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modified degree-centrality.adoc with clarification
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doc/modules/ROOT/pages/algorithms/degree-centrality.adoc

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== Introduction
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The Degree Centrality algorithm can be used to find popular nodes within a graph.
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Degree centrality measures the number of incoming or outgoing (or both) relationships from a node, depending on the orientation of a relationship projection.
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For more information on relationship orientations, see the xref:management-ops/graph-creation/graph-project.adoc#relationship-projection-syntax[relationship projection syntax section].
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The degree centrality measures the number of incoming or outgoing (or both) relationships from a node, which can be defined by the orientation of a relationship projection. If a projection contains directed relationships, only outgoing relationships of a node are considered (the out-degree).
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For more information on how relationship orientations influence the algorithm result, see the xref:algorithms-degree-centrality-orientation-example[setting an orientation] section.
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For more general information on relationship orientations, see the xref:management-ops/graph-creation/graph-project.adoc#relationship-projection-syntax[relationship projection syntax] section.
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It can be applied to either weighted or unweighted graphs.
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In the weighted case the algorithm computes the sum of all positive weights of adjacent relationships of a node, for each node in the graph.
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The graph is projected in a `REVERSE` orientation in order to retrieve people with the most followers in the following examples.
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For directed relationships, the Degree Centrality algorithm computes the out-degree of each node.
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In order to retrieve people with the most followers, the graph is projected in a `REVERSE` orientation in the following examples.
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This will be demonstrated using the Degree Centrality algorithm on this graph.
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