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PDF | Identifying 'networked flow' as the key driver of networked creativity, this new volume in the Springer Briefs series deploys concepts from a range of authors apply expertise in experimental, social, cultural and educational psychology.
Table of contents

You can download and read online Networked Flow: Towards an. Dordrecht: SpringerBriefs in Education. Consultant for activating e-learning in educational and vocational training environments; Networked Flow creativity in complex networks. The integration of these two tools will lead to a meaningful comprehension of the context,..

Identifying 'networked flow' as the key driver of networked creativity, this new volume in the Springer Briefs series deploys apply expertise in experimental, social, cultural and educational psychology.

Chapman, C. From hierarchies to networks - possibilities and pitfalls for and middle leadership in schools: exploring the knowledge base —. The Social Network Revolution has led to the rise of networking sites. The term is an analogy to the concept of viral infections, which can spread.

Cities are getting interested in education and learning. Nonetheless, the network has gone on to develop a set of metrics Switzerland: SpringerBriefs.


  1. Networked Flow!
  2. The Tombstone Treasure Mystery?
  3. Gypsy Bride: One girls true story of falling in love with a gypsy boy.
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Open distance teaching and learning. Using NetLogo to simulate building occupancy of a university building. Research on the characteristics of evolution in knowledge flow networks of strategic Complex Network-Based Methods SpringerBriefs in Cognitive Computation. Global collaboration continues to grow as a share of all scientific cooperation, This is an open access article distributed under the terms of the Creative Commons.. The structure of the network appears to be robust—meaning that.

Reviewing mixed methods approaches using Social Network Analysis for learning and education. In: Pe a-Ayala,.. Creativity and Creative teaching and Learning.

On being a white, male keynote

In: Cremin, T. On the map: towards a multidimensional understanding of Open Educational Practices. As another example, two users having multiple common contacts e. However, such implicit data normally requires network analysis to be created, and there are few tools or methods to provide such data automatically.

Editorials

To summarize, we consider this list of BSD types could be valuable for researchers to outline the scope of their interests and will guide them to achieve successful outcomes. Nevertheless, research community has to remember that the accessibility of such data is a crucial challenge of BSD. Lack of access to the data often held by various service providers hinders the utilization of and research opportunities related to this emerging concept. Thus, researches should search for ways of collaboration with social media platforms.

The holistic overview of related concepts, research fields as well as research communities provide ideas regarding methodological steps that should be taken to enable further research and utilization activities around BSD. This is a combination of three activities that should be primarily focused on in order to open new avenues for the utilization. Collecting data The initial step for all researchers who work with BSD is to collect needed datasets for analysis. This step brings up the ethical issues and challenges of data accessibility.

Information

Indeed, there are challenges in terms of accessing the data as it is often held by various service providers, which hinders the utilization of the data. Fortunately, recently we have seen various movements and joint efforts for bringing together data that, in theory, is public but very challenging to collect in high volume enough for research purposes for example, the OSoMe Footnote 1 project to help analyzing Twitter data. One of the most troubling issues is related to ethics: majority of people are not aware about their data being collected and analyzed by different organizations including government and social media companies.

Moreover, the regulations on accessing and usage of such data are not clear and not completely unified. There are also challenges that may cause privacy violation: collecting more private data than allowed; accessing data without permissions; utilizing data for purposes, which are different from the initial purpose of collecting the data; misinterpreting the data; and changing the content. To make collecting phase feasible we need to fulfill the next step of our framework.

Collaboration BSD is multidisciplinary area that will require practitioners to build a proper team for work. Our suggestion is to build collaboration with social media platforms or companies that have access to actually large data sets. For instance, the research outcomes from thousands of twits would be questionable in comparison with research under billions of human-generated content from multiple channels. Manipulating data We argue that for gaining meaningful insights from BSD, researchers should design virtual environments where they would be able to access multiple data types, to compare and control them.

It may bring new opportunities for authentic and reliable research outcomes. BSD artificial environments also could give opportunity to run virtual experiments and validate results with members of related research community. This paper was aimed to bring clarity on BSD topic in general for any application area. As for our intended future work, we aim to utilize BSD to foster serendipity and, thus, innovativeness in knowledge work organizations. Our objective is to obtain empirical evidence that analysis of BSD can help identify relevant new people to collaborate with.

The multidisciplinary and multi-dimensional nature of Big Social Data brings challenges to the development of a useful conceptualization and definition of the concept. Our literature overview shows that majority of related work on BSD is focused on the analysis of social data, giving less attention to describing what BSD actually is.

This can lead to lack of consensus, inconsistency, and vague understanding of what such data could be used for. To bring clarity and sophisticated understanding of BSD we propose a synthesized conceptualization and definition of the concept and this growing field.

Conceptualizing Big Social Data | Journal of Big Data | Full Text

We reviewed existing literature that demonstrates a variety of applications and approaches to study the phenomena around social data. We assume the knowledge about the involvement of each field would provide researches with the understanding of the expertise that is demanded for conducting research in this field. Additionally, we proposed the classification of BSD types that, from our perspective, well cover the spectrum of data that BSD consists of. In summary, with this paper, we aim to make researchers more informed about what is BSD, on what data to focus as well as motivate them to elaborate better conceptualization, in order to reach clear desirable research outcomes.

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Conceptualizing Big Social Data

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Networked Flow

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European Journal of Social Theory. Traffic analysis based on short texts from social media.