The graph represents a network of 3,667 Twitter users whose tweets in the requested range contained "ehealth", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Monday, 08 June 2020 at 06:32 UTC.
The requested start date was Monday, 08 June 2020 at 00:01 UTC and the maximum number of days (going backward) was 14.
The maximum number of tweets collected was 5,000.
The tweets in the network were tweeted over the 5-day, 21-hour, 17-minute period from Monday, 01 June 2020 at 14:15 UTC to Sunday, 07 June 2020 at 11:33 UTC.
Additional tweets that were mentioned in this data set were also collected from prior time periods. These tweets may expand the complete time period of the data.
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.
Author Description
Vertices : 3667
Unique Edges : 4963
Edges With Duplicates : 10168
Total Edges : 15131
Number of Edge Types : 5
MentionsInRetweet : 5889
Mentions : 4558
Retweet : 3385
Tweet : 999
Replies to : 300
Self-Loops : 1055
Reciprocated Vertex Pair Ratio : 0.0283613445378151
Reciprocated Edge Ratio : 0.0551583248212462
Connected Components : 269
Single-Vertex Connected Components : 141
Maximum Vertices in a Connected Component : 3042
Maximum Edges in a Connected Component : 14163
Maximum Geodesic Distance (Diameter) : 11
Average Geodesic Distance : 4.312203
Graph Density : 0.000582598427668605
Modularity : 0.431238
NodeXL Version : 1.0.1.433
Data Import : The graph represents a network of 3,667 Twitter users whose tweets in the requested range contained "ehealth", or who were replied to or mentioned in those tweets. The network was obtained from the NodeXL Graph Server on Monday, 08 June 2020 at 06:32 UTC.
The requested start date was Monday, 08 June 2020 at 00:01 UTC and the maximum number of days (going backward) was 14.
The maximum number of tweets collected was 5,000.
The tweets in the network were tweeted over the 5-day, 21-hour, 17-minute period from Monday, 01 June 2020 at 14:15 UTC to Sunday, 07 June 2020 at 11:33 UTC.
Additional tweets that were mentioned in this data set were also collected from prior time periods. These tweets may expand the complete time period of the data.
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 : ehealth
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
Top Domains
Top Word Pairs in Tweet in G2:
[296] seguimiento,#ehealth [290] ty,wef [266] madurez,digital [196] wef,enricomolinari [192] ndice,madurez [165] #ehealth,#health [128] informes,médicos [120] digital,fenin_es [120] elaborar,informes [119] médicos,veces Top Word Pairs in Tweet in G3:
[90] cdcemergency,cdc_ehealth [47] cdcgov,cdc_ehealth [44] cdcgov,cdcemergency [41] cdc_ehealth,cdcdirector [33] cdc_ehealth,cdcflu [30] cdc_ehealth,cdcgov [28] corona,virus [27] ncdcgov,confirms [27] cdc_ehealth,cdcemergency [27] covid,19 Top Word Pairs in Tweet in G4:
[33] animation,medical [22] medical,sector [21] sector,brings [10] brings,clarity [8] clarity,efficiency [7] efficiency,safety [7] safety,security [7] security,bpo [6] bpo,service [6] service,providers Top Word Pairs in Tweet in G5:
[242] knsmoh,govumarganduje [242] ncdcgov,dawisu [242] dawisu,fmohnigeria [242] fmohnigeria,ehealth_africa [242] ncdcgov,fmohnigeria [242] govumarganduje,ncdcgov [242] govumarganduje,dr_tyw [242] ehealth_africa,whonigeria [242] whonigeria,ehealth_africa [242] abuhabeebb,tijjanihussai11 Top Word Pairs in Tweet in G6:
[102] ehealth,inc [89] class,action [89] inc,ehth [66] action,lawsuit [65] against,ehealth [57] reminds,investors [54] developer,ehealth [53] encourages,investors [45] lawsuit,against [44] ehealth,ehth Top Word Pairs in Tweet in G7:
[38] #ehealth,#digitalhealth [21] schöne,farben [19] farben,icons [15] folge,104 [13] 104,usability [13] usability,gesundheits [10] gesundheits,durchaus [10] durchaus,ähm [9] ähm,ausbaufähig [8] ausbaufähig,mehr Top Word Pairs in Tweet in G8:
[12] #5g,coverage [10] coverage,specialised [10] specialised,#healthcare [9] #healthcare,professionals [9] professionals,º [9] º,conduct [9] conduct,virtual [9] virtual,visits [9] visits,rural [9] rural,communities Top Word Pairs in Tweet in G9:
[18] #throwback,#magazine [18] magazine,url [18] url,download [18] download,url [18] #ehealth,#health [18] developer,ehealth [18] managing,director [18] ehealth,webinar [18] medrecord,offering [18] offering,#remotejob Top Word Pairs in Tweet in G10:
[13] digital,health [13] online,digital [11] health,world [11] world,congress [8] congress,2020 [8] 2020,virtual [8] virtual,conference [8] conference,june [7] june,22 [7] 22,23 Top Replied-To in Entire Graph:
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Top Mentioned in Entire Graph:
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Top Tweeters in Entire Graph:
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