided with a neighborhood email discussion list and a neighborhood website. Hierarchical linear modeling (HLM) was used to model over time the number of strong and weak ties, emailed, met in-person, and talked to on the telephone. The neighborhood email lists were also analyzed for content. The results suggest that with experience using the Internet, the size of local social networks and email communication with local networks increases. The addition of a neighborhood email list further increases the number of weak neighborhood ties, but does not increase communication multiplexity. However, neighborhood effects reduce the influence of everyday Internet use, as well as the experimental intervention, in communities that lack the context to support local tie formation.     

Informal lending networks in rural Ethiopia

Economic development in emergent nations is tied to smallholder subsistence populations whose livelihoods are vulnerable to exogenous shocks. When shocks occur, individuals often rely on resources embedded within informal insurance networks. Resource access is related to network position and reflected in properties such as centrality and reachability. We analyze a complete informal lending network (188 nodes, 295 ties) among the Sidama, an agro-pastoralist population in southwestern Ethiopia. Results indicate that culturally salient indicators of wealth, such as cattle ownership and gender, largely account for network structure. Analysis of a complete network further allows us to discuss the impact of global network properties, such as overall typology, on a communities response to different types of shocks (covariate and idiosyncratic). These findings extend our understanding of how individuals and communities engage informal lending networks in response to exogenous shocks.     

A comparison of email networks and off-line social networks: A study of a medium-sized bank

Recently there has been a surge in the availability of online data concerning the connections between people, and these online data are now widely used to map the social structure of communities. There has been little research, however, on how these new types of relational data correspond to classical measures of social networks. To fill this gap, we contrast the structure of an email network with the underlying friendship, communication, and advice seeking networks. Our study is an explorative case study of a bank, and our data contains emails among employees and a survey of the ego networks of the employees. Through calculating correlations with QAP standard errors and estimating exponential random graph (ERG) models, we find that although the email network is related to the survey-based social networks, email networks are also significantly different: while off-line social networks are strongly shaped by gender, tenure, and hierarchical boundaries, the role of these boundaries are much weaker in the email network.