Index
Jingrong Tong
(Brunel University London, UK)
Landong Zuo
(IT Solution Architect, UK)
Tweeting the Environment #Brexit
ISBN: 978-1-78756-502-9, eISBN: 978-1-78756-499-2
Publication date: 8 October 2018
This content is currently only available as a PDF
Citation
Tong, J. and Zuo, L. (2018), "Index", Tweeting the Environment #Brexit, Emerald Publishing Limited, Leeds, pp. 189-198. https://doi.org/10.1108/978-1-78756-499-220181015
Publisher
:Emerald Publishing Limited
Copyright © 2018 Jingrong Tong and Landong Zuo
INDEX
Administrative rationalism environmentalism
, 36, 61
Advocacy campaigns on Twitter
, 30
Amazon Elastic Compute Cloud
, 152
@Amelia_Womack
, 44, 78, 101, 105, 108, 114
@Another_Europe
, 40, 43, 105
Anti-Brexit accounts
, 43, 91, 105, 113
API. See Application Programming Interface (API)
Application Programming Interface (API)
, 4
Asymmetrical Twitter space, elite domination in
asymmetric structure
, 70–74
attention-driven prominence of elites
, 81–83
decentralisation and anarchy on
, 74–81
Attention-based retweeting networks
, 72, 109
Attention-influenced discursive arguments
, 112–113
@Avaaz
, 51, 53
AWS-EC2
, 152
@BBCHARDtalk
, 79, 103
@BBCNews
, 79, 103, 105, 124
@BBCRealityCheck
, 79, 103–104
Betweenness centrality scores
, 89, 92–94, 104
Big data
, 5, 7–8, 151–153
Big social media data
, 7, 146, 147, 149–150, 160
@BirdLifeEurope
, 78, 120–121
@BorisJohnson
, 43, 48, 78, 100, 108, 116–118
Brexit
and of Brexiteers’ immigration concerns
, 47–48
on British environmental policies
, 61
campaign
, 122
environmental benefits
, 117, 127
environmental impacts and implications
, 47, 54–61
Brexiteers
arguments
, 48
climate deniers and
, 122
immigration concerns
, 47
Remainers and
, 65, 133
Bridging nodes
, 81, 94, 102, 109–110
Campaign-oriented tweeting strategies
, 113
@CarolineLucas
, 41, 44, 50, 56–57, 64, 75, 78, 86, 99–102, 108, 116–117
@ClimateHome
, 56, 75, 79, 97, 122
Climate Home News
, 122–123
@ClimateRetweet
, 72, 75, 79, 92–93
Clustering coefficient values
, 94
Communities
, 133
green camps
, 100–102
interactions and information flow
, 99–100
loosely connected or isolated communities
, 97–99
sparse communities
, 91–97
Computational multi-method analysis
, 154
Computer scientists and social scientists
, 159
Connected clusters
, 98, 103
Conservatism
, 20
Conservative Party
, 21, 32, 113–115, 117–118, 133, 137
Content words
, 39, 53–55, 154
Continuously tweeting
, 49
Core egonets
, 72, 73, 86–87
of green camps
, 103
loosely connected or isolated communities
, 97–99
mixed-methods, data analysis
, 155–157
news media and journalists
, 103–107
and political parties
, 78–81
twitter communication, asymmetric structure of
, 72, 73
Corpus linguistic techniques
, 154
Daily Express
, 53
@Daily_Express
, 51, 79, 103–104, 123
Daily Mail
, 20
Daily Telegraph
, 20, 122
Data driven inductive approach
, 149
@David_Cameron
, 64, 78, 100, 108, 116, 117
Decentralisation and anarchy on Twitter
core egonets and political parties
, 78–80
influential nodes
, 77
lack of persistence
, 77
news media, politicians, political parties and ENGOs
, 78–79
political parties
, 77
retweeting networks
, 77
tweets trends
, 74, 76
users attention
, 81
Deductive and inductive, methodological approaches
, 146–147
Degree
, 72, 89–90
Department for the Environment, Food and Rural Affairs (DEFRA)
, 24
@DesmogUK
, 122
Digital ethnography
, 149
Digital humanity study, mapping
, 88
Discourses
dichotomised claims in pre-referendum
, 37–49
dominant claims
, 49–54
environmental topics, concerns on
, 63–64
popular (retweeted) users
, 50–52
post-referendum
, 54–63
Dobson’s ecological citizenship concept
, 16–17
@DrJillStein
, 78, 101, 108
Ecological citizenship
, 16, 134–135
Ecological footprints
, 16
@EdinburghGreens
, 81
Egonets
, 10, 72, 74, 78, 80, 83, 86, 87, 94–97, 100–109, 156
ElasticSearch
, 7, 39, 152–154, 156
Elite groups
, 77, 81, 83, 101, 107, 135, 139
‘Energy bills/costs’ argument
, 49
@Energydesk
, 57, 61, 75, 77, 78, 97, 108, 120
ENGOs camp
, 119–123
See also Environmental Nongovernment Groups (ENGOs)
Environmental communication on social media
, 2
Environmental data
, 5–6
Environmentalism
, 20, 36, 61, 65, 140
Environmental mobilisation
, 119
Environmental Nongovernment Groups (ENGOs)
, 2, 8, 32
associates and environmental online media
, 86
environmental politics
, 132–133
Environmental online media source
, 72, 94
Environmental politics
awareness and politicisation in UK
, 17–23
in Britain
, 134
global rise of
, 13–17
immersed in social media
, 140–144
old and new players
, 139–140
shared affordances
, 131–133
social constructivist approach
, 132
social context, influence of
, 132–135
technological affordances
, 135–139
Twitter in public participation
, 132
UK’S EU membership
, 23–24
Environmental revolution
, 14
Environmental topics, concerns on
, 63–64, 120, 154
Environmental tweets
, 5, 6, 36, 37, 39, 49, 53, 55, 63, 70, 74, 86, 89, 101, 103, 122–123
Excel
, 152–154
@FoEScot
, 78, 121
Fragility
, 141
Framing and sentiment analysis
, 150
Full egonets
, 72, 94, 101, 103, 107, 156
@GdnPolitics
, 44, 79, 103–104, 123
Gephi
, 7, 152–153, 156
Global civic movement organisation
, 49, 53
Global public environmental awareness
Dobson’s ecological citizenship concept
, 16–17
ecological citizenship
, 16
ENGOs
, 15
environmental revolution
, 14
green consumerism
, 14
greenfreeze refrigerator
, 15
Green Party movement
, 14–15
media campaigns
, 15
political and policy agendas
, 14
trans-boundary pure environmental perspectives
, 17
Western Europe
, 14
Government surveillance disclosures
, 88
Graph density and clustering coefficient
, 89
@Greens4Animals
, 102
Green camps
, 103
bridging nodes
, 102
ENGOs camp
, 102
Green Party
, 101–102
political parties, core egonets of
, 102
Green consumerism
, 14
‘Green decision of a lifetime’
, 41, 46–49, 77, 116
Greenfreeze refrigerator
, 15
@GreenKeithMEP
, 64, 78, 86, 101, 102, 103, 108, 109, 114, 116
@GreenLibDems
, 115–116, 118
Green Party
, 2, 8, 21, 30–32, 47
camp
, 114
environmental politics
, 132–133
and its associates
, 86, 114
movement
, 14–15
theme
, 115
tweets and arguments
, 46
Greenpeace
, 8, 15, 32, 97–99, 120
Green politicians
, 107–110, 115–117
@GreensEP
, 81
the Guardian
, 20, 22, 103–105, 123, 125
@guardian
, 79, 103, 105, 124
@guardianeco
, 79, 105, 123
@GuardianSustBiz
, 79, 105, 123
Hashtags
, 4, 31, 152, 154
Immigration
, 1, 5, 9, 22, 37, 46, 47
In-degree
, 89–90
Indicating words
, 39–40, 53, 55
Influential nodes
, 77–78, 103
Influential social actors
, 153–154
categories
, 125–127
ENGOs camp
, 119–123
loosely connected or isolated communities
, 97–99
news media and journalists
, 123–125
political parties and politicians
, 113–119
social network analysis (SNA)
, 91
Information flow characteristics
, 153
Isolated nodes
, 99, 103
Isolated single nodes
, 97
@iVoteStay
, 72, 75, 93
@jeremycorbyn
, 50, 78, 100, 108, 116–118
Kibana
, 7, 152–154, 156
Laboratory for Energy and the Environment (LFEE)
, 18–19
Labour Party
, 9, 21, 32, 113–115, 117–118, 127, 137
@lboroCRCC
, 103
Liberal Democrats
, 21, 32, 113–114, 115, 133, 137
Liberalism
, 20
Literature, social media research
, 157–158
Loosely connected or isolated communities
connected clusters
, 98
core egonets
, 97–99
influential social actors
, 98
isolated single nodes
, 97
retweeting connections
, 97
@LouiseBoursUKIP
, 49, 78, 113, 116, 117–118
Low density community-clusters
, 109
Low-density networks
, 90, 109
Machine learning techniques
, 150
Major cluster
, 98, 103
Manual coding and computational analysis
, 154
Media ecology
, 25–27
Media-mediated communication
, 30
Mediated political communication
, 69
Mixed-methods, data analysis
computer applications
, 157
computer tools
, 156
core egonets
, 156–157
data conversion
, 156
inductive reasoning
, 157
multi-dimensional features
, 155
in SNA
, 156–157
@MollyMEP
, 81, 86, 92, 97, 102–103, 105, 108, 109, 115
Monthly active users (MAUs)
, 25–26
@natalieben
, 41, 46, 64, 77, 78, 86, 101–102, 108, 109, 116
National-interest-driven environmental discourses
, 143
Networked listeners
, 88
News media and journalists
betweenness centrality scores
, 104
core egonets
, 103–106
environmental organisation
, 105
green camps
, 103
the Guardian
, 103–104
influential social actors
, 123–125
isolated nodes
, 103
major cluster
, 103
Obama campaign in 2008
, 26
Observer
, 22
Office for National Statistics (ONS)
, 19
Offline reality
, 140–144
Offline referendum campaign
, 65
Online activism
, 51, 141
Ontological drift
, 149, 159
Original statements and retweeted tweets
, 70–71
Out-degree
, 89–90, 94
Political commentators and bloggers
, 88
Political mobilisation
, 119, 121
Political parties and non-green politicians
, 107–108
Popularity and activity level
, 70
‘Post-cosmopolitan’ citizenship
, 16
Post-referendum discourse
, 54–63
Pre-referendum discourses, dichotomised claims in
Brexit and of Brexiteers’ immigration concerns
, 47–48
content words
, 39
continuously tweeting
, 49
Elasticsearch
, 39
‘energy bills/costs’ argument
, 49
environmental corporation
, 47
environmental issues and immigration
, 46–47
funding and regulations
, 40
green decision of a lifetime
, 48
Green Party
, 47
Green Party’s tweets and arguments
, 46
indicating words
, 39–40
materialist claims
, 48
popular users
, 40–45
referendum campaign
, 48
Remainers’ arguments
, 46
themes types
, 37–40
transnational environmental concerns
, 40–46
Public discourses on social media
, 112
Public domain, tweets published in
, 155
Public participation and communication
, 143
Rationalism environmentalism
, 61
Referendum campaign
, 48
economy and migration in
, 3
energy bills in
, 48
offline
, 65
Twitter during
, 3–4, 114
Referendum day, dominant claims of remain
Brexit to natural disasters
, 54
content words
, 54
global civic movement organisation
, 53
popular (retweeted) users
, 49–52
themes
, 53
Remainers
arguments
, 46
and Brexiteers
, 65, 133
Retweeting
, 4, 10, 72, 100, 112, 122
connections
, 97
networks
, 77, 86, 105, 109
relationship
, 89, 114
Royal Society for Protection of Birds (RSPB)
, 15, 124
@SadiqKhan
, 52, 78
Scottish National Party (SNP)
, 113, 115, 118, 133, 137
Shared affordances
, 131–133
@SkyNewsBreak
, 79, 103, 105, 123
Social actors, relationships and interactions
, 87–88
Social media
communication
, 1–2, 140–144
and public discourses
, 112
Social media research
inductive approach, advantages and limitations
, 158–160
literature
, 158
methodological challenges
, 145–151
mixed-methods and computational applications
, 155–157
process
, 151–155
Social network analysis (SNA)
, 153–154
campaigns formation
, 88
communities, See Communities
degree
, 89–90
graph density and clustering coefficient
, 89
influential social actors
, 91
news media and journalists
, 103–107
political parties and non-green politicians
, 107–108
‘retweeting’ relationship
, 89
social actors, relationships and interactions
, 87–88
of social media
, 87–90
Spam campaign detecting study
, 88
Sparse communities
betweenness centrality score
, 94
clustering coefficient values
, 94
egonets
, 94–97
environmental online media source
, 94
networks
, 91–94
SPSS
, 7, 152–153
Strong ties
, 90
Swiss “nuclear withdrawal initiative”
, 88
Technical barriers
, 146, 159
Technological affordances
asymmetrical Twitter communication
, 135
attention-based control
, 136
digital divides
, 135, 138
inequalities in attention
, 137
legitimacy of expression
, 136–138
overall national-interest-driven discourse
, 138
retweeting networked communities
, 137
symbolic capital
, 136–137
users attention
, 135
@TelePolitics
, 79, 103, 105, 123–124
@TheGreenParty
, 41, 46–47, 75, 77–79, 81, 92, 100, 114, 116
Total taxes and social contributions (TTSC)
, 19
Traditional news media
, 25, 27, 62, 103, 111–112
Traditional political communication
, 69, 140
Traditional social science research
, 146–148
Transnational ecological citizenship
, 134–135
Tweets trends
, 74, 76
Twitter
advocacy campaigns on
, 30
Application Programming Interface (API)
, 4
Australian flood crises in 2010 and 2011
, 88
for certain purposes
, 88
communication studies
, 27–29
competing site
, 113
decentralisation and anarchy on
, 74–81
environmental communication on
, 29–32
Gezi Park protests in Turkey
, 88
hashtags
, 4
internet- or mobile-based
, 26
media ecology
, 27
old and new players
, 139–140
Pakistan floods
, 88
during referendum campaign
, 3–4
technical features
, 133
topic networks
, 88
Twitter4j
, 152
Twitter communication, asymmetric structure of
active and popular users
, 74–75
active user
, 72
attention-based retweeting networks
, 72
core egonets
, 72, 73
degree
, 72
full egonets
, 72
original statements and retweeted tweets
, 70–71
popularity and activity level
, 70
users types
, 73
UK green taxes
, 20
UK Independence Party (UKIP)
, 113–114, 118
Users
active and popular
, 74–75, 83
attention
, 81
frequently mentioned
, 81–83
types
, 73
@vote_leave
, 43, 45, 48
@Vote-LeaveMedia
, 43, 48
Weak ties
, 90, 108
Web 2.0
, 26
@WhyToVoteGreen
, 44, 51, 75, 77, 92–93, 105, 108
Wildlife Trusts
, 121–122
@WildlifeTrusts
, 40, 41, 50, 56, 70, 74, 75, 77, 78, 92, 93, 120
@wwwfoecouk
, 75, 77, 78, 102, 103, 108, 109, 121
- Prelims
- Chapter 1 Introduction
- Part 1
- Chapter 2 The Environment and Politics
- Chapter 3 Twitter, the Media Ecology and Environmental Communication
- Part 2
- Chapter 4 Environmental Discourses on Twitter
- Chapter 5 Elite Domination in the Asymmetrical Twitter Space
- Chapter 6 Sparse ‘Communities’ and Their Green Bridges in Twitter Networks
- Chapter 7 Influential Social Actors: Competing for Discourses on Twitter
- Part 3
- Chapter 8 Twitter and Environmental Politics
- Chapter 9 Social Media Research: Towards an Inductive Approach
- Bibliography
- Index