HRTech Twitter NodeXL SNA Map and Report

HRtech Twitter NodeXL SNA Map and Report for Sunday, 15 November 2015 at 22:50 UTC

HRTech Twitter NodeXL SNA Map and Report

Sunday, 15 November 2015 at 22:50 UTC

View an interactive version of this graph (experimental)

From: marc_smith
Uploaded on: November 15, 2015

Short Description:

HRTech via NodeXL http://bit.ly/1OMA1HN
@hrtechworld
@talentculture
@pointnem0
@hivetechhr
@meghanmbiro
@glarocque
@hrtechweekly
@zenpeak

Description

The graph represents a network of 3,969 Twitter users whose tweets in the requested range contained HRTech, or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Sunday, 15 November 2015 at 22:54 UTC.

The requested start date was Sunday, 15 November 2015 at 14:50 UTC and the maximum number of tweets (going backward in time) was 10,000.

The tweets in the network were tweeted over the 19-day, 11-hour, 48-minute period from Monday, 26 October 2015 at 15:06 UTC to Sunday, 15 November 2015 at 02:54 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.

Overall Graph Metrics

Vertices : 3969
Unique Edges : 6153
Edges With Duplicates : 6591
Total Edges : 12744
Self-Loops : 4203
Reciprocated Vertex Pair Ratio : 0.0699900957411687
Reciprocated Edge Ratio : 0.130823819808701
Connected Components : 652
Single-Vertex Connected Components : 466
Maximum Vertices in a Connected Component : 2896
Maximum Edges in a Connected Component : 10960
Maximum Geodesic Distance (Diameter) : 12
Average Geodesic Distance : 4.929646
Graph Density : 0.000411581896796951
Modularity : 0.429463
NodeXL Version : 1.0.1.344

Top Influencers: Top 10 Vertices, Ranked by Betweenness Centrality

 

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