Inferring Social Status and Rich Club Effects in Enterprise Communication Networks

Social status, defined as the relative rank or position that an individual holds in a social hierarchy, is known to be among the most important motivating forces in social behaviors. In this paper, we consider the notion of status from the perspective of a position or title held by a person in an enterprise. We study the intersection of social status and social networks in an enterprise. We study whether enterprise communication logs can help reveal how social interactions and individual status manifest themselves in social networks. To that end, we use two enterprise datasets with three communication channels --- voice call, short message, and email --- to demonstrate the social-behavioral differences among individuals with different status. We have several interesting findings and based on these findings we also develop a model to predict social status. On the individual level, high-status individuals are more likely to be spanned as structural holes by linking to people in parts of the enterprise networks that are otherwise not well connected to one another. On the community level, the principle of homophily, social balance and clique theory generally indicate a "rich club" maintained by high-status individuals, in the sense that this community is much more connected, balanced and dense. Our model can predict social status of individuals with 93% accuracy.Comment: 13 pages, 4 figure

More for less : on consumer rationality and bargaining power on telecommunication markets

We analyse the large scale agent-based model of a prepaid telecommunication market with oligopolistic competition, heterogeneous calling patterns and different levels of agent rationality. We apply innovative implementation approach of utilizing high performance CUDA computing devices which allows us to consider population of up to 1 million consumers. We measure influence of a call graph structure, intra-family network choice coordination and agent rationality level on the market equilibrium. We discover that boundedly rational subscribers, who exploit simple decision heuristics to coordinate network choice within closed user groups, exert much stronger pressure on suppliers than fully rational ones. This leads to lower average calling costs, increased welfare and decreased monopolistic power of operators. We also observe asymmetry in operator margins and volume of on-net and off-net calls in accordance with empirical facts

Investigating the influence of network effects on disruptive technologies in social networks

The main purpose of this doctoral thesis is to investigate the probability of technological disruption when network effects are present. It also investigates how consumer network structures, the social networks connecting consumers to each other, influence the potential for such disruption. The manner in which consumer network structures influence such technological disruption forms the subject of this investigation. The model and simulated influence of network effects assumes the inter-connectedness of all consumers within the population and the existence of a complete network. This assumption is tempered by consideration of the different ways in which consumers connect to each other within social networks, i.e. regular, lattice, small-world, and random networks characterized by clustering and path length properties. Even within the case of strong network effects, a consumer network characterized by high clustering and long path length provides favorable conditions for new potentially disruptive technology to survive in niche groups. Regular and small-world networks with few shortcuts fall within this category, whereas random networks that exhibit low clustering and short path-length properties favor established technology. Even under the favorable conditions of consumer network structures, a firm introduces a new, potentially disruptive technology requiring the creation of a critical mass if it is to enter the mainstream sector. The empirical section of this doctoral thesis identifies determinants of technology acceptance characterized by disruptiveness and network effects. The Theory of Planned Behavior and the Technology Acceptance Model provide a basis for the proposed model. An online survey was administered, while crowdsourcing together with social media were utilized to collect primary data on German and Indonesian users acceptance of technologies or applications in long-distance calls. The expected current and future number of users, representative of the technologys installed base, were found to be positively and significantly (albeit indirectly) related to their intention to use the technology. Perceptions of affordability and ease of use were also positively and significantly related to the attitude toward using which subsequently had an important relationship with an individuals intention to employ the technology

Monitoring extensions for component-based distributed software

This paper defines a generic class of monitoring extensions to component-based distributed enterprise software. Introducing a monitoring extension to a legacy application system can be very costly. In this paper, we identify the minimum support for application monitoring within the generic components of a distributed system, necessary for rapid development of new monitoring extensions. Furthermore, this paper offers an approach for design and implementation of monitoring extensions at reduced cost. A framework of basic facilities supporting the monitoring extensions is presented. These facilities handle different aspects critical to the monitoring process, such as ordering of the generated monitoring events, decoupling of the application components from the components of the monitoring extensions, delivery of the monitoring events to multiple consumers, etc.\ud The work presented in this paper is being validated in the prototype of a large distributed system, where a specific monitoring extension is built as a tool for debugging and testing the application behaviour.\u