The graph represents a network of 1,785 Twitter users whose recent tweets contained "mhealth", or who were replied to, mentioned, retweeted or quoted in those tweets, taken from a data set limited to a maximum of 5,000 tweets, tweeted between 3/26/2006 12:00:00 AM and 2/5/2023 5:00:35 PM. The network was obtained from Twitter on Monday, 06 February 2023 at 03:03 UTC.
The tweets in the network were tweeted over the 1849-day, 20-hour, 34-minute period from Saturday, 13 January 2018 at 04:18 UTC to Monday, 06 February 2023 at 00:53 UTC.
There is an edge for each "replies-to" relationship in a tweet, an edge for each "mentions" relationship in a tweet, an edge for each "retweet" relationship in a tweet, an edge for each "quote" relationship in a tweet, an edge for each "mention in retweet" relationship in a tweet, an edge for each "mention in reply-to" relationship in a tweet, an edge for each "mention in quote" relationship in a tweet, an edge for each "mention in quote reply-to" relationship in a tweet, and a self-loop edge for each tweet that is not from above.
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 : 1785
Unique Edges : 1562
Edges With Duplicates : 9891
Total Edges : 11453
Number of Edge Types : 9
Tweet : 1213
Retweet : 3107
MentionsInRetweet : 4783
Mentions : 1640
MentionsInQuote : 139
Quote : 59
Replies to : 140
MentionsInReplyTo : 369
MentionsInQuoteReply : 3
Self-Loops : 1860
Reciprocated Vertex Pair Ratio : 0.0511363636363636
Reciprocated Edge Ratio : 0.0972972972972973
Connected Components : 173
Single-Vertex Connected Components : 81
Maximum Vertices in a Connected Component : 1331
Maximum Edges in a Connected Component : 10531
Maximum Geodesic Distance (Diameter) : 9
Average Geodesic Distance : 4.180349
Graph Density : 0.000871424803105099
Modularity : 0.212219
NodeXL Version : 1.0.1.510
Data Import : The graph represents a network of 1,785 Twitter users whose recent tweets contained "mhealth", or who were replied to, mentioned, retweeted or quoted in those tweets, taken from a data set limited to a maximum of 5,000 tweets, tweeted between 3/26/2006 12:00:00 AM and 2/5/2023 5:00:35 PM. The network was obtained from Twitter on Monday, 06 February 2023 at 03:03 UTC.
The tweets in the network were tweeted over the 1849-day, 20-hour, 34-minute period from Saturday, 13 January 2018 at 04:18 UTC to Monday, 06 February 2023 at 00:53 UTC.
There is an edge for each "replies-to" relationship in a tweet, an edge for each "mentions" relationship in a tweet, an edge for each "retweet" relationship in a tweet, an edge for each "quote" relationship in a tweet, an edge for each "mention in retweet" relationship in a tweet, an edge for each "mention in reply-to" relationship in a tweet, an edge for each "mention in quote" relationship in a tweet, an edge for each "mention in quote reply-to" relationship in a tweet, and a self-loop edge for each tweet that is not from above.
Layout Algorithm : The graph was laid out using the Harel-Koren Fast Multiscale layout algorithm.
Graph Source : TwitterSearch2
Graph Term : mhealth
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:
[932] #digitalhealth,#socialmedia [474] #socialmedia,#digitalmarketing [317] digital,health [288] #ehealth,#mhealth [250] gt,gt [245] #digitalhealth,#wearables [226] #wearables,series [224] series,wearablesexpert [196] #telehealth,#telemedicine [180] #digitalhealth,#ehealth Top Word Pairs in Tweet in G1:
[210] #ehealth,#mhealth [190] #digitalhealth,#wearables [174] #wearables,series [172] series,wearablesexpert [171] digital,health [164] #telehealth,#telemedicine [162] #digitalhealth,#socialmedia [144] #digitalhealth,#ehealth [123] #mhealth,#telehealth [69] #mhealth,#ehealth Top Word Pairs in Tweet in G2:
[106] #digitalhealth,#socialmedia [56] gt,gt [55] #ehealth,#mhealth [55] digital,health [52] #digitalhealth,#wearables [50] #mhealth,#hcsm [49] series,wearablesexpert [49] #mhealth,#digitalhealth [49] #wearables,series [33] #socialmedia,#digitalmarketing Top Word Pairs in Tweet in G3:
[660] #digitalhealth,#socialmedia [389] #socialmedia,#digitalmarketing [152] gt,gt [78] #digitalmarketing,#ai [72] #iot,#industry40 [69] #iot,#healthtech [69] #ai,#iot [66] #ai,#mhealth [64] #digitalmarketing,#iot [63] #healthtech,#mhealth Top Word Pairs in Tweet in G4:
[149] consalud_es,sbr [149] xa,consalud_es [107] gracias,leer [93] #mhealth,gracias [80] #saludmental,#mhealth [77] alerta,co [77] primera,alerta [77] sbr,#saludmental [48] dralfonsovidal,primera [37] #mhealth,#ia Top Word Pairs in Tweet in G5:
[27] digital,health [12] mobile,health [9] mhealth,market [7] health,mhealth [6] monitoring,devices [6] devices,market [6] mhealth,intervention [5] asia,pacific [5] market,research [5] mhealth,apps Top Word Pairs in Tweet in G6:
[25] latest,mhealth [25] daily,thanks [25] mhealth,daily [3] services,healthcare [3] know,more [3] enhance,#healthcare [3] #digitalhealth,#healthtech [3] #business,app [3] employ,services [3] developed,know Top Word Pairs in Tweet in G7:
[22] hoy,lista [22] gaceta,saludable [22] lista,gracias [22] saludable,hoy [19] iacta,disponible [19] alea,iacta [19] disponible,gracias [19] #lupus,#mhealth [11] #mhealth,#últimahora [10] #mhealth,#trauma Top Word Pairs in Tweet in G8:
[55] mental,health [55] technologies,black [55] excited,share [55] explores,culturally [55] health,technologies [55] black,young [55] adapt,mobile [55] culturally,adapt [55] paper,explores [55] share,paper Top Word Pairs in Tweet in G9:
[26] mhealth,advocate [26] latest,mhealth [25] advocate,thanks [21] #digitalhealth,#healthtech [8] thanks,caring_mobile [6] caring_mobile,#digitalhealth [4] #digitalhealth,#ehealth [3] health,weekly [3] daily,stories [3] mobile,health Top Word Pairs in Tweet in G10:
[7] negative,effects [7] antidepressants,people [7] first,offered [7] effects,drugs [7] people,told [7] told,potential [7] drugs,first [7] potential,negative [6] monyamyms,antidepressants [6] offered,#informedco Top Replied-To in Entire Graph:
Top Replied-To in G1:
Top Replied-To in G2:
Top Replied-To in G10:
Top Mentioned in Entire Graph:
Top Mentioned in G1:
Top Mentioned in G2:
Top Mentioned in G3:
Top Mentioned in G4:
Top Mentioned in G5:
Top Mentioned in G6:
Top Mentioned in G7:
Top Mentioned in G8:
Top Mentioned in G9:
Top Mentioned in G10:
Top Tweeters in Entire Graph:
Top Tweeters in G1:
Top Tweeters in G2:
Top Tweeters in G3:
Top Tweeters in G4:
Top Tweeters in G5:
Top Tweeters in G6:
Top Tweeters in G7:
Top Tweeters in G8:
Top Tweeters in G9:
Top Tweeters in G10: