How context and attention shape behaviors in online communities: a modified garbage can model

2020 ◽  
Author(s):  
Nicolai J Foss ◽  
Lars Bo Jeppesen ◽  
Francesco Rullani
Keyword(s):  
Decision Making ◽  
Open Source ◽  
Open Source Software ◽  
Online Communities ◽  
Community Members ◽  
Individual Level ◽  
Garbage Can Model ◽  
Different Dimensions ◽  
Informal Context ◽  
Unique Dataset

Abstract Online communities have emerged as important organizational forms, but there are many gaps in our understanding. In particular, researchers have mainly focused on individual-level drivers of behaviors in communities, while downplaying (formal, informal) context at various levels. We theorize that different dimensions of context (i.e. omnibus and discrete context) influence decision-making in online communities through mechanisms involving community members’ attention. Specifically, context influences which problems members perceive and which solutions they retrieve and apply, thereby shaping the process of matching solutions and problems. We derive four hypotheses about contribution behaviors in online communities and how such behaviors are influenced by context. The empirical setting for our study is the open-source software community. We find support for our hypotheses in a unique dataset that captures the behavior of 24,057 community members who used the SourceForge.net online platform from 2000 to 2002.

scholarly journals Knowledge sharing in open source software communities: motivations and management

2015 ◽  
Vol 19 (4) ◽  
pp. 791-813 ◽  
Author(s):  
Zilia Iskoujina ◽  
Joanne Roberts
Keyword(s):  
Knowledge Sharing ◽  
Open Source ◽  
Open Source Software ◽  
Online Communities ◽  
Descriptive Analysis ◽  
Online Questionnaire ◽  
Content Type ◽  
The Individual ◽  
The Impact

Purpose – This paper aims to add to the understanding of knowledge sharing in online communities through an investigation of the relationship between individual participant’s motivations and management in open source software (OSS) communities. Drawing on a review of literature concerning knowledge sharing in organisations, the factors that motivate participants to share their knowledge in OSS communities, and the management of such communities, it is hypothesised that the quality of management influences the extent to which the motivations of members actually result in knowledge sharing. Design/methodology/approach – To test the hypothesis, quantitative data were collected through an online questionnaire survey of OSS web developers with the aim of gathering respondents’ opinions concerning knowledge sharing, motivations to share knowledge and satisfaction with the management of OSS projects. Factor analysis, descriptive analysis, correlation analysis and regression analysis were used to explore the survey data. Findings – The analysis of the data reveals that the individual participant’s satisfaction with the management of an OSS project is an important factor influencing the extent of their personal contribution to a community. Originality/value – Little attention has been devoted to understanding the impact of management in OSS communities. Focused on OSS developers specialising in web development, the findings of this paper offer an important original contribution to understanding the connections between individual members’ satisfaction with management and their motivations to contribute to an OSS project. The findings reveal that motivations to share knowledge in online communities are influenced by the quality of management. Consequently, the findings suggest that appropriate management can enhance knowledge sharing in OSS projects and online communities, and organisations more generally.

scholarly journals CREGIS-Q: a GIS tool to support decision making in case of aquifer contamination emergency

2016 ◽  
Author(s):  
Anna Bruna Petrangeli ◽  
Elisabetta Preziosi ◽  
Francesco Campopiano ◽  
Angelo Corazza ◽  
Andrea Duro
Keyword(s):  
Decision Making ◽  
Emergency Management ◽  
Open Source ◽  
Open Source Software ◽  
Aquifer Contamination ◽  
Gis Technology ◽  
Structure Programming ◽  
Spatial Decision Making ◽  
Environmental Risk Analysis ◽  
Support Decision Making

GIS technology has been used for many years in environmental risk analysis due to its capability to focus on the management and analysis of geographic and alphanumeric data to support spatial decision-making (Vairavamoorthy et al, 2007). Especially in emergency management, a DSS (Decision Support System) constitutes an important task to provide quick responses, though not completely exhaustive, to immediately handle a critical scenario and limit the possible damage. In the framework of a collaboration between the Water Research Institute and the National Civil Protection Department, a customized tool called CREGIS (ContaminazioneRisorseEvento-GIS) has been developed in order to facilitate the emergency management of accidental contamination of aquifers and support decision making (Preziosi et al, 2013). The tool is aimed at both national and local authorities in order to improve response capability for a better emergency management. Originally, the tool has been developed programming Python in an ArcGIS environment; but due to the great development and dissemination of open source software, our aim is to replicate the same structure programming Python in a GIS open source environment (QGIS). The review of the tool's code is still in progress. The goal is to make the tool (now named CREGIS-Q) free and accessible to a greater number of people and stakeholders.

scholarly journals CREGIS-Q: a GIS tool to support decision making in case of aquifer contamination emergency

2016 ◽  
Author(s):  
Anna Bruna Petrangeli ◽  
Elisabetta Preziosi ◽  
Francesco Campopiano ◽  
Angelo Corazza ◽  
Andrea Duro
Keyword(s):  
Decision Making ◽  
Emergency Management ◽  
Open Source ◽  
Open Source Software ◽  
Aquifer Contamination ◽  
Gis Technology ◽  
Structure Programming ◽  
Spatial Decision Making ◽  
Environmental Risk Analysis ◽  
Support Decision Making

GIS technology has been used for many years in environmental risk analysis due to its capability to focus on the management and analysis of geographic and alphanumeric data to support spatial decision-making [Vairavamoorthy et al, 2007]. Especially in emergency management, a DSS (Decision Support System) constitutes an important task to provide quick responses, though not completely exhaustive, to immediately handle a critical scenario and limit the possible damage. In the framework of a collaboration between the Water Research Institute and the National Civil Protection Department, a customized tool called CREGIS (ContaminazioneRisorseEvento-GIS) has been developed in order to facilitate the emergency management of accidental contamination of aquifers and support decision making [Preziosi et al, 2013]. The tool is aimed at both national and local authorities in order to improve response capability for a better emergency management. Originally, the tool has been developed programming Python in an ArcGIS environment; but due to the great development and dissemination of open source software, our aim is to replicate the same structure programming Python in a GIS open source environment (QGIS). The review of the tool's code is still in progress. The goal is to make the tool (now named CREGIS-Q) free and accessible to a greater number of people and stakeholders.

Conquery: an Open Source Application to analyze High Content Healthcare Data (Preprint)

2021 ◽  
Author(s):  
Fabian Kovacs ◽  
Max Thonagel ◽  
Marion Ludwig ◽  
Alexander Albrecht ◽  
Manuel Hegner ◽  
...  
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Data Analysis ◽  
Open Source ◽  
Open Source Software ◽  
Medical Records ◽  
Healthcare Sector ◽  
Study Cohort ◽  
Decision Making Processes ◽  
Analytical Approaches

BACKGROUND Big data in healthcare must be exploited to achieve a substantial increase in efficiency and competitiveness. Especially the analysis of patient-related data possesses huge potential to improve decision-making processes. However, most analytical approaches used today are highly time- and resource-consuming. OBJECTIVE The presented software solution Conquery is an open-source software tool providing advanced, but intuitive data analysis without the need for specialized statistical training. Conquery aims to simplify big data analysis for novice database users in the medical sector. METHODS Conquery is a document-oriented distributed timeseries database and analysis platform. Its main application is the analysis of per-person medical records by non-technical medical professionals. Complex analyses are realized in the Conquery frontend by dragging tree nodes into the query editor. Queries are evaluated by a bespoke distributed query-engine for medical records in a column-oriented fashion. We present a custom compression scheme to facilitate low response times that uses online calculated as well as precomputed metadata and data statistics. RESULTS Conquery allows for easy navigation through the hierarchy and enables complex study cohort construction whilst reducing the demand on time and resources. The UI of Conquery and a query output is exemplified by the construction of a relevant clinical cohort. CONCLUSIONS Conquery is an efficient and intuitive open-source software for performant and secure data analysis and aims at supporting decision-making processes in the healthcare sector.

Model to Estimate the Human Factor Quality in FLOSS Development

2015 ◽  
pp. 219-236
Author(s):  
Zulaima Chiquin ◽  
Kenyer Domínguez ◽  
Luis E. Mendoza ◽  
Edumilis Méndez
Keyword(s):  
Decision Making ◽  
Human Resources ◽  
Open Source ◽  
Open Source Software ◽  
Human Factor ◽  
Three Dimensions ◽  
Decision Making Process ◽  
Self Evaluation ◽  
Systemic Quality

This chapter presents a Model to Estimate the Human Factor Quality in Free/Libre Open Source Software (FLOSS) Development, or EHFQ-FLOSS. The model consists of three dimensions: Levels (individual, community, and foundation), Aspects (internal or contextual), and Forms of Evaluation (self-evaluation, co-evaluation, and hetero-evaluation). Furthermore, this model provides 145 metrics applicable to all three levels, as well as an algorithm that guides their proper application to estimate the systemic quality of human resources involved in the development of FLOSS, guide the decision-making process, and take possible corrective actions.

Key Concepts and Definitions of Open Source Communities

2010 ◽  
pp. 753-760
Author(s):  
Ruben van Wendel de Joode ◽  
Sebastian Spaeth
Keyword(s):  
Software Development ◽  
Open Source ◽  
Open Source Software ◽  
Online Communities ◽  
Source Code ◽  
Professional Organizations ◽  
Large Numbers ◽  
Key Concepts ◽  
Open Source Communities ◽  
Do So

Most open source software is developed in online communities. These communities are typically referred to as “open source software communities” or “OSS communities.” In OSS communities, the source code, which is the human-readable part of software, is treated as something that is open and that should be downloadable and modifiable to anyone who wishes to do so. The availability of the source code has enabled a practice of decentralized software development in which large numbers of people contribute time and effort. Communities like Linux and Apache, for instance, have been able to connect thousands of individual programmers and professional organizations (although most project communities remain relatively small). These people and organizations are not confined to certain geographical places; on the contrary, they come from literally all continents and they interact and collaborate virtually.

scholarly journals Canadian Public Libraries and their Interest in Open Source Software (OSS)

2018 ◽  
Author(s):  
Dinesh Rathi
Keyword(s):  
Decision Making ◽  
Open Source ◽  
Open Source Software ◽  
Public Libraries ◽  
Evaluation Criteria ◽  
Prise De Décision ◽  
Use Of Resources ◽  
Insight Into

This study presents findings of research conducted in the Open Source Software (OSS) domain in a Canadian public libraries context. The findings from the survey will provide insight into various facets such as use, benefits and challenges of OSS from Canadian libraries’ perspective, OSS evaluation criteria, use of resources to learn about OSS, and decision-making associated with OSS in Canadian libraries context.Cette étude présente les résultats de recherches menées dans le domaine des logiciels libres (Open Source Software - OSS) dans le contexte des bibliothèques publiques canadiennes. Les résultats du sondage fourniront un aperçu de diverses facettes telles que l'utilisation, les avantages et les défis des logiciels libres, du point de vue des bibliothèques canadiennes, des critères d'évaluation des logiciels libres, de l'utilisation des ressources pour en apprendre davantage sur les logiciels libres, et la prise de décision associée aux logiciels libres dans le contexte des bibliothèques canadiennes.

scholarly journals A Bias-Corrected Estimator for the Crosswise Model with Inattentive Respondents

2021 ◽  
pp. 1-15
Author(s):  
Yuki Atsusaka ◽  
Randolph T. Stevenson
Keyword(s):  
Sensitivity Analysis ◽  
Open Source ◽  
Open Source Software ◽  
Bias Correction ◽  
Power Analysis ◽  
Simple Design ◽  
Individual Level ◽  
Survey Technique ◽  
Sensitive Attribute ◽  
Crosswise Model

Abstract The crosswise model is an increasingly popular survey technique to elicit candid answers from respondents on sensitive questions. Recent studies, however, point out that in the presence of inattentive respondents, the conventional estimator of the prevalence of a sensitive attribute is biased toward 0.5. To remedy this problem, we propose a simple design-based bias correction using an anchor question that has a sensitive item with known prevalence. We demonstrate that we can easily estimate and correct for the bias arising from inattentive respondents without measuring individual-level attentiveness. We also offer several useful extensions of our estimator, including a sensitivity analysis for the conventional estimator, a strategy for weighting, a framework for multivariate regressions in which a latent sensitive trait is used as an outcome or a predictor, and tools for power analysis and parameter selection. Our method can be easily implemented through our open-source software cWise.

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