scholarly journals Social network analysis and the implications for Pontocaspian biodiversity conservation in Romania and Ukraine: A comparative study

PLoS ONE ◽  
2020 ◽  
Vol 15 (10) ◽  
pp. e0221833
Author(s):  
Aleksandre Gogaladze ◽  
Niels Raes ◽  
Jacobus C. Biesmeijer ◽  
Camelia Ionescu ◽  
Ana-Bianca Pavel ◽  
...  
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Comparative Study ◽  
Biodiversity Conservation

scholarly journals The transition towards a bio-based economy: A comparative study based on social network analysis

2019 ◽  
Vol 230 ◽  
pp. 255-265 ◽  
Author(s):  
Enrica Imbert ◽  
Luana Ladu ◽  
Almona Tani ◽  
Piergiuseppe Morone
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Comparative Study

EXPLORATORY ANALYSIS ON THE DIFFERENT MODELS AND APPROACHES FOR SOCIAL NETWORK ANALYSIS

2021 ◽  
Vol 12 (1) ◽  
pp. 706-711
Author(s):  
Mansi Singh ◽  
Chandni Deb ◽  
Ashna Prasad ◽  
Naveen Renji
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Comparative Study ◽  
Exploratory Analysis ◽  
General Activity ◽  
The Comparative Study

The following paper consists of an overall comparative study of Social Network Analysis. The comparative study provides detailed information and is carried out based on the different models approached for Social Network Analysis. Social network analysis is a method capable of monitoring the interactions in an online environment.SNA can be used to reveal important information about the sentiments of different actors, such as the general activity and the active groups.

Graph Tools for Social Network Analysis

2018 ◽  
pp. 18-33 ◽  
Author(s):  
Nadeem Akhtar ◽  
Mohd Vasim Ahamad
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Comparative Study ◽  
General Graph ◽  
Network Mining ◽  
Social Network Mining ◽  
Time Graph ◽  
The Social

A social network can be defined as a complex graph, which is a collection of nodes connected via edges. Nodes represent individual actors or people in the network, whereas edges define relationships among those actors. Most popular social networks are Facebook, Twitter, and Google+. To analyze these social networks, one needs specialized tools for analysis. This chapter presents a comparative study of such tools based on the general graph aspects as well as the social network mining aspects. While considering the general graph aspects, this chapter presents a comparative study of four social network analysis tools—NetworkX, Gephi, Pajek, and IGraph—based on the platform, execution time, graph types, algorithm complexity, input file format, and graph features. On the basis of the social network mining aspects, the chapter provides a comparative study on five specialized tools—Weka, NetMiner 4, RapidMiner, KNIME, and R—with respect to the supported mining tasks, main functionality, acceptable input formats, output formats, and platform used.

scholarly journals Using social network analysis to assess the Pontocaspian biodiversity conservation capacity in Ukraine

2020 ◽  
Vol 25 (2) ◽  
Author(s):  
Aleksandre Gogaladze ◽  
Frank P. Wesselingh ◽  
Koos Biesmeijer ◽  
Vitaliy V. Anistratenko ◽  
Natalia Gozak ◽  
...  
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Biodiversity Conservation

Graph Tools for Social Network Analysis

2021 ◽  
pp. 485-500
Author(s):  
Nadeem Akhtar ◽  
Mohd Vasim Ahamad
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Comparative Study ◽  
General Graph ◽  
Network Mining ◽  
Social Network Mining ◽  
Time Graph ◽  
The Social

A social network can be defined as a complex graph, which is a collection of nodes connected via edges. Nodes represent individual actors or people in the network, whereas edges define relationships among those actors. Most popular social networks are Facebook, Twitter, and Google+. To analyze these social networks, one needs specialized tools for analysis. This chapter presents a comparative study of such tools based on the general graph aspects as well as the social network mining aspects. While considering the general graph aspects, this chapter presents a comparative study of four social network analysis tools—NetworkX, Gephi, Pajek, and IGraph—based on the platform, execution time, graph types, algorithm complexity, input file format, and graph features. On the basis of the social network mining aspects, the chapter provides a comparative study on five specialized tools—Weka, NetMiner 4, RapidMiner, KNIME, and R—with respect to the supported mining tasks, main functionality, acceptable input formats, output formats, and platform used.

scholarly journals Social network analysis and the implications for Pontocaspian biodiversity conservation in Romania and Ukraine: A comparative study

2019 ◽  
Author(s):  
Aleksandre Gogaladze ◽  
Niels Raes ◽  
Koos Biesmeijer ◽  
Camelia Ionescu ◽  
Bianca Pavel ◽  
...  
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Biodiversity Conservation ◽  
Black Sea ◽  
The Black Sea ◽  
The European Union ◽  
Conservation Action ◽  
Social Network Structure ◽  
The Social

AbstractRomania and Ukraine share the Black Sea coastline, the Danube Delta and associated habitats, which harbor the unique Pontocaspian biodiversity. Pontocaspian biota represents endemic aquatic taxa adapted to the brackish (anomalohaline) conditions, which evolved in the Caspian and Black Sea basins. Currently, this biota is diminishing both in the numbers of species and their abundance because of human activities. Consequently, its future persistence strongly depends on the adequacy of conservation measures. Romania and Ukraine have a common responsibility to effectively address the conservation of this biota. The socio-political and legal conservation frameworks, however, differ in the two countries - Romania is a member of the European Union (EU), thus complying with the EU environmental policy, whereas Ukraine is an EU-associated country. This may result in differences in the social network structure of stakeholder institutions with different implications for Pontocaspian biodiversity conservation. Here, we study the structure and implications of the social network of stakeholder organizations involved in conservation of Pontocaspian biodiversity in Romania, and compare it to Ukraine. We apply a mix of qualitative and quantitative social network analysis methods to combine the content and context of the interactions with relational measures. We show that the social networks of stakeholder organizations in Romania and Ukraine are very different. Structurally, in Romanian network there is a room for improvement through e.g. more involvement of governmental and non-governmental organizations and increased motivation of central stakeholders to initiate conservation action, whereas Ukrainian network is close to optimal. Regardless, both networks translate into sub-optimal conservation action and the road to optimal conservation is different. We end with sketching implications and recommendations for improved national and cross-border conservation efforts.

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