Non-Conservative Diffusion and its Application to Social Network Analysis

The random walk is fundamental to modeling dynamic processes on networks. Metrics based on the random walk have been used in many applications from image processing to Web page ranking. However, how appropriate are random walks to modeling and analyzing social networks? We argue that unlike a random walk, which conserves the quantity diffusing on a network, many interesting social phenomena, such as the spread of information or disease on a social network, are fundamentally non-conservative. When an individual infects her neighbor with a virus, the total amount of infection increases. We classify diffusion processes as conservative and non-conservative and show how these differences impact the choice of metrics used for network analysis, as well as our understanding of network structure and behavior. We show that Alpha-Centrality, which mathematically describes non-conservative diffusion, leads to new insights into the behavior of spreading processes on networks. We give a scalable approximate algorithm for computing the Alpha-Centrality in a massive graph. We validate our approach on real-world online social networks of Digg. We show that a non-conservative metric, such as Alpha-Centrality, produces better agreement with empirical measure of influence than conservative metrics, such as PageRank. We hope that our investigation will inspire further exploration into the realms of conservative and non-conservative metrics in social network analysis

Studying Diffusion of Viral Content at Dyadic Level

Diffusion of information and viral content, social contagion and influence are still topics of broad evaluation. As theory explaining the role of influentials moves slightly to reduce their importance in the propagation of viral content, authors of the following paper have studied the information epidemic in a social networking platform in order to confirm recent theoretical findings in this area. While most of related experiments focus on the level of individuals, the elementary entities of the following analysis are dyads. The authors study behavioral motifs that are possible to observe at the dyadic level. The study shows significant differences between dyads that are more vs less engaged in the diffusion process. Dyads that fuel the diffusion proccess are characterized by stronger relationships (higher activity, more common friends), more active and networked receiving party (higher centrality measures), and higher authority centrality of person sending a viral message.Comment: ASONAM 2012, The 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining. IEEE Computer Society, pp. 1291-129

Topology comparison of Twitter diffusion networks effectively reveals misleading information

In recent years, malicious information had an explosive growth in social media, with serious social and political backlashes. Recent important studies, featuring large-scale analyses, have produced deeper knowledge about this phenomenon, showing that misleading information spreads faster, deeper and more broadly than factual information on social media, where echo chambers, algorithmic and human biases play an important role in diffusion networks. Following these directions, we explore the possibility of classifying news articles circulating on social media based exclusively on a topological analysis of their diffusion networks. To this aim we collected a large dataset of diffusion networks on Twitter pertaining to news articles published on two distinct classes of sources, namely outlets that convey mainstream, reliable and objective information and those that fabricate and disseminate various kinds of misleading articles, including false news intended to harm, satire intended to make people laugh, click-bait news that may be entirely factual or rumors that are unproven. We carried out an extensive comparison of these networks using several alignment-free approaches including basic network properties, centrality measures distributions, and network distances. We accordingly evaluated to what extent these techniques allow to discriminate between the networks associated to the aforementioned news domains. Our results highlight that the communities of users spreading mainstream news, compared to those sharing misleading news, tend to shape diffusion networks with subtle yet systematic differences which might be effectively employed to identify misleading and harmful information.Comment: A revised new version is available on Scientific Report

Public Research in Regional Networks of Innovators: A Comparative Study of Four East-German Regions

Universities and public research organizations are said to be an integrative and essential element of a functioning innovation system as they play a vital role not only in the generation of new technological knowledge, but also in its diffusion. We analyse four East German local networks of innovators which differ in structure and innovative performance and investigate the characteristic role of public research within these local systems by applying methods of social network analysis. Our results show that universities and non-university institutions of public research are key actors in all regional networks of innovators both in terms of patent output and in terms of centrality of their position in the networks. Further we find the 'thicker' networks to have more central public research organizations. Higher centrality of public research compared to private actors may be due to the fact that universities are explicitly designed to give away their knowledge and that they increasingly face the need to raise external funds.Innovator Networks; Public research; R+D Cooperation; Mobility

Trust networks and innovation dynamics of small farmers in Colombia: An approach from territorial system of agricultural innovation

This study addresses the concepts of territorial systems of agricultural innovation and social network analysis. The general purpose of this research was analyzing a relationship between trust networks (technical, strategic and normative) and the dynamics of technological diffusion and adoption by Hass avocado farmers in each territory. To this end, two rural municipalities were compared as case studies; where 94 farmers were interviewed. A database was obtained and analyzed using a social network approach by calculating network indicators, as well as the technology adoption index (TAI) for farmers. Correlation tests were also used to determine the effect of the farmers' trust networks on their own technology diffusion-adoption dynamics. Case studies showed that there are no significant differences in terms of technology adoption when comparing municipalities. However, the farmers' diffusion networks show different public-private actors, as well as different degrees of input centrality and intermediation in each municipality, where correlation was found only with normative trust networks in a municipality. The capture of specific information from a geographical space is steered by the approach of territorial systems of agricultural innovation, allowing for the development of increasingly accurate strategies and interventions. Highlights This study empirically demonstrated how both technology adoption by farmers and diffusion networks have different trends across geographical spaces. The capture of specific information from a geographical space is steered by the approach of territorial systems of agricultural innovation, allowing for the development of increasingly accurate strategies and interventions. Diffusion networks of farmers from each rural municipality were built upon different actors, several of which were different and had different input centrality indicators. These actors are quite important as they are cited as intermediation indicators and sources of learning, which means they are fundamental actors in promoting greater diffusion in each territory. Trust networks (technical, strategic and normative) were found to have a different influence in each rural municipality in relation to farmers' diffusion networks and the technology adoption index.This study addresses the concepts of territorial systems of agricultural innovation and social network analysis. The general purpose of this research was analyzing a relationship between trust networks (technical, strategic and normative) and the dynamics of technological diffusion and adoption by Hass avocado farmers in each territory. To this end, two rural municipalities were compared as case studies; where 94 farmers were interviewed. A database was obtained and analyzed using a social network approach by calculating network indicators, as well as the technology adoption index (TAI) for farmers. Correlation tests were also used to determine the effect of the farmers' trust networks on their own technology diffusion-adoption dynamics. Case studies showed that there are no significant differences in terms of technology adoption when comparing municipalities. However, the farmers' diffusion networks show different public-private actors, as well as different degrees of input centrality and intermediation in each municipality, where correlation was found only with normative trust networks in a municipality. The capture of specific information from a geographical space is steered by the approach of territorial systems of agricultural innovation, allowing for the development of increasingly accurate strategies and interventions. Highlights This study empirically demonstrated how both technology adoption by farmers and diffusion networks have different trends across geographical spaces. The capture of specific information from a geographical space is steered by the approach of territorial systems of agricultural innovation, allowing for the development of increasingly accurate strategies and interventions. Diffusion networks of farmers from each rural municipality were built upon different actors, several of which were different and had different input centrality indicators. These actors are quite important as they are cited as intermediation indicators and sources of learning, which means they are fundamental actors in promoting greater diffusion in each territory. Trust networks (technical, strategic and normative) were found to have a different influence in each rural municipality in relation to farmers' diffusion networks and the technology adoption index