#FutureNursing_2021-01-13_05-55-42.xlsx (experimental version)

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From:

NodeXLExcelAutomator

Uploaded on:

January 13, 2021

Short Description:

#FutureNursing via NodeXL https://bit.ly/3icpjwk

@jimjam1306

@werglobalnurses

@westudentnurse

@thercn

@lesleybainbrid1

@150leaders

@nq_forum

@stnurseproject

@wenurses

Top hashtags:

Tweet
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@jimjam1306

@werglobalnurses

@westudentnurse

@thercn

@lesleybainbrid1

@150leaders

@nq_forum

@stnurseproject

@wenurses

Top hashtags:

Tweet

Description:

The graph represents a network of 9 Twitter users whose tweets in the requested range contained "#FutureNursing", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Wednesday, 13 January 2021 at 13:58 UTC.

The requested start date was Wednesday, 13 January 2021 at 01:01 UTC and the maximum number of tweets (going backward in time) was 7,500.

The tweets in the network were tweeted over the 0-minute period from Thursday, 10 December 2020 at 14:59 UTC to Thursday, 10 December 2020 at 14:59 UTC.

There is an edge for each "replies-to" relationship in a tweet, an edge for each "mentions" relationship in a tweet, and a self-loop edge for each tweet that is not a "replies-to" or "mentions".

The graph is directed.

The graph's vertices were grouped by cluster using the Clauset-Newman-Moore cluster algorithm.

The graph was laid out using the Harel-Koren Fast Multiscale layout algorithm.

The requested start date was Wednesday, 13 January 2021 at 01:01 UTC and the maximum number of tweets (going backward in time) was 7,500.

The tweets in the network were tweeted over the 0-minute period from Thursday, 10 December 2020 at 14:59 UTC to Thursday, 10 December 2020 at 14:59 UTC.

There is an edge for each "replies-to" relationship in a tweet, an edge for each "mentions" relationship in a tweet, and a self-loop edge for each tweet that is not a "replies-to" or "mentions".

The graph is directed.

The graph's vertices were grouped by cluster using the Clauset-Newman-Moore cluster algorithm.

The graph was laid out using the Harel-Koren Fast Multiscale layout algorithm.

Vertices : 9

Unique Edges : 8

Edges With Duplicates : 0

Total Edges : 8

Number of Edge Types : 2

Replies to : 1

Mentions : 7

Self-Loops : 0

Reciprocated Vertex Pair Ratio : 0

Reciprocated Edge Ratio : 0

Connected Components : 1

Single-Vertex Connected Components : 0

Maximum Vertices in a Connected Component : 9

Maximum Edges in a Connected Component : 8

Maximum Geodesic Distance (Diameter) : 2

Average Geodesic Distance : 1.580247

Graph Density : 0.111111111111111

Modularity : 0

NodeXL Version : 1.0.1.442

Data Import : The graph represents a network of 9 Twitter users whose tweets in the requested range contained "#FutureNursing", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Wednesday, 13 January 2021 at 13:58 UTC.

The requested start date was Wednesday, 13 January 2021 at 01:01 UTC and the maximum number of tweets (going backward in time) was 7,500.

The tweets in the network were tweeted over the 0-minute period from Thursday, 10 December 2020 at 14:59 UTC to Thursday, 10 December 2020 at 14:59 UTC.

There is an edge for each "replies-to" relationship in a tweet, an edge for each "mentions" relationship in a tweet, and a self-loop edge for each tweet that is not a "replies-to" or "mentions".

Layout Algorithm : The graph was laid out using the Harel-Koren Fast Multiscale layout algorithm.

Graph Source : GraphServerTwitterSearch

Graph Term : #FutureNursing

Groups : The graph's vertices were grouped by cluster using the Clauset-Newman-Moore cluster algorithm.

Edge Color : Edge Weight

Edge Width : Edge Weight

Edge Alpha : Edge Weight

Vertex Radius : Betweenness Centrality

Unique Edges : 8

Edges With Duplicates : 0

Total Edges : 8

Number of Edge Types : 2

Replies to : 1

Mentions : 7

Self-Loops : 0

Reciprocated Vertex Pair Ratio : 0

Reciprocated Edge Ratio : 0

Connected Components : 1

Single-Vertex Connected Components : 0

Maximum Vertices in a Connected Component : 9

Maximum Edges in a Connected Component : 8

Maximum Geodesic Distance (Diameter) : 2

Average Geodesic Distance : 1.580247

Graph Density : 0.111111111111111

Modularity : 0

NodeXL Version : 1.0.1.442

Data Import : The graph represents a network of 9 Twitter users whose tweets in the requested range contained "#FutureNursing", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Wednesday, 13 January 2021 at 13:58 UTC.

The requested start date was Wednesday, 13 January 2021 at 01:01 UTC and the maximum number of tweets (going backward in time) was 7,500.

The tweets in the network were tweeted over the 0-minute period from Thursday, 10 December 2020 at 14:59 UTC to Thursday, 10 December 2020 at 14:59 UTC.

There is an edge for each "replies-to" relationship in a tweet, an edge for each "mentions" relationship in a tweet, and a self-loop edge for each tweet that is not a "replies-to" or "mentions".

Layout Algorithm : The graph was laid out using the Harel-Koren Fast Multiscale layout algorithm.

Graph Source : GraphServerTwitterSearch

Graph Term : #FutureNursing

Groups : The graph's vertices were grouped by cluster using the Clauset-Newman-Moore cluster algorithm.

Edge Color : Edge Weight

Edge Width : Edge Weight

Edge Alpha : Edge Weight

Vertex Radius : Betweenness Centrality

@jimjam1306 | |

Follow |

@werglobalnurses | |

Follow |

@westudentnurse | |

Follow |

@thercn | |

Follow |

@lesleybainbrid1 | |

Follow |

@150leaders | |

Follow |

@nq_forum | |

Follow |

@stnurseproject | |

Follow |

@wenurses | |

Follow |

Top URLs in Tweet in Entire Graph:

[1] https://twitter.com/i/web/status/1337049350992695301

Top URLs in Tweet in G1:

[1] https://twitter.com/i/web/status/1337049350992695301

[1] https://twitter.com/i/web/status/1337049350992695301

Top URLs in Tweet in G1:

[1] https://twitter.com/i/web/status/1337049350992695301

Top Mentioned in Entire Graph:

Top Mentioned in G1:

@lesleybainbrid1 | ||

@werglobalnurses | ||

@westudentnurse | ||

@stnurseproject | ||

@wenurses | ||

@150leaders | ||

@nq_forum | ||

Top Mentioned in G1:

@lesleybainbrid1 | ||

@werglobalnurses | ||

@westudentnurse | ||

@stnurseproject | ||

@wenurses | ||

@150leaders | ||

@nq_forum | ||

Top Tweeters in Entire Graph:

Top Tweeters in G1:

@wenurses | ||

@thercn | ||

@stnurseproject | ||

@westudentnurse | ||

@werglobalnurses | ||

@150leaders | ||

@jimjam1306 | ||

@nq_forum | ||

@lesleybainbrid1 | ||

Top Tweeters in G1:

@wenurses | ||

@thercn | ||

@stnurseproject | ||

@westudentnurse | ||

@werglobalnurses | ||

@150leaders | ||

@jimjam1306 | ||

@nq_forum | ||

@lesleybainbrid1 | ||