The Social Network Analysis to Study Discourse …
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environmental and economic dimensions of the provoked trade-offs by allocating
resources between the three domains of the nexus. Therefore, it becomes relevant to
consider how social sciences and interdisciplinary approaches can contribute toward
obtaining more promising results that can be applied in decision-making for integrated resource management [1]. These epistemological challenges, externalized by
the nexus approach, are often justified by a lack of sufficient information [2] or
specific methodologies and tools for analysis, and can be justified by the sectorialization of the knowledge and management models applied to the management
of resources over the years. Therefore, we understand that by testing methodologies from different contexts and territorial sections it can contribute toward the
optimization of research applied to the nexus.
3 Social Network Analysis
Social network analysis (SNA) is the study of social structures, specifically the interactions and networks between a group of actors (individuals or organizations), represented by nodes, which are tied by some way by common interests, such as financial exchanges, friendship, dislike, knowledge or prestige [10, 22]. Social networks
operate on many levels, from family relationships and diseases spreading to the level
of corporate strategies, social movements or even nations.
SNA is a way to re-incorporate context and bridge the gap between the micro and
the macro, the cells constituting an animal, the individuals constituting groups, or the
actors constituting a political system. Thus, the method allows researchers to retain
the traditional units of recording but simultaneously broadens the perspective by
including information about the relationships across units. The additional structural
information gained from this method allows researchers to address existing research
questions with new tools and to approach them from different theoretical perspective
[9].
SNA mixes sociology and mathematics in an attempt to simplify sociological
concept and explain macro-sociologicaly issues from a micro-sociology perspective.
In SNA analysis, social relations are conceived in terms of vertices and edges, and
mathematical graphs (called “graphs”), whereby actors are represented by vertices
and connections are represented by either edges or arcs (with directions) [10, 41].
Actors can either be individuals or groups of individuals, for example, companies,
communities, social organizations, countries, or cities. Connections are relationships among actors, for example, power, partnerships, family kinship, e-mail contact,
common religious beliefs, or rivalry. Moreover, connections may have one or more
weights. The result produced are structures based on graphs or sociograms, sometimes very complex and difficult to interpret, and has achieved significant results
thanks to the joint of innumerable researchers from various fields, in particular from
the field of computer science.
Network analysis focuses on calculating all the basic properties of a given network,
such as the diameter of the graph and the geodesic distances (shortest path lengths),
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environmental and economic dimensions of the provoked trade-offs by allocating
resources between the three domains of the nexus. Therefore, it becomes relevant to
consider how social sciences and interdisciplinary approaches can contribute toward
obtaining more promising results that can be applied in decision-making for integrated resource management [1]. These epistemological challenges, externalized by
the nexus approach, are often justified by a lack of sufficient information [2] or
specific methodologies and tools for analysis, and can be justified by the sectorialization of the knowledge and management models applied to the management
of resources over the years. Therefore, we understand that by testing methodologies from different contexts and territorial sections it can contribute toward the
optimization of research applied to the nexus.
3 Social Network Analysis
Social network analysis (SNA) is the study of social structures, specifically the interactions and networks between a group of actors (individuals or organizations), represented by nodes, which are tied by some way by common interests, such as financial exchanges, friendship, dislike, knowledge or prestige [10, 22]. Social networks
operate on many levels, from family relationships and diseases spreading to the level
of corporate strategies, social movements or even nations.
SNA is a way to re-incorporate context and bridge the gap between the micro and
the macro, the cells constituting an animal, the individuals constituting groups, or the
actors constituting a political system. Thus, the method allows researchers to retain
the traditional units of recording but simultaneously broadens the perspective by
including information about the relationships across units. The additional structural
information gained from this method allows researchers to address existing research
questions with new tools and to approach them from different theoretical perspective
[9].
SNA mixes sociology and mathematics in an attempt to simplify sociological
concept and explain macro-sociologicaly issues from a micro-sociology perspective.
In SNA analysis, social relations are conceived in terms of vertices and edges, and
mathematical graphs (called “graphs”), whereby actors are represented by vertices
and connections are represented by either edges or arcs (with directions) [10, 41].
Actors can either be individuals or groups of individuals, for example, companies,
communities, social organizations, countries, or cities. Connections are relationships among actors, for example, power, partnerships, family kinship, e-mail contact,
common religious beliefs, or rivalry. Moreover, connections may have one or more
weights. The result produced are structures based on graphs or sociograms, sometimes very complex and difficult to interpret, and has achieved significant results
thanks to the joint of innumerable researchers from various fields, in particular from
the field of computer science.
Network analysis focuses on calculating all the basic properties of a given network,
such as the diameter of the graph and the geodesic distances (shortest path lengths),