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COVID-19 Health Communication Networks on Twitter: Identifying Sources, Disseminators, and Brokers Cover

COVID-19 Health Communication Networks on Twitter: Identifying Sources, Disseminators, and Brokers

By: Ian Kim and  Thomas W. Valente  
Open Access
|Jan 2021

Figures & Tables

Figure 1:

Volume of #COVID19 tweets from April 13, 2020, 08:00:00 AM, to April 16, 2020, 07:59:59 AM, GMT (UTC +0), with 5 minutes time intervals.
Volume of #COVID19 tweets from April 13, 2020, 08:00:00 AM, to April 16, 2020, 07:59:59 AM, GMT (UTC +0), with 5 minutes time intervals.

Figure 2:

Toy networks: (a) retweet and mention networks; (b) information diffusion network; (c) influential user identification in the retweet and mention networks.
Toy networks: (a) retweet and mention networks; (b) information diffusion network; (c) influential user identification in the retweet and mention networks.

Figure 3:

Scale free in-degree and out-degree distributions on a log-log scale for retweet and mention networks.
Scale free in-degree and out-degree distributions on a log-log scale for retweet and mention networks.

Figure 4:

Graphs of the #COVID19 retweet and mention networks (April 13, 2020, 5–6 PM, GMT (UTC +0)).
Graphs of the #COVID19 retweet and mention networks (April 13, 2020, 5–6 PM, GMT (UTC +0)).

Centrality statistics for influential and all other users in both networks_

RetweetMention
Influential usersAll usersInfluential usersAll users
In-degreeN=100N=438,821N=100N=531,019
Mean2,6811.472,5601.43
SD2,68958.232,36448.13
Median1,50601,8150
Min.70507490
Max.11,95411,95411,60811,608
Skewness132.10140.25
Kurtosis21,154.4924,930.94
Out-degreeN=100N=438,821N=100N=531,019
Mean471.47621.43
SD231.78292.09
Median381521
Min.320390
Max.158158187187
Skewness12.4313.22
Kurtosis491.54537.58
BetweennessN=100N=438,821N=100N=531,019
Mean9,433,4712,894.6667,239,43416,452.62
SD7,976,886188,252.4058,763,8641,230,822
Median6,886,086040,851,6720
Min.2,728,657015,904,0900
Max.43,309,21343,309,213215,538,020215,538,020
Skewness123.89125.39
Kurtosis19,750.7017,758.65

P-values from Fisher’s exact test comparing occupations across user roles and between networks_

RetweetMentionRetweet vs. mention
123123123
1. Information sources<0.001<0.001<0.001<0.0010.6909
2. Information disseminators<0.001<0.0010.2707
3. Information brokers0.0630

Occupations of influential users in retweet and mention networks_

Information sources (N=100)Information disseminators (N=100)Information brokers (N=100)
Retweet
Health20Care providers16 (80.0%)3Care providers1 (33.3%)48Care providers29 (60.4%)
professionalsResearchers/Scientists4 (20.0%)Researchers/Scientists2 (66.7%)Researchers/Scientists19 (39.6%)
Communication16Media broadcasters3 (18.8%)18Media broadcasters13 (72.2%)13Media broadcasters4 (30.8%)
professionalsJournalists/Reporters13 (81.2%)Journalists/Reporters5 (27.8%)Journalists/Reporters9 (69.2%)
Government28Politicians/Policy makers23 (82.1%)3Politicians/Policy makers1 (33.3%)12Politicians/Policy makers6 (50.0%)
officialNational agencies5 (17.9%)National agencies2 (66.7%)National agencies6 (50.0%)
Non-professionals36Public figures29 (80.6%)76Public figures4 (5.3%)27Public figures6 (22.2%)
Ordinary Individuals7 (19.4%)Ordinary Individuals72 (94.7%)Ordinary Individuals21 (77.8%)
Mention
Health19Care providers16 (84.2%)5Care providers2 (40.0%)57Care providers22 (38.6%)
professionalsResearchers/Scientists3 (15.8%)Researchers/Scientists3 (60.0%)Researchers/Scientists35 (61.4%)
Communication18Media broadcasters4 (22.2%)17Media broadcasters13 (76.5%)15Media broadcasters6 (40.0%)
professionalsJournalists/Reporters14 (77.8%)Journalists/Reporters4 (23.5%)Journalists/Reporters9 (60.0%)
Government34Politicians/Policy makers29 (85.3%)9Politicians/Policy makers4 (44.4%)16Politicians/Policy makers6 (37.5%)
officialNational agencies5 (14.7%)National agencies5 (55.6%)National agencies10 (62.5%)
Non-professionals29Public figures25 (86.2%)69Public figures5 (7.2%)12Public figures8 (66.7%)
Ordinary individuals4 (13.8%)Ordinary individuals64 (92.8%)Ordinary individuals4 (33.3%)

Network metrics for the retweet and mention networks_

Network
RetweetMention
Number of nodes438,821531,019
Number of edges (directed)646,183758,313
Diameter (largest connected component)3546
Average path length12.0916.58
Reciprocity0.0026780.004815
Transitivity0.0001610.000182
Number of clusters12,51928,528
Average clustering coefficient0.0120.008
Modularity0.7820.797
Density< 0.001< 0.001
DOI: https://doi.org/10.21307/connections-2019.018 | Journal eISSN: 2816-4245 | Journal ISSN: 0226-1766
Language: English
Page range: 129 - 142
Published on: Jan 5, 2021
Published by: International Network for Social Network Analysis (INSNA)
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2021 Ian Kim, Thomas W. Valente, published by International Network for Social Network Analysis (INSNA)
This work is licensed under the Creative Commons Attribution 4.0 License.