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.     

Centrality and network flow

Centrality measures, or at least popular interpretations of these measures, make implicit assumptions about the manner in which traffic flows through a network. For example, some measures count only geodesic paths, apparently assuming that whatever flows through the network only moves along the shortest possible paths. This paper lays out a typology of network flows based on two dimensions of variation, namely the kinds of trajectories that traffic may follow (geodesics, paths, trails, or walks) and the method of spread (broadcast, serial replication, or transfer). Measures of centrality are then matched to the kinds of flows that they are appropriate for. Simulations are used to examine the relationship between type of flow and the differential importance of nodes with respect to key measurements such as speed of reception of traffic and frequency of receiving traffic. It is shown that the off-the-shelf formulas for centrality measures are fully applicable only for the specific flow processes they are designed for, and that when they are applied to other flow processes they get the “wrong” answer. It is noted that the most commonly used centrality measures are not appropriate for most of the flows we are routinely interested in. A key claim made in this paper is that centrality measures can be regarded as generating expected values for certain kinds of node outcomes (such as speed and frequency of reception) given implicit models of how traffic flows, and that this provides a new and useful way of thinking about centrality.     

Bridging,brokerage and betweenness

Valente and Fujimoto (2010) proposed a measure of brokerage in networks based on Granovetter's classic work on the strength of weak ties. Their paper identified the need for finding node-based measures of brokerage that consider the entire network structure, not just a node's local environment. The measures they propose, aggregating the average change in cohesion for a node's links, has several limitations. In this paper we review their method and show how the idea can be modified by using betweenness centrality as an underpinning concept. We explore the properties of the new method and provide point, normalized, and network level variations. This new approach has two advantages, first it provides a more robust means to normalize the measure to control for network size, and second, the modified measure is computationally less demanding making it applicable to larger networks.     

Disliking friends of friends in schools: How positive and negative ties can co-occur in large numbers

Current network scholarship does not explain why negative and positive ties both frequently occur in large numbers in some settings, such as schools. In the present paper, I argue that this can happen when people disproportionately send negative ties to socially close individuals (‘friends of friends’). I propose a new theory—‘intensity theory’—which argues that disliking ties disproportionately occur between friends of friends in ‘intense foci’. Intense foci are settings that concentrate social relations, and in which other people are difficult to avoid. I draw on a mixed-methods case study of a boarding school and several strands of literature to substantiate the theory. In so doing, I offer a new mechanism for the initial appearance of disliking ties, propose a contextual approach to balance theory and networks in general, and suggest a more complex view of the link between positive and negative ties.     

Partitioning signed social networks

Structural balance theory has proven useful for delineating the blockmodel structure of signed social networks. Even so, most of the observed signed networks are not perfectly balanced. One possibility for this is that in examining the dynamics underlying the generation of signed social networks, insufficient attention has been given to other processes and features of signed networks. These include: actors who have positive ties to pairs of actors linked by a negative relation or who belong to two mutually hostile subgroups; some actors that are viewed positively across the network despite the presence of negative ties and subsets of actors with negative ties towards each other. We suggest that instead viewing these situations as violations of structural balance, they can be seen as belonging to other relevant processes we call mediation, differential popularity and internal subgroup hostility. Formalizing these ideas leads to the relaxed structural balance blockmodel as a proper generalization of structural balance blockmodels. Some formal properties concerning the relation between these two models are presented along with the properties of the fitting method proposed for the new blockmodel type. The new method is applied to four empirical data sets where improved fits with more nuanced interpretations are obtained.     

Prismatic effects of negative ties

Research on negative ties has focused primarily on the harm they do. In this paper, we show that negative ties can also have beneficial effects. We argue that, like positive ties, negative ties can link actors together in the minds of observers. As a result, we theorize that negative ties with high-status actors can benefit a focal actor, whereas negative ties with low-status actors can harm the focal actor. This prismatic effect depends on the existing status of the focal actor: a focal actor of low status is likely to benefit far more from negative ties with high-status actors and suffer more from negative ties with low-status actors than will an actor of high-status. To test our ideas, we analyze the phenomenon of "diss songs" in hip-hop music. A diss song is a song in which a rapper makes derogatory comments about another rapper, constituting a negative tie. We analyze the effects of negative ties among 53 rappers over 20 points in time on audience reaction as measured by record sales. We find that negative ties with high-status actors enhance future sales for low-status actors. However, negative ties with lower-status actors have no effect on the future sales of both low- and high-status actors. Just as some researchers have reported both positive and negative consequences of social capital, our study demonstrates that negative ties can also have both positive and negative outcomes.     

Embedding time in positions: Temporal measures of centrality for social network analysis

Digital data enable researchers to obtain fine-grained temporal information about social interactions. However, positional measures used in social network analysis (e.g., degree centrality, reachability, betweenness) are not well suited to these time-stamped interaction data because they ignore sequence and time of interactions. While new temporal measures have been developed, they consider time and sequence separately. Building on formal algebra, we propose three temporal equivalents to positional network measures that incorporate time and sequence. We demonstrate how these temporal equivalents can be applied to an empirical context and compare the results with their static counterparts. We show that, compared to their temporal counterparts, static measures applied to interaction networks obscure meaningful differences in the way in which individuals accumulate alters over time, conceal potential disconnections in the network by overestimating reachability, and bias the distribution of betweenness centrality, which can affect the identification of key individuals in the network.     

Network centrality and social movement media coverage: A two-mode network analytic approach

This article examines the relationship between structural location (namely, degree centrality) and news media coverage. Our central hypothesis is that the network centrality of social movement actors is positively associated with the prevalence of actors being cited in the print news media. This paper uses two-mode data from a communication network of environmentalists in British Columbia, and examines the relationship between their structural location and the frequency by which they are cited in newsprint media with regard to particular frames (about forest conservation, environmental protest, and related issues). We asked a sample of social movement participants about their ties to a target list of relatively high profile actors (environmental activists). We turned the resulting network matrix into a bipartite graph that examined the relationships amongst the target actors vis a vis the respondents. Next we calculated point in-degree for the target actors. For the target actors we also have data from a representative sample of 957 print news articles about forestry and conservation of old growth forests in British Columbia. We compare the effects of network centrality of the target actor versus several attributes of the target actors (gender, level of radicalism, leadership status) on the amount of media coverage that each of the target actors receives. We find that network centrality is associated with media coverage controlling for actor attributes. We discuss theoretical implications of this research. Finally, we also discuss the methodological pros and cons of using a “target name roster” to construct two-mode data on social movement activists.     

How stable is the core discussion network?

Researchers have paid increasing attention to the core discussion network, the set of people we turn to when discussing important matters. Because the core discussion network is theorized to be composed of people's closest ties, not fleeting acquaintances, it is expected to be largely stable, evolving slowly over the span of people's lives. However, recent studies have shown that networks are strongly affected by the contexts in which people interact with others, and as people experience life course transitions, they also often enter new contexts – school, college, work, marriage, and retirement. We ask whether, as actors enter new social contexts, the core discussion network remains stable or changes rapidly. Based on original, longitudinal, qualitative and quantitative data on the experience of first-year graduate students in three academic departments in a large university, we examine the stability of the core discussion network over the first 6 and 12 months in this new context. We test four competing hypotheses that focus on strength of ties, new opportunities, obligations, and routine activity and predict, respectively, stasis, expansion, shedding, and substitution. We find that the core discussion network changes remarkably quickly, with little or no lag, and that it appears to do so because both the obligations that people face and the routine activities they engage in are transformed by new institutional environments. Findings suggest that core discussion network may be less a “core” network than a highly contextual support network in which people are added and dropped as actors shift from environment to environment.     

Assessing the performance of the bootstrap in simulated assemblage networks

Archaeologists are increasingly interested in networks constructed from site assemblage data, in which weighted network ties reflect sites’ assemblage similarity. Equivalent networks would arise in other scientific fields where actors’ similarity is assessed by comparing distributions of observed counts, so the assemblages studied here can represent other kinds of distributions in other domains. One concern with such work is that sampling variability in the assemblage network and, in turn, sampling variability in measures calculated from the network must be recognized in any comprehensive analysis. In this study, we investigated the use of the bootstrap as a means of estimating sampling variability in measures of assemblage networks. We evaluated the performance of the bootstrap in simulated assemblage networks, using a probability structure based on the actual distribution of sherds of ceramic wares in a region with 25 archaeological sites. Results indicated that the bootstrap was successful in estimating the true sampling variability of eigenvector centrality for the 25 sites. This held both for centrality scores and for centrality ranks, as well as the ratio of first to second eigenvalues of the network (similarity) matrix. Findings encourage the use of the bootstrap as a tool in analyses of network data derived from counts.     

A network centrality bias: Central individuals in workplace networks have more supportive coworkers

Combining the results of two empirical studies, we investigate the role of alters’ motivation in explaining change in ego’s network position over time. People high in communal motives, who are prone to supportive and altruistic behavior in their interactions with others as a way to gain social acceptance, prefer to establish ties with co-workers occupying central positions in organizational social networks. This effect results in a systematic network centrality bias: The personal network of central individuals (individuals with many incoming ties from colleagues) is more likely to contain more supportive and altruistic people than the personal network of individuals who are less central (individuals with fewer incoming ties). This result opens the door to the possibility that the effects of centrality so frequently documented in empirical studies may be due, at least in part, to characteristics of the alters in an ego’s personal community, rather than to egos themselves. Our findings invite further empirical research on how alters’ motives affect the returns that people can reap from their personal networks in organizations.     

Correlations among centrality indices and a class of uniquely ranked graphs

Various centrality indices have been proposed to capture different aspects of structural importance but relations among them are largely unexplained. The most common strategy appears to be the pairwise comparison of centrality indices via correlation. While correlation between centralities is often read as an inherent property of the indices, we argue that it is confounded by network structure in a systematic way. In fact, correlations may be even more indicative of network structure than of relationships between indices. This has substantial implications for the interpretation of centrality effects as it implies that competing explanations embodied in different indices cannot be separated from each other if the network structure is close to a certain generalization of star graphs.     

Keep around,drop, or revise? exploring what becomes of difficult ties in personal networks

Previous studies increasingly recognize the presence and impact of difficult individuals within personal networks. However, current research sheds little light on the turnover, retention, and change in quality of such difficult ties. The current study addresses this gap by focusing on two distinct forms of network change. We examine how role relationships, support exchange, relational homophily, and personal characteristics are associated with these processes. Data are drawn from three waves of the University of California Social Network Study (UCNets), a project containing comprehensive longitudinal data on ego networks among two adult cohorts. Findings indicate that over time, 34% of difficult ties re-appear in people’s networks as sources of aggravation; 26% of difficult ties are removed from the network; and 40% can no longer be verified as problematic network members. Most ties no longer deemed difficult are identified as providing one or more supportive functions. Multinomial multilevel models reveal that exchanging support tends to anchor difficult ties in the network. Kinship, meanwhile, plays a large role in whether difficult ties remain or get dropped. Personal characteristics such as gender, income, and relocation also play a role in these processes. Overall, we conclude that the turnover dynamics of difficult ties are similar to other ties, and the apparent change from negative to positive suggests that many ties hold ambivalent properties that make shedding such ties less common than may be expected.     

Change in Covert Social Movement Networks: The ‘Inner Circle’ of the Provisional Irish Republican Army

In this paper, we contribute to both the growing body of literature on social movement networks and the growing body of literature on change in networks by exploring patterns and mechanisms of change within the network of the ‘inner circle’ of the Provisional Irish Republican Army. Specifically, we focus upon the period between 1969 (when it formed) and 1988 (the last point for which we have been able to gather good data). Our primary aims are substantive. We want to know how this network changed over time. In addition, however, our analysis identifies changes which other analysts might look for in their networks and offers methodological suggestions for those who, like us, find that their networks do not meet the assumptions of mainstream approaches to modelling network dynamics. There is a further dimension to the paper, however. We are studying a covert social movement network. This is a special type of movement network whose organisation and dynamics are predicted to vary from other movement networks. Some have suggested that they are inclined to be relatively static because the need for trust within them is so great and the risk to whatever they hold secret so considerable when new ties are formed that their members tend only to recruit within the pool of their pre-existing ties and actively seek to minimise recruitment and the formation of new ties. One of the aims of our paper was to determine whether and to what extent this is so.     

Node centrality in weighted networks: Generalizing degree and shortest paths

Ties often have a strength naturally associated with them that differentiate them from each other. Tie strength has been operationalized as weights. A few network measures have been proposed for weighted networks, including three common measures of node centrality: degree, closeness, and betweenness. However, these generalizations have solely focused on tie weights, and not on the number of ties, which was the central component of the original measures. This paper proposes generalizations that combine both these aspects. We illustrate the benefits of this approach by applying one of them to Freeman’s EIES dataset.     

Positive and negative tie perceptual accuracy: Pollyanna principle vs. negative asymmetry explanations

We examine the affective content of ties and explore whether negative affective tie content is systematically advantaged or disadvantaged when recalling the social network as compared to positive affective tie content. We test this in three workgroups from two organizations and analyze differences in perceptual accuracy comparing negative and positive affective tie perception. We theorize that ego will be more accurate for others’ positive than negative ties due to generalized positivity bias, or the Pollyanna principle. We also theorize that ego will be more accurate for their own negative ties due to negative asymmetry perspective, as ego will attend more to those ties that pose a personal threat. Findings suggest that observers were more accurate overall about their own and others’ positive compared to negative affective ties. We conclude that the Pollyanna principle is an important factor in explaining perceptions in naturalistic cognitive networks. Supplementary analysis showed that negative ties were more likely to be missed and imagined and having a valenced tie toward another person influences perceptions of that persons’ network ties. Finally, we find that balanced and imbalanced triads were also important factors of relative accuracy. The study’s contribution, limitations, and future research are also discussed.     

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.     

Children and the Modern Farming Movement

In the twenty‐first century, a small percentage of U.S. children have ties to family‐based agriculture. Yet with the rise of the modern farming movement that emphasizes local and family‐based production, new spaces may exist for involving children and youth in farming. This article focuses on the social value of children to family‐based agriculture in the contemporary era. Drawing on a qualitative study of families that farm in the capital region of New York—an epicenter for the modern food movement—we consider why families farm, how they involve children in their farms, and how they understand children's contributions. Interviews with 76 adult members of 50 families show children to be central to families' goals; they often rationalize farming as a lifestyle choice undertaken for the benefit of their children. Families also actively involve their own children—and other people's children—in their farms. By documenting the way families talk about children and farming, we shed light on the logic used to incorporate children into modern productive enterprises. The centrality of children, we argue, helps explain the success of the modern food movement and the persistence of family‐based agriculture despite conditions that make it economically difficult to accomplish.     

You are who remembers you. Detecting leadership through accuracy of recall

We measured interpersonal perception accuracy by focusing on the relationship between actors’ centrality and their ability to accurately report their social interactions. We used the network measures of actors’ betweenness centrality and degree centrality to identify the most prominent members by correlating ego-perception and alter-perception in a “non-reciprocity” type of misalignment. We found a positive correlation between actors’ centrality and their centrality as assessed by senior management, and a negative correlation between actors’ centrality and their accuracy in recalling interactions. Underreporting social interactions may represent a third way of measuring the importance of members and finding the most influential actors.