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

Ian Kim
Ian Kim
 y 
Thomas W. Valente
Thomas W. Valente
   | 05 ene 2021
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Publicado en línea: 05 ene 2021
Páginas: 129 - 142
DOI: https://doi.org/10.21307/connections-2019.018
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© 2020 Ian Kim et al., published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.

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
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