Antecedents of Different Social Network Structures on Open Source Projects Popularity

2020 ◽  
pp. 143-157
Author(s):  
Shahab Bayati ◽  
Arvind Tripathi
Keyword(s):  
Social Network ◽  
Open Source ◽  
Network Structures

Social Network Structures in Open Source Software Development Teams

2009 ◽  
pp. 645-658
Author(s):  
Yuan Long ◽  
Keng Siau
Keyword(s):  
Social Network ◽  
Open Source ◽  
Open Source Software ◽  
Interaction Pattern ◽  
Network Structures ◽  
Monthly Data ◽  
Development Teams ◽  
Longitudinal View ◽  
Software Development Teams ◽  
Bug Tracking

Drawing on social network theories and previous studies, this research examines the dynamics of social network structures in open source software (OSS) teams. Three projects were selected from SourceForge.net in terms of their similarities as well as their differences. Monthly data were extracted from the bug tracking systems in order to achieve a longitudinal view of the interaction pattern of each project. Social network analysis was used to generate the indices of social structure. The finding suggests that the interaction pattern of OSS projects evolves from a single hub at the beginning to a core/periphery model as the projects move forward.

Social Network Structures in Open Source Software Development Teams

2009 ◽  
pp. 1835-1848 ◽  
Author(s):  
Yuan Long ◽  
Keng Siau
Keyword(s):  
Social Network ◽  
Open Source ◽  
Open Source Software ◽  
Interaction Pattern ◽  
Network Structures ◽  
Monthly Data ◽  
Development Teams ◽  
Longitudinal View ◽  
Software Development Teams ◽  
Bug Tracking

Drawing on social network theories and previous studies, this research examines the dynamics of social network structures in open source software (OSS) teams. Three projects were selected from SourceForge.net in terms of their similarities as well as their differences. Monthly data were extracted from the bug tracking systems in order to achieve a longitudinal view of the interaction pattern of each project. Social network analysis was used to generate the indices of social structure. The finding suggests that the interaction pattern of OSS projects evolves from a single hub at the beginning to a core/periphery model as the projects move forward.

scholarly journals Social Network Structures of Breast Cancer Patients and the Contributing Role of Patient Navigators

2017 ◽  
Vol 22 (8) ◽  
pp. 918-924 ◽  
Author(s):  
Christine M. Gunn ◽  
Victoria A. Parker ◽  
Sharon M. Bak ◽  
Naomi Ko ◽  
Kerrie P. Nelson ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Social Network ◽  
Cancer Patients ◽  
Network Structures ◽  
Breast Cancer Patients ◽  
Patient Navigators

Social Network Structures among Groundnut Farmers

2013 ◽  
Vol 19 (4) ◽  
pp. 339-359 ◽  
Author(s):  
Mary Thuo ◽  
Alexandra A. Bell ◽  
Boris E. Bravo-Ureta ◽  
David K. Okello ◽  
Evelyn Nasambu Okoko ◽  
...  
Keyword(s):  
Social Network ◽  
Network Structures

Simulating Social Network Formation

2011 ◽  
pp. 581-599
Author(s):  
Robert Gilles ◽  
Tabitha James ◽  
Reza Barkhi ◽  
Dimitrios Diamantaras
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Network Structure ◽  
Network Formation ◽  
Theoretic Model ◽  
Network Structures ◽  
Agent Behavior ◽  
Graph Theoretic ◽  
Model And Simulation ◽  
Graph Theoretic Models

Social networks depict complex systems as graph theoretic models. The study of the formation of such systems (or networks) and the subsequent analysis of the network structures are of great interest. For information systems research and its impact on business practice, the ability to model and simulate a system of individuals interacting to achieve a certain socio-economic goal holds much promise for proper design and use of cyber networks. We use case-based decision theory to formulate a customizable model of information gathering in a social network. In this model, the agents in the network have limited awareness of the social network in which they operate and of the fixed, underlying payoff structure. Agents collect payoff information from neighbors within the prevailing social network, and they base their networking decisions on this information. Along with the introduction of the decision theoretic model, we developed software to simulate the formation of such networks in a customizable context to examine how the network structure can be influenced by the parameters that define social relationships. We present computational experiments that illustrate the growth and stability of the simulated social networks ensuing from the proposed model. The model and simulation illustrates how network structure influences agent behavior in a social network and how network structures, agent behavior, and agent decisions influence each other.

Social Network Structures for Explicit, Tacit and Potential Knowledge

2011 ◽  
pp. 81-90
Author(s):  
Anssi Smedlund
Keyword(s):  
Knowledge Management ◽  
Social Network ◽  
Tacit Knowledge ◽  
Network Structure ◽  
Explicit Knowledge ◽  
Network Structures ◽  
Underlying Assumption ◽  
Knowledge Assets ◽  
Social Network Structure

The purpose of this conceptual article is to develop argumentation of the knowledge assets of a firm as consisting of three constructs, to extend the conventional explicit, tacit dichotomy by including potential knowledge. The article highlights the role of knowledge, which has so far not been utilized in value creation. The underlying assumption in the article is that knowledge assets can be thought of as embedded in the relationships between individuals in the firm, rather than possessed by single actors. The concept of potential knowledge is explained with selected social network and knowledge management literature. The findings suggest that the ideal social network structure for explicit knowledge is centralized, for tacit knowledge it is distributed, and for potential knowledge decentralized. Practically, the article provides a framework for understanding the connection between knowledge assets and social network structures, thus helping managers of firms in designing suitable social network structures for different types of knowledge.

INFORMATION EXCHANGES OF SOCIAL MEDIA EVANGELISTS DURING FLOOD: A SOCIAL NETWORK ANALYSIS

2016 ◽  
Vol 78 (9-3) ◽  
Author(s):  
Abdus-samad Temitope Olanrewaju ◽  
Rahayu Ahmad ◽  
Kamarul Faizal Hashim
Keyword(s):  
Social Media ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Network Structure ◽  
Information Dissemination ◽  
Network Structures ◽  
Analysis Technique ◽  
Types Of Information ◽  
Information Brokers

Information dissemination during disaster is very crucial, but inherits several complexities associated with the dynamic characteristics of the disaster. Social media evangelists (activists) play an important role in disseminating critical updates at on-site locations. However, there is limited understanding on the network structure formed and its evolution and the types of information shared. To address these questions, this study employs Social Network Analysis technique on a dataset containing 157 social media posts from an influential civilian fan page during Malaysia’s flood. The finding demonstrates three different network structures emerged during the flood period. The network structure evolves depending on the current state of the flood, the amount of information available and the need of information. Through content analysis, there were seven types of information exchanges discovered. These information exchanges evolved as the scale and magnitude of flood changes. In conclusion, this study shows the emergence of different network structures, density and identification of influential information brokers among civilians that use social media during disaster. Despite the low number of influential information brokers, they successfully manage their specific cluster in conveying information about the disaster and most importantly coordinating the rescue mission.

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