The graph represents a network of 4,071 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, 14 June 2021 at 05:18 UTC.
The requested start date was Monday, 14 June 2021 at 00:01 UTC and the maximum number of days (going backward) was 14.
The maximum number of tweets collected was 7,500.
The tweets in the network were tweeted over the 9-day, 3-hour, 0-minute period from Friday, 04 June 2021 at 08:14 UTC to Sunday, 13 June 2021 at 11:15 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 : 4071
Unique Edges : 4547
Edges With Duplicates : 25606
Total Edges : 30153
Number of Edge Types : 5
Mentions : 9917
Replies to : 360
Tweet : 1250
Retweet : 5059
MentionsInRetweet : 13567
Self-Loops : 1286
Reciprocated Vertex Pair Ratio : 0.0386535261743248
Reciprocated Edge Ratio : 0.074430067775724
Connected Components : 243
Single-Vertex Connected Components : 115
Maximum Vertices in a Connected Component : 3453
Maximum Edges in a Connected Component : 29200
Maximum Geodesic Distance (Diameter) : 11
Average Geodesic Distance : 3.870472
Graph Density : 0.000489770939291941
Modularity : 0.233515
NodeXL Version : 1.0.1.445
Data Import : The graph represents a network of 4,071 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, 14 June 2021 at 05:18 UTC.
The requested start date was Monday, 14 June 2021 at 00:01 UTC and the maximum number of days (going backward) was 14.
The maximum number of tweets collected was 7,500.
The tweets in the network were tweeted over the 9-day, 3-hour, 0-minute period from Friday, 04 June 2021 at 08:14 UTC to Sunday, 13 June 2021 at 11:15 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 Entire Graph:
[1165] cdcgov,cdctravel [1137] cdcdirector,cdc_ehealth [1136] cdctravel,cdcdirector [1126] #loveisnottourism,cdcgov [1031] cdc_ehealth,whcovidresponse [601] whcovidresponse,aslavitt46 [540] aslavitt46,aslavitt [432] open,visitors [432] visitors,negative [432] negative,vaxxed Top Word Pairs in Tweet in G1:
[284] mashable,enricomolinari [280] biozhena,files [238] files,downloads [230] seguimiento,#ehealth [227] wef,enricomolinari [222] enricomolinari,#ehealth [214] #ehealth,#health [186] #impinv,#vc [156] add'l,biozhena [139] #finserv,#insurtech Top Word Pairs in Tweet in G2:
[1165] cdcgov,cdctravel [1137] cdcdirector,cdc_ehealth [1136] cdctravel,cdcdirector [1126] #loveisnottourism,cdcgov [1031] cdc_ehealth,whcovidresponse [601] whcovidresponse,aslavitt46 [540] aslavitt46,aslavitt [432] open,visitors [432] visitors,negative [432] negative,vaxxed Top Word Pairs in Tweet in G3:
[17] ehealth,innovation [17] innovation,summit [17] #ehealth,#innovation [17] #innovation,summit [12] funding,opportunities [10] join,dhe_2020 [10] dhe_2020,cei_secretariat [10] cei_secretariat,deep [10] deep,dive [10] dive,funding Top Word Pairs in Tweet in G4:
[84] matt,anderson [65] ehealth,ontario [53] ontario,lost [48] behind,ehealth [48] ontario,scandal [47] uoft_dlsph,ontariohealthoh [46] anderson,behind [46] scandal,ontario [42] lost,billion [38] billion,aldasteinn Top Word Pairs in Tweet in G5:
[10] digital,health [9] 10,jahre [9] jahre,zank [9] zank,#epa [9] #epa,mal [9] mal,#röntgenbilder [9] #röntgenbilder,#ct [9] #ct,speichern [9] speichern,der_knoche [9] der_knoche,derlummer Top Word Pairs in Tweet in G6:
[18] bbcworld,bbchindi [15] cnn,cnni [13] narendramodi,narendramodi_in [12] e_health_,ehealth [12] #corruption_free,#india [12] #india,letter [12] letter,pmoindia [12] pmoindia,two [12] two,years [12] years,ago Top Word Pairs in Tweet in G7:
[73] taking,india [73] india,ehealth [73] ehealth,journey [73] journey,forward [73] forward,esanjeevani [67] esanjeevani,touches [67] touches,milestone [67] milestone,60 [67] 60,lakh [67] lakh,tele Top Word Pairs in Tweet in G8:
[10] ehealth,inc [7] #ehealth,#health [6] ehealth,literacy [6] administrateur,generaal [5] digital,health [5] tata,digital [5] majority,stake [5] ehth,insider [5] insider,filing [5] filing,ehealth Top Word Pairs in Tweet in G9:
[62] markcrypto23,aimedis [57] app,store [56] aimedis,making [56] making,ehealth [56] ehealth,secure [56] secure,affordable [56] affordable,accessible [56] accessible,worldwide [56] worldwide,app [56] app,available Top Word Pairs in Tweet in G10:
[13] review,identified [13] identified,36 [13] 36,theories [13] theories,used [13] used,explain [13] explain,#implementation [13] #implementation,approaches [13] approaches,#ehealth [13] #ehealth,commonly [13] commonly,used Top Replied-To in Entire Graph:
Top Replied-To in G1:
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Top Replied-To in G10:
Top Mentioned in Entire Graph:
Top Mentioned in G1:
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Top Tweeters in Entire Graph:
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Top Tweeters in G5:
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Top Tweeters in G10: