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Why do animals form swarms? - Maria R. D'Orsogna
🔖 Different approaches to community detection
Martin Rosvall, Jean-Charles Delvenne, Michael T. Schaub, Renaud Lambiotte
🔗 arxiv.org/pdf/1712.06468.pdf
📌 ABSTRACT
A precise definition of what constitutes a community in networks has remained elusive. Consequently, network scientists have compared community detection algorithms on benchmark networks with a particular form of community structure and classified them based on the mathematical techniques they employ. However, this comparison can be misleading because apparent similarities in their mathematical machinery can disguise different reasons for why we would want to employ community detection in the first place. Here we provide a focused review of these different motivations that underpin community detection. This problem-driven classification is useful in applied network science, where it is important to select an appropriate algorithm for the given purpose. Moreover, highlighting the different approaches to community detection also delineates the many lines of research and points out open directions and avenues for future research.
Martin Rosvall, Jean-Charles Delvenne, Michael T. Schaub, Renaud Lambiotte
🔗 arxiv.org/pdf/1712.06468.pdf
📌 ABSTRACT
A precise definition of what constitutes a community in networks has remained elusive. Consequently, network scientists have compared community detection algorithms on benchmark networks with a particular form of community structure and classified them based on the mathematical techniques they employ. However, this comparison can be misleading because apparent similarities in their mathematical machinery can disguise different reasons for why we would want to employ community detection in the first place. Here we provide a focused review of these different motivations that underpin community detection. This problem-driven classification is useful in applied network science, where it is important to select an appropriate algorithm for the given purpose. Moreover, highlighting the different approaches to community detection also delineates the many lines of research and points out open directions and avenues for future research.
🎞 Stanford Complexity Symposium Videos Now Online
https://www.youtube.com/playlist?list=PL4K77C_Lzqan0Ysv_BtrTDJT8vAt2ezC7
https://www.youtube.com/playlist?list=PL4K77C_Lzqan0Ysv_BtrTDJT8vAt2ezC7
YouTube
Stanford Complexity Symposium - 11/14/2017 - YouTube
🎞 How can we understand a city through its infrastructure networks?
https://cns.ceu.edu/article/2017-12-19/visualizing-street-network-budapest
https://vimeo.com/247808832?ref=tw-share
https://cns.ceu.edu/article/2017-12-19/visualizing-street-network-budapest
https://vimeo.com/247808832?ref=tw-share
Vimeo
Budapest Network Attack Tolerance
Simulation of a network attack based on the betweenness centrality of the nodes.
Complex Systems Studies
https://iasbs.ac.ir/seminar/physics/condmat-meeting/m24/
A one-day school is also planned prior to the meeting, which will offer lectures for graduate students and young researchers on a special topic each year. The subject of this year's school will be "Complex Systems".
A Peregrine falcon chasing a flock of starling. Awesome pics by Nick Dunlop https://t.co/Tdvn4pOMWs
#سمینارهای_هفتگی گروه سیستمهای پیچیده و علم شبکه دانشگاه شهید بهشتی
🔹دوشنبه، ۴ دیماه، ساعت ۱۶ - کلاس۱ دانشکده فیزیک دانشگاه شهید بهشتی.
@carimi
🔹دوشنبه، ۴ دیماه، ساعت ۱۶ - کلاس۱ دانشکده فیزیک دانشگاه شهید بهشتی.
@carimi
🔖 The advantages of interdisciplinarity in modern science
Moreno Bonaventura, Vito Latora, Vincenzo Nicosia, Pietro Panzarasa
🔗 arxiv.org/pdf/1712.07910.pdf
📌 ABSTRACT
As the increasing complexity of large-scale research requires the combined efforts of scientists with expertise in different fields, the advantages and costs of interdisciplinary scholarship have taken center stage in current debates on scientific production. Here we conduct a comparative assessment of the scientific success of specialized and interdisciplinary researchers in modern science. Drawing on comprehensive data sets on scientific production, we propose a two-pronged approach to interdisciplinarity. For each scientist, we distinguish between background interdisciplinarity, rooted in knowledge accumulated over time, and social interdisciplinarity, stemming from exposure to collaborators' knowledge. We find that, while abandoning specialization in favor of moderate degrees of background interdisciplinarity deteriorates performance, very interdisciplinary scientists outperform specialized ones, at all career stages. Moreover, successful scientists tend to intensify the heterogeneity of collaborators and to match the diversity of their network with the diversity of their background. Collaboration sustains performance by facilitating knowledge diffusion, acquisition and creation. Successful scientists tend to absorb a larger fraction of their collaborators' knowledge, and at a faster pace, than less successful ones. Collaboration also provides successful scientists with opportunities for the cross-fertilization of ideas and the synergistic creation of new knowledge. These results can inspire scientists to shape successful careers, research institutions to develop effective recruitment policies, and funding agencies to award grants of enhanced impact.
Moreno Bonaventura, Vito Latora, Vincenzo Nicosia, Pietro Panzarasa
🔗 arxiv.org/pdf/1712.07910.pdf
📌 ABSTRACT
As the increasing complexity of large-scale research requires the combined efforts of scientists with expertise in different fields, the advantages and costs of interdisciplinary scholarship have taken center stage in current debates on scientific production. Here we conduct a comparative assessment of the scientific success of specialized and interdisciplinary researchers in modern science. Drawing on comprehensive data sets on scientific production, we propose a two-pronged approach to interdisciplinarity. For each scientist, we distinguish between background interdisciplinarity, rooted in knowledge accumulated over time, and social interdisciplinarity, stemming from exposure to collaborators' knowledge. We find that, while abandoning specialization in favor of moderate degrees of background interdisciplinarity deteriorates performance, very interdisciplinary scientists outperform specialized ones, at all career stages. Moreover, successful scientists tend to intensify the heterogeneity of collaborators and to match the diversity of their network with the diversity of their background. Collaboration sustains performance by facilitating knowledge diffusion, acquisition and creation. Successful scientists tend to absorb a larger fraction of their collaborators' knowledge, and at a faster pace, than less successful ones. Collaboration also provides successful scientists with opportunities for the cross-fertilization of ideas and the synergistic creation of new knowledge. These results can inspire scientists to shape successful careers, research institutions to develop effective recruitment policies, and funding agencies to award grants of enhanced impact.