scholarly journals Inventors Dynamics in Balkanic Area: Evidences by a Network Analysis

2021 ◽  
Vol 7 (4) ◽  
pp. 230-242
Author(s):  
T. Ciano ◽  
P. Fotia ◽  
B. A. Pansera ◽  
M. Ferrara
Keyword(s):  
Network Analysis ◽  
Innovation Process ◽  
The European Union ◽  
Patent Data ◽  
Seminal Paper ◽  
Analysis Techniques ◽  
Novel Approach ◽  
Source Of Information ◽  
Over Time ◽  
Selection Of

Abstract: Patent data is a key source of information for innovation economists. In recent decades it has been possible to observe its significant diffusion and success mainly thanks either to archives digitization or to authorities’ greater openness with respect to patent granting procedure. Furthermore, the use of this information over time has not been limited to simple statistics on patents and their classification, but, going further, has extended to the analysis of applicants, inventors, citations, and much more. By this seminal paper, we are going to analyze starting from Data analysis related to a selection of Balkanic Countries, chosen among the most dynamic in innovation process and production of patents: Croatia, Serbia, and Bosnia and Herzegovina. How it will explain into the work, this selection was not accidental: the aim was to represent the evolution of these Countries, in terms of patent internationalization, depending on their “link” with the European Union, not all Western Balkan Countries are in fact part of it. Croatia, an official EU member since 2012, was chosen as the representative state of European influence. Some interesting results were obtained with a novel approach by social network analysis techniques.

scholarly journals A scoping review using social network analysis techniques to summarise the prevalance of methods used to acquire data for athlete survelliance in sport

2021 ◽  
Vol 20 (2) ◽  
pp. 175-197
Author(s):  
P. J. Watson ◽  
J. E. Fieldsend ◽  
V.H. Stiles
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Scoping Review ◽  
Data Driven ◽  
Surveillance Systems ◽  
Analysis Techniques ◽  
Access Information ◽  
Visual Resource ◽  
Selection Of

Abstract To aid the implementation of athlete surveillance systems relative to logistical circumstances, easy-to-access information that summarises the extent to which methods of acquiring data are used in practice to monitor athletes is required. In this scoping review, Social Network Analysis and Mining (SNAM) techniques were used to summarise and identify the most prevalent combinations of methods used to monitor athletes in research studying team, individual, field- and court-based sports (357 articles; SPORTDiscus, MEDLINE, CINHAL, and WebOfScience; 2014-2018 inc.) . The most prevalent combination in team and field-based sports were HR and/or sRPE (internal) and GPS, whereas in individual and court-based sports, internal methods (e.g., HR and sRPE) were most prevalent. In court-based sports, where external methods were occasionally collected in combination with internal methods of acquiring data, the use of accelerometers or inertial measuring units (ACC/IMU) were most prevalent. Whilst individual and court-based sports are less researched, this SNAM-based summary reveals that court-based sports may lead the way in using ACC/IMU to monitor athletes. Questionnaires and self-reported methods of acquiring data are common in all categories of sport. This scoping review provides coaches, sport-scientists and researchers with a data-driven visual resource to aid the selection of methods of acquiring data from athletes in all categories of sport relative to logistical circumstances. A guide on how to practically implement a surveillance system based on the visual summaries provided herein, is also presented.

scholarly journals Novel Approach for Optimizing Information Propagation in Dynamic Social Network

2020 ◽  
Vol 19 ◽  
Keyword(s):  
Graph Theory ◽  
Social Network ◽  
Network Analysis ◽  
Dynamic Networks ◽  
Degree Centrality ◽  
Information Propagation ◽  
Precise Information ◽  
Dynamic Social Network ◽  
Novel Approach ◽  
Selection Of

Identification of potential node is one of the essential operations to be carried out in social network analysis as it is necessary to undertake various important decisions associated with the information propagation. Review of existing literature towards social network highlights that there is very less work carried out towards emphasizing potential node. Therefore, the proposed study offers a novel and unique solution that is capable of optimizing the level of information propagation when it is exposed to dynamic networks. The proposed study has been modeled using graph theory and it uses degree centrality distribution in order to offer more insight towards analyzing the selection of potential nodes in a social network. The study significantly contributes towards precise information propagation and its sustainability in the presence of dynamic social network in every aspect.

When the team’s jersey is what matters: Network analysis of party cohesion and structure in the Canadian House of Commons

2018 ◽  
Vol 26 (5) ◽  
pp. 555-569
Author(s):  
David Chartash ◽  
Nicholas J Caruana ◽  
Markus Dickinson ◽  
Laura B Stephenson
Keyword(s):  
Network Analysis ◽  
Voting Behavior ◽  
Prime Minister ◽  
Central Control ◽  
House Of Commons ◽  
Members Of Parliament ◽  
Novel Approach ◽  
Party Line ◽  
Party Cohesion ◽  
Over Time

Are parties “high discipline, low cohesion” in Westminster legislatures? This study applies network analysis to voting behavior among members of parliament (MPs), a novel approach that measures not deviation from party-line voting, but rather whether MPs with similar voting patterns are co-partisans. We study the Canadian Parliament from 2006 to 2015, during which time the governing party under Prime Minister Stephen Harper maintained tight central control and discipline, a likely source of elevated cohesion. We find that “low cohesion” generally holds, and parties do not always conform to commonsense expectations about how cohesively they “should” behave in various parliamentary situations, though they show themselves capable of learning over time. Moreover, we find that party cohesion stems less from shared voting behaviors and more from simple partisan identity. Further research should consider to what extent parliamentary behavior is based mainly on party alignment.

scholarly journals Analysis of scientific collaboration network of Italian Institute of Technology

2021 ◽  
Author(s):  
Enrico di Bella ◽  
Luca Gandullia ◽  
Sara Preti
Keyword(s):  
Social Network ◽  
Network Analysis ◽  
Scientific Collaboration ◽  
Complex Structure ◽  
Scientific Productivity ◽  
Positive Influence ◽  
Collaboration Network ◽  
Analysis Techniques ◽  
Institute Of Technology ◽  
Over Time

AbstractIt has been proven that collaboration between authors leads to a positive influence on research. This paper aims to analyse the complex structure of the co-authorship network among researchers of the Italian Institute of Technology. In this paper, we examine two different co-authorship networks created starting from the data of the papers published by the Italian Institute of Technology during the period 2006–2019. We apply the main Social Network Analysis techniques to describe the relational structure of the group of researchers and its evolution over time. The structure and characteristics of the networks are analysed both at macro and micro levels, and an attempt is made to identify a possible relationship between the position of researchers in the graphs and their scientific productivity and quality.

scholarly journals Networked Pantheon: a Relational Database of Globally Famous People

2018 ◽  
Author(s):  
Pablo Beytía ◽  
Janosch Schobin
Keyword(s):  
Network Analysis ◽  
Relational Database ◽  
Digital Method ◽  
Information Flows ◽  
Human History ◽  
Famous People ◽  
Occupational Information ◽  
Historical Figures ◽  
Source Of Information ◽  
Over Time

This article presents Networked Pantheon, a relational database of biographies of globally famous people spanning the last 5,500 years of human history. This source of information is intended to complement Pantheon 1.0 (Yu et. al. 2016), a biographical dataset that includes temporal, spatial, gender, and occupational information on 11,341 world-renowned people –defined as those who have their biographies in 25 or more Wikipedia language-versions–. Networked Pantheon adds information about the biographical links between these historical figures, which was compiled from the hyperlinks between the biographies in English Wikipedia. This digital method allows technics from network analysis to be used to study the relationships between globally famous people, and thus to calculate different measures of historical centrality for individuals, cities, countries, genders, and occupations. Networked Pantheon complements the historical popularity indicators of Pantheon 1.0 with measurements of the centrality of the figures in the network of biographical references, allowing for an approximation to the information flows between different territories, genders, and occupations of famous people over time.

Developing a sustainable Digital Health Innovation Ecosystem in a rural and resource-poor region: A monitored networking approach (Preprint)

2020 ◽  
Author(s):  
Arunangsu Chatterjee ◽  
Sebastian Stevens ◽  
Sheena Asthana ◽  
Ray B Jones
Keyword(s):  
Social Network ◽  
Network Analysis ◽  
Data Collection ◽  
Digital Health ◽  
Resource Poor Setting ◽  
Quadruple Helix ◽  
Innovation Ecosystem ◽  
Resource Poor ◽  
Quadruple Helix Model ◽  
Over Time

BACKGROUND Digital health (DH) innovation ecosystems (IE) are key to the development of new e-health products and services. Within an IE, third parties can help promote innovation by acting as knowledge brokers and the conduits for developing inter-organisational and interpersonal relations, particularly for smaller organisations. Kolehmainen’s quadruple helix model suggests who the critical IE actors are, and their roles. Within an affluent and largely urban setting, such ecosystems evolve and thrive organically with minimal intervention due to favourable economic and geographical conditions. Facilitating and sustaining a thriving DH IE within a resource-poor setting can be far more challenging even though far more important for such peripheral economics and the health and well-being of those communities. OBJECTIVE Taking a rural and remote region in the UK, as an instance of an IE in a peripheral economy, we adapt the quadruple helix model of innovation, apply a monitored social networking approach using McKinsey’s Three Horizons of growth to explore: • What patterns of connectivity between stakeholders develop within an emerging digital health IE? • How do networks develop over time in the DH IE? • In what ways could such networks be nurtured in order to build the capacity, capability and sustainability of the DH IE? METHODS Using an exploratory single case study design for a developing digital health IE, this study adopts a longitudinal social network analysis approach, enabling the authors to observe the development of the innovation ecosystem over time and evaluate the impact of targeted networking interventions on connectivity between stakeholders. Data collection was by an online survey and by a novel method, connection cards. RESULTS Self-reported connections between IE organisations increased between the two waves of data collection, with Small and Medium-sized Enterprises (SMEs) and academic institutions the most connected stakeholder groups. Patients involvement improved over time but still remains rather peripheral to the DH IE network. Connection cards as a monitoring tool worked really well during large events but required significant administrative overheads. Monitored networking information categorised using McKinsey’s Three Horizons proved to be an effective way to organise networking interventions ensuring sustained engagement. CONCLUSIONS The study reinforces the difficulty of developing and sustaining a DH IE in a resource-poor setting. It demonstrates the effective monitored networking approach supported by Social Network Analysis allows to map the networks and provide valuable information to plan future networking interventions (e.g. involving patients or service users). McKinsey’s Three Horizons of growth-based categorisation of the networking assets help ensure continued engagement in the DH IE contributing towards its long-term sustainability. Collecting ongoing data using survey or connection card method will become more labour intensive and ubiquitous ethically driven data collection methods can be used in future to make the process more agile and responsive.

Forecasting Interconnections in International Housing Markets: Evidence from the Dynamic Model Averaging Approach

2020 ◽  
Vol 42 (1) ◽  
pp. 37-103
Author(s):  
Hardik A. Marfatia
Keyword(s):  
Dynamic Model ◽  
Model Averaging ◽  
Housing Markets ◽  
The United States ◽  
Forecasting Model ◽  
Change Over Time ◽  
The United Kingdom ◽  
Novel Approach ◽  
Dynamic Model Averaging ◽  
Over Time

In this paper, I undertake a novel approach to uncover the forecasting interconnections in the international housing markets. Using a dynamic model averaging framework that allows both the coefficients and the entire forecasting model to dynamically change over time, I uncover the intertwined forecasting relationships in 23 leading international housing markets. The evidence suggests significant forecasting interconnections in these markets. However, no country holds a constant forecasting advantage, including the United States and the United Kingdom, although the U.S. housing market's predictive power has increased over time. Evidence also suggests that allowing the forecasting model to change is more important than allowing the coefficients to change over time.

scholarly journals The use of cement concrete pavements for roads, depending on climatic conditions

2019 ◽  
Vol 13 (3) ◽  
pp. 235-240
Author(s):  
Iryna Solonenko
Keyword(s):  
European Union ◽  
Statistical Models ◽  
Road Network ◽  
The European Union ◽  
Rational Selection ◽  
Cement Concrete ◽  
The Road ◽  
Road Pavement ◽  
Operational Characteristics ◽  
Selection Of

The development of road network infrastructure is an important component of the economic development of the European Union. Updating of the road network contributes to the integration of the economies of countries into a coherent whole. The road network provides the free movement of citizens, the movement of goods and the effective implementation of various services. The increase in the length of the road network leads to an increase in the financial and material costs necessary to ensure its maintenance and repair. One of the ways to reduce costs is by strengthening the physic-mechanical and operational characteristics of the pavement due to the widespread use of cement concrete. The quality of the pavement of cement concrete depends largely on the rational selection of its composition. This allows a significant increase in the durability of road pavement. The purpose of the research was: the development of recommendations for the rational selection of the composition of the road pavement material of cement concrete, aimed at upgrading longevity, and taking into account its frost resistance grade. According to the goal, the following tasks were developed: the analyses of the climatic zones in which the road network of the European Union is located; the development of a research plan, a selection of the response function and influence factors; the study of physico-mechanical and operational characteristics of the researched material of road pavement; on the basis of the obtained data, the calculation of the complex of experimental-statistical models, which describe the physico-mechanical and operational characteristics of the road pavement material; on the basis of experimental statistical models, a method was proposed for selecting the rational compositions of the cement concrete pavement road material depending on the conditions of its application. The results presented in the article can be used in engineering and scientific practice for the selection of road pavement from cement concrete for highways.

scholarly journals Non-random associations in group housed rats (Rattus norvegicus)

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Leanne Proops ◽  
Camille A. Troisi ◽  
Tanja K. Kleinhappel ◽  
Teresa Romero
Keyword(s):  
Network Analysis ◽  
Empirical Evidence ◽  
Rattus Norvegicus ◽  
Dominance Hierarchy ◽  
Group Living ◽  
Ecological Factors ◽  
Limited Evidence ◽  
Rat Strains ◽  
Social Species ◽  
Over Time

AbstractEcological factors, such as predation, have traditionally been used to explain sociability. However, it is increasingly recognised that individuals within a group do not associate randomly, and that these non-random associations can generate fitness advantages. The majority of the empirical evidence on differentiated associations in group-living mammals, however, comes from a limited number of taxa and we still know very little about their occurrence and characteristics in some highly social species, such as rats (Rattus spp.). Here, using network analysis, we quantified association patterns in four groups of male fancy rats. We found that the associations between rats were not randomly distributed and that most individuals had significantly more preferred/avoided associates than expected by random. We also found that these preferences can be stable over time, and that they were not influenced by individuals’ rank position in the dominance hierarchy. Our findings are consistent with work in other mammals, but contrast with the limited evidence available for other rat strains. While further studies in groups with different demographic composition are warranted to confirm our findings, the occurrence of differentiated associations in all male groups of rats have important implications for the management and welfare of captive rat populations.

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