Analyzing interactions in a healthcare network: first step for the design of a flexible information system

Healthcare network is an emergent organization mode which we were able to observe via RPM (“Réseau Pôle Mémoire” in French, which means memory pole network), dedicated to the medicopsycho- social coverage of people suffering from memory confusions. We define this collective as a community of action and we describe its functioning in order to suggest computer features allowing to support cooperative work between the professionals engaged in this network. In this article, we first position our work towards other researches on computer-supported medical activities. Then, we present RPM and suggest an analysis framework. We expose our first results after one year of observation, and we finally suggest improvements of the design of the cooperative information system

The Provision of Online Public Goods: Examining Social Structure in a Network of Practice

Networks of practice (NOPs) are social spaces where individuals working on similar problems self-organize to help each other and share perspectives about their occupational practice or common interests, and exist primarily through computer-mediated exchange. This exchange of knowledge through message postings produces an online public good, where all participants in the network can access the knowledge, regardless of their contribution. Thus, this research builds upon theories of collective action and public goods to better understand the provision and maintenance of knowledge in a network of practice. We use social network analysis to examine the following research questions: (1) What is the pattern of contribution that produces and sustains the public good? (2) Are NOPs maintained by a critical mass? (3) How does the heterogeneity of resources and interests of participants impact the collective action of the NOP? We find that the network of practice is sustained through generalized exchange, is supported by a critical mass of active members, and is shaped as a star. The critical mass is significantly related to tenure in the occupation, expertise, availability of local resources, and desire to enhance oneís reputation

The Evidence Hub: harnessing the collective intelligence of communities to build evidence-based knowledge

Conventional document and discussion websites provide users with no help in assessing the quality or quantity of evidence behind any given idea. Besides, the very meaning of what evidence is may not be unequivocally defined within a community, and may require deep understanding, common ground and debate. An Evidence Hub is a tool to pool the community collective intelligence on what is evidence for an idea. It provides an infrastructure for debating and building evidence-based knowledge and practice. An Evidence Hub is best thought of as a filter onto other websites — a map that distills the most important issues, ideas and evidence from the noise by making clear why ideas and web resources may be worth further investigation. This paper describes the Evidence Hub concept and rationale, the breath of user engagement and the evolution of specific features, derived from our work with different community groups in the healthcare and educational sector

A conceptual model for the development of CSCW systems

Models and theories concerning cooperation have long been recognised as an important aid in the development of Computer Supported Cooperative Work (CSCW) systems. However, there is no consensus regarding the set of concepts and abstractions that should underlie such models and theories. Furthermore, common patterns are hard to discern in different models and theories. This paper analyses a number of existing models and theories, and proposes a generic conceptual framework based on the strengths and commonalities of these models. We analyse five different developments, viz., Coordination Theory, Activity Theory, Task Manager model, Action/Interaction Theory and Object-Oriented Activity Support model, to propose a generic model based on four key concepts common to these developments, viz. activity, actor, information and service

The Role of Group Learning in Implementation of a Personnel Management System in a Hospital

A new HR system was introduced in a Dutch hospital. The system implied collaborative work among its users. The project planning seemed to be reasonably straightforward: the system's introduction was intended to take place gradually, including pilots in different departments and appropriate feedback. After some time, the system was successfully adopted by one group of users, but failed with another. We conceptualize the implementation process of groupware as group learning to frame the adoption of the system, and analyze the qualitative data collected during the longitudinal case study. We found that in the user group with strong group learning, adoption of the system occurred effectively and on time. In another user group with rather weak group learning, the use of the system was blocked after a short time. The results provided a first confirmation of our assumption about the importance of group learning processes in the implementation of groupware

Mobilizing the Trump Train: Understanding Collective Action in a Political Trolling Community

Political trolls initiate online discord not only for the lulz (laughs) but also for ideological reasons, such as promoting their desired political candidates. Political troll groups recently gained spotlight because they were considered central in helping Donald Trump win the 2016 US presidential election, which involved difficult mass mobilizations. Political trolls face unique challenges as they must build their own communities while simultaneously disrupting others. However, little is known about how political trolls mobilize sufficient participation to suddenly become problems for others. We performed a quantitative longitudinal analysis of more than 16 million comments from one of the most popular and disruptive political trolling communities, the subreddit /r/The\_Donald (T\D). We use T_D as a lens to understand participation and collective action within these deviant spaces. In specific, we first study the characteristics of the most active participants to uncover what might drive their sustained participation. Next, we investigate how these active individuals mobilize their community to action. Through our analysis, we uncover that the most active employed distinct discursive strategies to mobilize participation, and deployed technical tools like bots to create a shared identity and sustain engagement. We conclude by providing data-backed design implications for designers of civic media

Recursive encoding and decoding of the noiseless subsystem for qudits

We give a full explanation of the noiseless subsystem that protects a single-qubit against collective errors and the corresponding recursive scheme described by C.-K. Li et. al. [Phys. Rev. A 84, 044301 (2011)] from a representation theory point of view. Furthermore, we extend the construction to qudits under the influence of collective SU($d$) errors. We find that under this recursive scheme, the asymptotic encoding rate is $1/d$