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

Application of network analysis in evaluating organizational structure and determining its future shape

The article presents the result of an empirical study that compares the formal structure of a company with its less formal counterpart: the network of cooperation, flow of information, knowledge and decision between employees. An empirical study surveys 374 employees from two companies about their position in formal structure and their connections with other employees. The conducted analysis examines the relationship between company structural characteristics and performance, as one of studied company performs less effective than other. The paper examines such issues as: the level of convergence of both structures, the degree of compliance of formal and informal authority and the allocation of network resources. In a company characterized by higher performance we observed higher level of convergence of both structures, higher degree of compliance of the position of the employee with the level of their informal authority, and higher level of support provided by the managers. Results suggest that the comparison of formal and informal structure of the company provides information about its performance that is difficult to obtain in any other way. Finally, presented managerial implications refer to the specific ways how to improve the organizational structure on the basis of information obtained by analyzing the organizational network

The application of social network analysis for the studies on organizational structure

Using social network analysis for the studies of organizational structure allows to understand in more details the ways of real organizing of employees. The manner in which people work is the quotidian knowledge that is often not realized very well but it is essential for effective performance of a company. The article presents the research process that results in a picture of organizational structure reflected as the network of connections between employees. The studies are usually conducted with survey questions that are presented in the article (cooperation, information flow, the flow of knowledge and problem-solving, and finally the decision flow) and interpreted in the context of the analysis made in a real company. The network structure of an innovative IT company (125 employees) consisting of 3097 connections has been visualized and analyzed. We tested the assumptions regarding the degree of company integration, the level of centralization in decision making process, the way of task coordination and the possible blockages in the flow of knowledge. We also highlighted employees that were important in these areas and specified their roles

Paul D. Trapnell and Jennifer D. Campbell’s Rumination-Reflection Questionnaire (RRQ) – polish adaptation of the measure

The article presents Polish adaptation of the Rumination-Reflection Questionnaire (RRQ) designed by Paul D. Trapnell and Jennifer D. Campbell. It starts with theoretical background that refers to the distinction between ruminative and reflective types of private self-consciousness and presents psychometric properties of the Polish version of RRQ. Obtained results (N = 798) are similar to the results of studies conducted on the original version of RRQ which shows that the adapted version of RRQ is reliable and theoretically valid instrument and can be used in scientific research

Jak wybrać agentów zmian w organizacji? Porównanie metod klasycznych i sieciowych

Dynamika rynku zmusza firmy do wprowadzania ciągłych zmian i dostosowywania się do potrzeb i wyzwań otoczenia. Proces ten może być prowadzony przy pomocy agentów zmian rozprzestrzeniających informacje i dostarczających wsparcie innym pracownikom. W artykule przedstawiamy podejście oparte na analizie sieci organizacyjnej. Proponujemy sposób wyboru pracowników do roli agentów zmiany pozwalający na optymalizowanie ich zasięgu w sieci, by przy jak najmniejszej liczbie wybranych osób maksymalizowany był ich łączny zasięg wyrażony liczbą pracowników, do których mogą bezpośrednio dotrzeć. W celach eksploracji i wstępnej weryfikacji zaproponowanego podejścia na trzech sieciach współpracy pracowników przedsiębiorstw średniej wielkości porównaliśmy kilka metod wyboru agentów. Wyniki sugerują, że agenci wybrani przy wykorzystaniu miary centralności sieciowej, jaką jest pośrednictwo (betweenness), uzyskują najlepszy i istotnie wyższy zasięg w sieci w porównaniu z agentami wybranymi na podstawie wysokiej pozycji w hierarchii. Także sam zasięg agentów wydaje się duży – w najlepszym testowanym przypadku 5% wybranych agentów jest w stanie dotrzeć do 70% wszystkich pracowników, w porównaniu z 40% zasięgiem uzyskanym przez agentów wybranych losowo. Duży zasięg komunikacji i wsparcia w zmianie organizacyjnej może zwiększyć szanse jej powodzenia dzięki kompleksowemu i ciągłemu dostarczaniu pracownikom rzetelnych informacji pochodzących z pierwszej ręki i wsparcia oraz zbieraniu od nich informacji zwrotnej. Jednocześnie zaangażowanie jak najmniejszej liczby osób w proces wsparcia zmiany pozwala na utrzymanie kosztów jej implementacji na relatywnie niskim poziomie.The dynamic business environment forces companies to change and adapt constantly. The process can be organized with help of change agents. We develop a simple network approach to spreading information and delivering feedback in organizations. We suggest selecting employees with a role of change agents, focusing on the coverage they can obtain in the network – minimize the number of involved agents and maximize the size of their overall communication area. To explore and pre-verify the proposed approach, we compared and examined several network and classical methods of selection. Data includes networks of collaboration from three medium-sized companies. Agents selected according to network betweenness centrality obtained the best and significantly broader reach than agents selected as employees with high hierarchy levels. Moreover, selected change agents reach impressive coverage; even 5% of company employees engaged as agents may directly reach up to 70% of company staff, compared to 40% for agents selected randomly. A large coverage of a company organizational network can increase the success of change initiatives as vital for spreading reliable, first-hand information and feedback about implemented change. On the other hand, engaging only a limited number of influential employees in a company’s network should keep costs of implementing change relatively low

Lome.io − cloud based, participatory network mapping platform for organizational network studies

Lome.io is cloud based software for collecting and analyzing network data. It integrates the process of collecting network data designed to support the most common organizational network studies with online network analysis module. It uses a highly customizable survey module to collect data that are connected to online network visualization and statistics modules, hence fully supporting the organizational and social network analysis (ONA, SNA) research process in a cloud. We present several key features of lome.io software in the context of organizational network analysis studies