Community Structure Characterization

This entry discusses the problem of describing some communities identified in a complex network of interest, in a way allowing to interpret them. We suppose the community structure has already been detected through one of the many methods proposed in the literature. The question is then to know how to extract valuable information from this first result, in order to allow human interpretation. This requires subsequent processing, which we describe in the rest of this entry

Business-oriented Analysis of a Social Network of University Students

Despites the great interest caused by social networks in Business Science, their analysis is rarely performed both in a global and systematic way in this field: most authors focus on parts of the studied network, or on a few nodes considered individually. This could be explained by the fact that practical extraction of social networks is a difficult and costly task, since the specific relational data it requires are often difficult to access and thereby expensive. One may ask if equivalent information could be extracted from less expensive individual data, i.e. data concerning single individuals instead of several ones. In this work, we try to tackle this problem through group detection. We gather both types of data from a population of students, and estimate groups separately using individual and relational data, leading to sets of clusters and communities, respectively. We found out there is no strong overlapping between them, meaning both types of data do not convey the same information in this specific context, and can therefore be considered as complementary. However, a link, even if weak, exists and appears when we identify the most discriminant attributes relatively to the communities. Implications in Business Science include community prediction using individual data.Social Networks; Business Science; Cluster Analysis; Community Detection; Community Comparison; Individual Data; Relational Data

Community Currencies (CCs) in Spain: An empirical study of their social effects

Despite its sudden proliferation along the economic crisis period, no previous study has investigated the social effects of the community currency (CCs) experiences in Spain. Previous research on CCs experiences from different countries provided evidences about social capital improvement, introducing CCs as sustainability tools. This research uses the theoretical frameworks of social capital and complex adaptive systems to approach concepts like sustainability, networks, trust, norms, participation and cooperation. Statistical analysis of the data collected in June 2013 through online survey explores social capital and resilience indicators among the Spanish exchange community users, concluding that Spanish CCs systems improve community social capital through the proposed dimensions, although they are in an early stage and several weakness need to be corrected. The values, motivations, attitude and positive perception of their members suggest that CCs could be appropriate tools for sustainability due its potential to improve social capital and resilience. Detected weakness may affect the interests and commitment of their members. Therefore experience from senior currency systems may help them to face adversities and fully develop their potential for sustainability.Despite its sudden proliferation along the economic crisis period, no previous study has investigated the social effects of the community currency (CCs) experiences in Spain. Previous research on CCs experiences from different countries provided evidences about social capital improvement, introducing CCs as sustainability tools. This research uses the theoretical frameworks of social capital and complex adaptive systems to approach concepts like sustainability, networks, trust, norms, participation and cooperation. Statistical analysis of the data collected in June 2013 through online survey explores social capital and resilience indicators among the Spanish exchange community users, concluding that Spanish CCs systems improve community social capital through the proposed dimensions, although they are in an early stage and several weakness need to be corrected. The values, motivations, attitude and positive perception of their members suggest that CCs could be appropriate tools for sustainability due its potential to improve social capital and resilience. Detected weakness may affect the interests and commitment of their members. Therefore experience from senior currency systems may help them to face adversities and fully develop their potential for sustainability

Wearable Bluetooth Sensors for Capturing Relational Variables and Temporal Variability in Relationships: A Construct Validation Study

The advent of wearable sensor technologies has the potential to transform organizational research by offering the unprecedented opportunity to collect continuous, objective, highly granular data over extended time periods. Recent evidence has demonstrated the potential utility of Bluetooth-enabled sensors, specifically, in identifying emergent networks via colocation signals in highly controlled contexts with known distances and groups. Although there is proof of concept that wearable Bluetooth sensors may be able to contribute to organizational research in highly controlled contexts, to date there has been no explicit psychometric construct validation effort dedicated to these sensors in field settings. Thus, the two studies described here represent the first attempt to formally evaluate longitudinalBluetooth data streams generated in field settings, testing their ability to (a) show convergent validity with respect to traditional self-reports of relational data; (b) display discriminant validitywith respect to qualitative differences in the nature of alternative relationships (i.e., advice vs. friendship); (c) document predictive validity with respect to performance; (d) decompose variance in network-related measures into meaningful within- and between-unit variability over time; and (e) complement retrospective self-reports of time spent with different groups where there is a “ground truth” criterion. Our results provide insights into the validity of Bluetooth signals with respect to capturing variables traditionally studied in organizational science and highlight how the continuous data collection capabilities made possible by wearable sensors can advance research far beyond that of the static perspectives imposed by traditional data collection strategies