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Spread of tweets in climate discussions: A case study of the 2019 Nobel Peace Prize announcement

Yan Xia

Yan Xia

Department of Computer Science, Aalto UniversityFinland
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Xia, Yan
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Ted Hsuan Yun Chen

Ted Hsuan Yun Chen

Department of Computer Science, Aalto University, Faculty of Social Sciences, University of Helsinki
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Chen, Ted Hsuan Yun
 y 
Mikko Kivelä

Mikko Kivelä

Department of Computer Science, Aalto UniversityFinland
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Kivelä, Mikko
  
06 jul 2021
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Publicado en línea: 06 jul 2021
Páginas: 96 - 117
DOI: https://doi.org/10.2478/njms-2021-0006
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© 2021 Yan Xia et al., published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Figure 1

Partitioned retweet networkComments: The partitioned retweet network of selected users and tweets, where the green bubble consists of 14, 812 users classified as climate activists, and the orange bubble consists of 5, 816 users classified as climate sceptics.
Partitioned retweet networkComments: The partitioned retweet network of selected users and tweets, where the green bubble consists of 14, 812 users classified as climate activists, and the orange bubble consists of 5, 816 users classified as climate sceptics.

Figure 2

Most characteristic words, activist and sceptic groupsComments: Most characteristic words among the top-500 retweeted tweets in the activist group (green) and the sceptic group (orange), ranked by the difference between word counts in the two groups. The bars of “change” and “climate”, with exceptionally large word counts, are truncated for visualisation purposes, but the actual word counts are attached in number to the right of the bars.
Most characteristic words, activist and sceptic groupsComments: Most characteristic words among the top-500 retweeted tweets in the activist group (green) and the sceptic group (orange), ranked by the difference between word counts in the two groups. The bars of “change” and “climate”, with exceptionally large word counts, are truncated for visualisation purposes, but the actual word counts are attached in number to the right of the bars.

Figure 3

Percentage of tweets labelled with each feature, activist and sceptic groups
Percentage of tweets labelled with each feature, activist and sceptic groups

Figure 4

Scatter plot of tweets with respect to number of retweeters in each group
Scatter plot of tweets with respect to number of retweeters in each group

Figure 5

Twitter's timeline algorithmComments: Different tweeting and retweeting scenarios and what appears on the follower's timeline. In both cases, additional retweeting beyond the source closest to the original tweet is not visible on the timeline.
Twitter's timeline algorithmComments: Different tweeting and retweeting scenarios and what appears on the follower's timeline. In both cases, additional retweeting beyond the source closest to the original tweet is not visible on the timeline.

Tweet features for coding

Feature Coding Rule
Universal (Style) Mocking Does the tweet make fun of an entity at its expense? (yes/no)
Incivility Does the tweet contain uncivil language? (yes/no)
Universal (Content) Call to Action Does the tweet call on others to behave in a certain way? (yes/no)
Ingroup Praise Does the tweet speak of the ingroup in a positive manner? (yes/no)
Outgroup Criticism Does the tweet speak of the outgroup in a negative manner? (yes/no)
Science Does the tweet invoke “science” or “facts” as support? (yes/no)
Hashtagsa Machine extracted count of hashtags used in the tweet.
Mentionsa Machine extracted count of users mentioned in the tweet.
Activists Solutions Does the tweet present solutions to addressing climate change? (yes/no)
Movement Does the tweet emphasise the strength of the pro-climate movement? (yes/no)
Sceptics Anti-international Does the tweet speak negatively of international organisations? (yes/no)
Hypocrisy Does the tweet claim that supporters are hypocritical or inconsistent? (yes/no)
Conspiracy Does the tweet claim that climate policy is a front for other agendas? (yes/no)

Effects of the explanatory variables on tweet virality, activist and sceptic groups

Explanatory variable Predicted change in virality (%)
Activist group (n = 261) Mocking 0.0
Call to Action 0.0
Ingroup Praise 0.9
Outgroup Criticism 1.5
Science −2.7
Movement 12.3
Solution 0.0
Hashtags 0.5
Mentions 1.7
Authors −32.3∼46.4
Sceptic group (n = 128) Mocking 0.0
Incivility 16.2
Call to Action 14.5
Ingroup Praise 0.0
Outgroup Criticism −7.9
Science 0.0
Anti-international 0.0
Hypocrisy 10.1
Conspiracy 0.0
Hashtags 1.6
Mentions 1.1
Authors −27.3∼26.5

Most- and least-viral tweet pairs in the sceptic group

User Most-viral tweet Least-viral tweet
S1a Virality score: 0.190[Incivility]I learned basic skills like sewing, cooking, woodwork, automobiles, and metalwork in high school home economics and shop classes :)Kids are now taught BS Socialism and Fake Climate Change... :/KAG Virality score: 0.037[Mocking]Thanks to California banning Plastic Straws... The Climate is becoming much better... It's only 45 today when it would have been 46... It's working... yay...
S2a Virality score: 0.118[Call to Action]Just one year ago, no political party would say:

Climate crisis is a hoax

Immigration is too high

Corporate welfare and supply management must be eliminated

The budget can be balanced within two years

 PPC is changing the conversation and bringing change along with it.#VotePPC		 Virality score: 0.044[Conspiracy, Outgroup Criticism]The network of globalist elites are all supporting each other. They promote fake climate change to scare people into submission. They are liars.
S3a Virality score: 0.113[Hypocrisy, Outgroup Criticism]Greens Sarah Hanson-Young: The government needs to declare a climate emergency!Also Sarah Hanson-Young: I have taken 58 flights this year with taxpayer money.Do as I say, not do as I do.[image] Virality score: 0.072[Outgroup Criticism]When will the Victoria police bill all these climate change protestors?[link]

Most- and least-viral tweet pairs in the activist group

User Most-viral tweet Least-viral tweet
A1 Virality score: 0.155[Movement]LOOK AT ALL THOSE PEOPLE marching in Alberta to demand #climateaction!Even here people want action on the #ClimateEmergency.Denying our situation doesn’t help.#ActOnClimate#ClimateStrike #FridaysforFutures #cdn-poli #climate #energy #elxn43 @GretaT-hunberg. Via @vineshpratap [video] Virality score: 0.035[Science, Call to Action]Air pollution is now more deadly than war, smoking and TB. It kills 7 million people every year.We have solutions to keep our communities safe and deal with the #climate crisis.Let's implement them. #GreenNewDeal #AirPollution #ClimateChange #energy #tech #PanelsNotPipelines [video]
A2a Virality score: 0.125[Ingroup Praise, Outgroup Criticism]Attacks on Thunberg is motivated by one thing. She is intelligent, eloquent, compassionate, and young. She has scared some hateful and reactionary so-called ‘grown ups’, #ActOnClimate #ClimateCrisis [link] Virality score: 0.035[Science]Climate change has rapidly and dramatically affected the arctic region. Even just ten years ago it was impossible for container ships to go through the Northern Sea Route. [link]
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