This is an overview of Overall Graph Metrics shown in the Overall Metrics spreadsheet of NodeXL and on the network report pages in NodeXL Graph Gallery.
A vertex is an element of a network. The vertices count is the number of people or things in the network.
An edge is a connection between two vertices. The “unique” edges count is the number of connections where multiple connections between A and B are counted only once.
Edges With Duplicates
An edge is a connection between two vertices. The “duplicate” edges count is the total number of multiple connections between two vertices.
The “total” edges count is the total number of connections where multiple connections between A and B are all counted.
An edge that starts and ends in the same vertex is a self-loop. These are also called isolates.
Reciprocated Vertex Pair Ratio
When two vertices both link to each other their connection is “reciprocated”. This is the percentage of vertices that have a reciprocal relationship. When an edge from A to B is joined by another edge from B to A then their connection is “reciprocated”.
Reciprocated Edge Ratio
This is the percentage of edges that have a reciprocal relationship.
A group of vertices that are all connected is a component. This is the number of separate sets of connected vertices.
Single-Vertex Connected Components
A vertex that has zero connections is “isolated” or an “island”. This is the count of vertices that have zero connections.
Maximum Vertices in a Connected Component
A connected component is composed of a number of vertices. This is the count of vertices in the largest connected component.
Maximum Edges in a Connected Component
A connected component is composed of a number of edges. This is the count of total edges in the largest connected component.
Maximum Geodesic Distance (Diameter)
A geodesic is a chain or path composed of edges that link two vertices, potentially through intermediate vertices. A “shortest path” is the minimum number of connections needed to link two vertices. The “longest” “shortest path” is the “maximum geodesic distance”.
Average Geodesic Distance
A geodesic is a chain or path composed of edges that link two vertices, potentially through intermediate vertices. The average length of these paths is the “average geodesic distance”.
Density is the measure of the number edges among a group of vertices over the total possible number if everyone was connected to everyone. A high graph density means that most people are connected to many others. A low graph density means that most people are not connected to many others.
Modularity is a measure of the fitness of the groups that are created in a clustered network. Many group cluster algorithms are intended to find sets of vertices that are strongly connected and relatively separate from other strongly connected groups. Modularity is the measure of the number of edges that leave a group to connect to vertices in a different group. If modularity is low, the clusters or groups created may be of low quality. If modularity is high, the groups are well defined.
NodeXL updates frequently and the current version number is provided to enable troubleshooting and to ensure older datasets are properly understood.
Time period of the data imported from the data source.
The algorithm used to determine the location of each vertex in the network visualization.
This is the data source of the network.
This is the query term used to import data from the data source listed above.
The algorithm used to determine the group membership for each vertex in the network.
Available cluster algorithms in NodeXL are: Clauset-Newman-Moore, Wakita-Tsurumi and Girvan-Newman. It is also possible to group by Vertex attribute or Connected Component.
This value represents the strength of a connection between two vertices, e.g. if Vertex A connects to Vertex B in five edges, then the Edge Weight is 5.
Edge Color: Edge weight
This value determines the color of each edge. A common value for coloring edges is Edge Weight.
Edge Width: Edge weight
This value determines the width of each edge. A common value for coloring edges is Edge Weight.
Edge Alpha: Edge Weight
This value determines the transparency / opacity of each edge. A common value for coloring edges is Edge Weight.
This value determines the size of each vertex. Common values to size the vertices are Betweenness Centrality, In-Degree and Out-Degree.
Below you find explanations of the different sections of a network report page in NodeXL Graph Gallery.
Top users ranked by a network score calculated based on the person’s connection to otherwise disconnected groups of people. “Betweenness” is the “Bridge Score” that measures how much a person is the only way to connect from one part of the network to another. It is a sociological proxy for “influence”. It is different from other “social media reputation” scores in that it is local and bounded: It finds the people other people find valuable within a particular topic during a particular time. This is in contrast to “global” reputation scores that claim to capture the value of a person in all possible contexts with a single value. In contrast, local and bounded reputation is timely and specific to a selected topic or issue. This score does NOT use follower count, tweet count, or retweet count as an input. It is based on the behavior of other people towards a user to determine their value.
Top URLs mentioned in the data ranked by frequency along with the raw count. This highlights relevant web resources, and when the top URLs in each of the groups are compared, this reveals the differences between segments of the network based on different patterns of URLs mentioned. The report provides a breakout for each of the top ten groups. These patterns are a fingerprint of what this group cares about.
Top domains extracted from the top URLs, reveal the web sites (rather than specific pages) that are most frequently mentioned. This can be used to identify the websites where organic or paid content might best be placed.
Top hashtags that co-occur with this search term ranked by frequency of mention reported along with the raw count of mentions.
Ranked and sentiment analyzed list of words that appear in the Tweets in this dataset (after a list of “stop” or “skip” words is removed). NodeXL has a sentiment feature that categorizes words into three lists (which can be configured by the user). By default we report “Positive”, “Negative”, and “Angry” words.
Top Word Pairs
Ranked list of pairs of words that appear next to one another with the greatest frequency (after a list of “stop” or “skip” words is removed) reported along with the raw count of their appearance.
Top users ranked by how often their usernames appeared in the first part of a collected set of tweets (excluding the times their username appeared elsewhere in a message, which is classified as a mention instead).
Top users ranked by how often their usernames appeared in the collected set of tweets (excluding the times their username started a message, which is classified as a reply instead).
Top users ranked by how many times they have ever tweeted as reported in their profile. Often these are spam or low value accounts, they are included here to contrast with the set of users identified in the Top Influencers report.