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One Day in the Life of a National Twittersphere

Axel Bruns
Axel Bruns
 and 
Brenda Moon
Brenda Moon
   | Jun 28, 2019
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Published Online: Jun 28, 2019
Page range: 11 - 30
DOI: https://doi.org/10.2478/nor-2019-0011
Keywords
© 2019 Axel Bruns et al., published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Figure 1

Follower–followee network among the best-connected accounts in the Australian TwittersphereComment: Selected clusters labelled according to their thematic focus (reproduced from Bruns et al., 2017)
Follower–followee network among the best-connected accounts in the Australian TwittersphereComment: Selected clusters labelled according to their thematic focus (reproduced from Bruns et al., 2017)

Figure 2a

Tweets and unique accounts per hourSource: TrISMA (Bruns et al., 2016).
Tweets and unique accounts per hourSource: TrISMA (Bruns et al., 2016).

Figure 2b

Tweet types and hashtagged tweets per hourSource: TrISMA (Bruns et al., 2016).
Tweet types and hashtagged tweets per hourSource: TrISMA (Bruns et al., 2016).

Figure 3

Tweets using one of the top 25 hashtags as a percentage of all the tweets using at least one such hashtagSource: TrISMA (Bruns et al., 2016).
Tweets using one of the top 25 hashtags as a percentage of all the tweets using at least one such hashtagSource: TrISMA (Bruns et al., 2016).

Figure 4

Network of @mention and retweet interactions for accounts with degree ≥10Comment: Force Atlas 2 algorithm, Louvain modularity detection (resolution 0.5). Selected clusters are labelled following qualitative interpretation.Source: TrISMA (Bruns et al., 2016).
Network of @mention and retweet interactions for accounts with degree ≥10Comment: Force Atlas 2 algorithm, Louvain modularity detection (resolution 0.5). Selected clusters are labelled following qualitative interpretation.Source: TrISMA (Bruns et al., 2016).

Figure 5

Tweeting activity by accounts in ten major interactivity network clusters over the course of the daySource: TrISMA (Bruns et al., 2016).
Tweeting activity by accounts in ten major interactivity network clusters over the course of the daySource: TrISMA (Bruns et al., 2016).

Distribution of tweeting activity across different tweet types and styles, 22 March 2017

Tweets Percentage of tweets Unique accounts Percentage of accounts
Total 1,294,569 100 176,737 100
Original tweets 427,537 33 101,785 58
@mentions 422,895 33 93,260 53
Retweets 555,003 43 88,752 50
Hashtag 301,405 23 72,672 41
No hashtag 993,164 77 104,065 59
URL 695,282 54 136,599 77
No URL 599,287 46 40,138 22
Twitter.com URL 365,995 28 84,263 48
Non-Twitter.com URL 369,177 29 90,044 51

Key metrics for selected clusters in the interaction network

Cluster Active accounts Tweets Hashtagged Original @mentions Retweets URL tweets
Phatic sharing 2,440 88,912 5% 23% 25% 56% 48%
Australian politics 1,663 67,493 35% 13% 37% 71% 47%
Right-wing politics 1,067 38,023 23% 14% 43% 57% 48%
Progressive netizens 963 24,844 10% 23% 51% 33% 37%
US politics 941 34,001 22% 12% 32% 69% 53%
Teen culture 938 36,606 14% 20% 39% 53% 48%
Health and indigenous 611 11,966 40% 17% 38% 65% 55%
Energy and environment 597 10,733 44% 16% 44% 59% 56%
Science 493 8,090 48% 16% 56% 56% 55%
eISSN:
2001-5119
Language:
English
Publication timeframe:
2 times per year
Journal Subjects:
Social Sciences, Communication Science, Mass Communication, Public and Political Communication
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