Scientific Collaboration in a Framework Programme: An Intensity-Heterogeneity Approach

2014 ◽  
Author(s):  
Aurrlien Fichet de Clairfontaine ◽  
Rafael Lata ◽  
Manfred F. Paier ◽  
Manfred M. Fischer
Keyword(s):  
Scientific Collaboration ◽  
Framework Programme

scholarly journals Multi-hop assortativities for network classification

2018 ◽  
Vol 7 (4) ◽  
pp. 603-622 ◽  
Author(s):  
Leonardo Gutiérrez-Gómez ◽  
Jean-Charles Delvenne
Keyword(s):  
Machine Learning ◽  
Scientific Collaboration ◽  
State Of The Art ◽  
Medical Engineering ◽  
Research Field ◽  
Classification Task ◽  
Collaboration Network ◽  
Structural Patterns ◽  
Art Methods

Abstract Several social, medical, engineering and biological challenges rely on discovering the functionality of networks from their structure and node metadata, when it is available. For example, in chemoinformatics one might want to detect whether a molecule is toxic based on structure and atomic types, or discover the research field of a scientific collaboration network. Existing techniques rely on counting or measuring structural patterns that are known to show large variations from network to network, such as the number of triangles, or the assortativity of node metadata. We introduce the concept of multi-hop assortativity, that captures the similarity of the nodes situated at the extremities of a randomly selected path of a given length. We show that multi-hop assortativity unifies various existing concepts and offers a versatile family of ‘fingerprints’ to characterize networks. These fingerprints allow in turn to recover the functionalities of a network, with the help of the machine learning toolbox. Our method is evaluated empirically on established social and chemoinformatic network benchmarks. Results reveal that our assortativity based features are competitive providing highly accurate results often outperforming state of the art methods for the network classification task.

scholarly journals The link between ethnic diversity and scientific impact: the mediating effect of novelty and audience diversity

2021 ◽  
Author(s):  
Jielan Ding ◽  
Zhesi Shen ◽  
Per Ahlgren ◽  
Tobias Jeppsson ◽  
David Minguillo ◽  
...  
Keyword(s):  
Ethnic Diversity ◽  
Scientific Collaboration ◽  
Information Science ◽  
Mediating Effect ◽  
Path Modeling ◽  
Control Variables ◽  
Scientific Impact ◽  
Subject Categories ◽  
Sound Management ◽  
The Relationship

AbstractUnderstanding the nature and value of scientific collaboration is essential for sound management and proactive research policies. One component of collaboration is the composition and diversity of contributing authors. This study explores how ethnic diversity in scientific collaboration affects scientific impact, by presenting a conceptual model to connect ethnic diversity, based on author names, with scientific impact, assuming novelty and audience diversity as mediators. The model also controls for affiliated country diversity and affiliated country size. Using path modeling, we apply the model to the Web of Science subject categories Nanoscience & Nanotechnology, Ecology and Information Science & Library. For all three subject categories, and regardless of if control variables are considered or not, we find a weak positive relationship between ethnic diversity and scientific impact. The relationship is weaker, however, when control variables are included. For all three fields, the mediated effect through audience diversity is substantially stronger than the mediated effect through novelty in the relationship, and the former effect is much stronger than the direct effect between the ethnic diversity and scientific impact. Our findings further suggest that ethnic diversity is more associated with short-term scientific impact compared to long-term scientific impact.

Scholar2vec: Vector Representation of Scholars for Lifetime Collaborator Prediction

2021 ◽  
Vol 15 (3) ◽  
pp. 1-19
Author(s):  
Wei Wang ◽  
Feng Xia ◽  
Jian Wu ◽  
Zhiguo Gong ◽  
Hanghang Tong ◽  
...  
Keyword(s):  
Scientific Collaboration ◽  
Early Stage ◽  
Collaboration Network ◽  
Vector Representation ◽  
Network Embedding ◽  
Machine Learning Methods ◽  
Academic Networks ◽  
Special Relationships ◽  
Real World Datasets ◽  
Vector Representations

While scientific collaboration is critical for a scholar, some collaborators can be more significant than others, e.g., lifetime collaborators. It has been shown that lifetime collaborators are more influential on a scholar’s academic performance. However, little research has been done on investigating predicting such special relationships in academic networks. To this end, we propose Scholar2vec, a novel neural network embedding for representing scholar profiles. First, our approach creates scholars’ research interest vector from textual information, such as demographics, research, and influence. After bridging research interests with a collaboration network, vector representations of scholars can be gained with graph learning. Meanwhile, since scholars are occupied with various attributes, we propose to incorporate four types of scholar attributes for learning scholar vectors. Finally, the early-stage similarity sequence based on Scholar2vec is used to predict lifetime collaborators with machine learning methods. Extensive experiments on two real-world datasets show that Scholar2vec outperforms state-of-the-art methods in lifetime collaborator prediction. Our work presents a new way to measure the similarity between two scholars by vector representation, which tackles the knowledge between network embedding and academic relationship mining.

scholarly journals Franco-British responses to chemical warfare 1915–8, with special reference to the medical services, casualty statistics and the threat to civilians

2021 ◽  
Vol 65 (2) ◽  
pp. 101-120
Author(s):  
Hanene Zoghlami
Keyword(s):  
Scientific Collaboration ◽  
Historical Narrative ◽  
Home Front ◽  
Medical Services ◽  
Striking Similarity ◽  
Chemical Weapon ◽  
The Impact ◽  
Compare And Contrast ◽  
British Chemical ◽  
Material Exchange

AbstractThis dual-focussed examination will critically compare and contrast the British Royal Army Medical Corps and the French Medical Service’s involvement in the Western Front chemical campaign between 1915 and 1918. Because the Anglophone historiography has tended to marginalise the French contribution to the allied chemical war, this article will attempt to re-balance the historical narrative by emphasising the collective nature and importance of this joint Franco-British enterprise. By interrogating a raft of under-utilised primary evidence in the French and British archives, this investigation will contribute to the ‘alliance literature’ by arguing that when it comes to aspects of the Franco-British chemical war such as the co-operation of the medical services, the appellation ‘together but alone’ does not fully hold. The article will explore avenues of the two national armies evolving process of mutual medical assistance, material exchange and scientific collaboration. The striking similarity of French and British gas casualty statistics is highlighted with reference to the overall congruence of their anti-gas strategies – notwithstanding the problematic nature of these statistics. In addition to enhancing soldiers’ resistance to the poison gas threat on the battlefield, the Medical Services were also responsible for the protection of local civilians in the war zones. With reference mainly to France, this investigation will discuss the significance and implications of the poison gas threat to the home front. Finally, the impact of chemical weapon production upon civilian war workers in France and Britain will be commented upon.

What the evaluation record tells us about European Union Framework Programme performance

2005 ◽  
Vol 32 (5) ◽  
pp. 385-397 ◽  
Author(s):  
Erik Arnold ◽  
John Clark ◽  
Alessandro Muscio
Keyword(s):  
European Union ◽  
Framework Programme
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