Policy Agenda Setting and Twitter

253 Pages·2017·1.58 MB·English

Policy Agenda Setting and Twitter -
Three Cases from Canada
A Thesis
Submitted to the Faculty of Graduate Studies and Research
In Partial Fulfillment of the Requirements
For the Degree of
Doctor of Philosophy
in
Public Policy
By
Bruno Ryan Douglas Deschamps
Regina, Saskatchewan
March 27, 2017
Copyright 2017: B.R.D. Deschamps
UNIVERSITY OF REGINA

FACULTY OF GRADUATE STUDIES AND RESEARCH

SUPERVISORY AND EXAMINING COMMITTEE

Bruno-Ryan Douglas Deschamps, candidate for the degree of Doctor of Philosophy in Public
Policy, has presented a thesis titled, Policy Agenda Setting and Twitter - Three Cases
from Canada, in an oral examination held on March 7, 2017. The following committee
members have found the thesis acceptable in form and content, and that the candidate
demonstrated satisfactory knowledge of the subject material.

External Examiner: *Dr. Anatoliy Gruzd, Ryerson University

Supervisor: **Dr. Kathleen McNutt, Johnson Shoyama Graduate School of
Public Policy

Committee Member: Dr. Justin Longo, Johnson Shoyama Graduate School of
Public Policy

Committee Member: **Dr. Ken Rasmussen, Johnson Shoyama Graduate School of
Public Policy

Committee Member: **Dr. Peter Phillips, Johnson Shoyama Graduate School of
Public Policy, Adjunct

Chair of Defense: Dr. Paul Clarke, Faculty of Education

*Via Skype
**Via teleconference
Abstract
Social media sites are arenas for online collaboration, political controversy or, at times, mob
justice. These sites are also arenas for discussion about policy problems. Dramatic events,
amplified by Twitter, create an opportunity for citizens to support solutions to social
problems or to hold politicians to account for decisions made or not made. While media
portrays such events as transformative and heroic, most policy decisions have a historical
pedigree that is invisible to the public. By focussing on three cases of political discussion
on Twitter (Idle No More, Copyright, and Cyberbullying), this dissertation measures the
extent that policy theory explains the role of online networks on the policy process using a
social network analysis of Twitter users in communication with each other during notable
policy events. Areas of interest include the national or regional character of the discussion,
the role of actors with continued interest in the topic, changes to network demographics
from issue to issue, the influence of organizations, the formation of strongly connected
components in the network structure and the differences in structure between dramatic
events and government announcements. In terms of the Twitter networks, policy theory
does a poor job of explaining how Twitter networks form, although the Idle No More and
copyright networks did reflect national interest and the importance of the organizational
model (including organizations, stable actors and professional groups) on the networks.
The cyberbullying networks were more international and less stable in terms of actor
participation than the other groups. The networks were found to be less influential on
policy than previous legislations and global agreements. The conclusion proposes the use of
stakeholder analysis techniques to help manage public agendas for government, including
an awareness of “thin” engagement approaches where the stability of networks cannot be
assumed for policy issues.
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Acknowledgements
I would like first to thank my committee all of whom have played an essential role in
supporting me through this dissertation. I have also drawn from a number of faculty at
the Johnson Shoyama Graduate School of Public Policy for this work. Emails to Jeremy
Rayner, Ken Coates, Murray Fulton, Gregory Marchildon and Amy Zarzeczny were all
kindly replied to with helpful advice and kind words. A small network of social network
analysis scholars have also kindly provided their helpful words for my dissertation. Peter
Carrington and John McLevey helped me grasp some of the sociological perspectives
on public policy and some of the finer aspects of social network analysis. Ian Milligan
encouraged me to explore the use of social network analysis in a big data context and
through hackathons and other activities gave me a much stronger grasp of computational
approaches than I had before I started. My supervisor, Kathleen McNutt, was a major
source to draw on for support when I needed it most, and I wish to thank her from the
bottom of my heart for that. Michael Kontak and Olena Kapral played a major role in the
copy editing of my work for which I am deeply grateful. Finally, none of my work would be
possible without the patience and support of my family including my wife Wanda and my
two sons Adrien and Rene. The latter two are just now beginning to grasp both the power
and limitations of Twitter as a way to promote political positions. I wish them luck and
will forever be available to support them whenever things go sour.
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Contents
Abstract i
Acknowledgements ii
1 Introduction 1
2 Agenda Setting Theory: Canada’s Tradition 8
2.1 Agenda Setting in Canadian Democracy . . . . . . . . . . . . . . . . . . . . 11
2.2 The Media’s Role in Shaping Policy Agendas . . . . . . . . . . . . . . . . . 14
2.3 Technology and Its Influence on Canadian Government . . . . . . . . . . . . 20
2.4 Public Discourse, Social Activism and Agenda Setting . . . . . . . . . . . . 25
2.5 The Network society . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
2.6 The Theoretic Path Forward . . . . . . . . . . . . . . . . . . . . . . . . . . 31
3 Twitter as Agenda Setting Tool 33
3.1 Establishing a Twitter Identity . . . . . . . . . . . . . . . . . . . . . . . . . 35
3.2 Twitter as News Beat: . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
3.3 Twitter as Social Network . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39
3.4 Twitter as Organization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40
3.5 How to Study the Connection of Twitter to Public Policy . . . . . . . . . . 42
3.6 Policy Events and Policy Issues . . . . . . . . . . . . . . . . . . . . . . . . . 43
3.7 Research Questions and Hypotheses . . . . . . . . . . . . . . . . . . . . . . 47
4 Methodology 53
4.1 Historical Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53
4.2 Social Network analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56
4.3 Network boundaries & Sampling . . . . . . . . . . . . . . . . . . . . . . . . 58
4.4 Exponential Random Graph Models . . . . . . . . . . . . . . . . . . . . . . 61
4.5 Connected Components . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64
4.6 Limitations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65
5 First Nations Treaty Rights and The Idle No More Movement 67
5.1 The Policy Agenda: Treaty Land Claims, Economic Development and Edu-
cation Sovereignty . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69
5.2 Aboriginal Sovereignty, Treaty Rights & Identity . . . . . . . . . . . . . . . 71
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5.3 Idle No More Movement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75
5.4 Do Twitter networks reflect sustained attention by Canadians on Canadian
issues? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78
5.5 Actor Stability Across Events . . . . . . . . . . . . . . . . . . . . . . . . . . 84
5.6 Group Influence and Model Selection . . . . . . . . . . . . . . . . . . . . . . 89
5.7 Group Formation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92
5.8 Analysis and Initial Recommendations . . . . . . . . . . . . . . . . . . . . . 94
6 Copyright and Fair Use 97
6.1 The Principles of Canadian Copyright . . . . . . . . . . . . . . . . . . . . . 99
6.2 The Policy Agenda . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101
6.3 Do Twitter networks reflect sustained attention by Canadians on Canadian
issues? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105
6.4 Actor Stability Across events . . . . . . . . . . . . . . . . . . . . . . . . . . 108
6.5 Group Influence and Model Selection . . . . . . . . . . . . . . . . . . . . . . 111
6.6 Network Formation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112
6.7 Analysis and Initial recommendations . . . . . . . . . . . . . . . . . . . . . 114
7 Cyberbullying and Online Harassment 117
7.1 The Policy Agenda: Victim’s Rights, Lawful Access and Criminal Account-
ability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120
7.2 Cyberbullying, Twitter and Online culture . . . . . . . . . . . . . . . . . . . 123
7.3 The Deaths of Amanda Todd and Rehtaeh Parsons . . . . . . . . . . . . . . 125
7.4 Do Twitter networks reflect sustained attention by Canadians on Canadian
issues? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 128
7.5 Actor Stability Across events . . . . . . . . . . . . . . . . . . . . . . . . . . 131
7.6 Group Influence and Model Selection . . . . . . . . . . . . . . . . . . . . . . 134
7.7 Network Formation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 136
7.8 Analysis and Initial recommendations . . . . . . . . . . . . . . . . . . . . . 137
8 Conclusions and Recommendations 141
8.1 Do Twitter networks reflect sustained attention by Canadians on Canadian
issues? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 143
8.2 How do Actor Traits influence the formation of Networks? . . . . . . . . . . 145
8.3 What is the Structure of a Twitter Network? . . . . . . . . . . . . . . . . . 146
8.4 Policy Analysis for Agenda Setting in Online Networks . . . . . . . . . . . . 147
8.5 Parasociality and Thin Interaction . . . . . . . . . . . . . . . . . . . . . . . 150
8.6 Thin Engagement - A New Research Program . . . . . . . . . . . . . . . . . 151
8.7 Recommendations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 154
8.8 Final Words . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155
9 Executive Summary / Policy Brief 157
9.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 157
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9.2 Agenda Setting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 157
9.3 Twitter as a Bringer of New Voices . . . . . . . . . . . . . . . . . . . . . . . 158
9.4 Results. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 158
9.5 Conclusion and Policy Implications . . . . . . . . . . . . . . . . . . . . . . . 159
Bibliography 160
A Appendix 184
A.1 Appendix One: Exponential Random Graph Result Tables . . . . . . . . . . 184
A.1.1 IDLE NO MORE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 184
A.1.2 COPYRIGHT / FAIR USE . . . . . . . . . . . . . . . . . . . . . . . 208
A.1.3 CYBERBULLYING . . . . . . . . . . . . . . . . . . . . . . . . . . . 218
A.2 Appendix Two: Goodness of Fit Graphs for Selected Cases . . . . . . . . . . 234
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List of Tables
3.1 Events and example search terms for three case studies. . . . . . . . . . . . 45
3.2 Model development and variables for analysis of Twitter networks. . . . . . 50
5.1 Network statistics for Idle No More events. . . . . . . . . . . . . . . . . . . 79
5.2 Global demographics for Idle No More Networks. . . . . . . . . . . . . . . . 81
5.3 Canadian National demographics for Idle No More Networks. . . . . . . . . 82
5.4 Professionals in the Idle No More networks. . . . . . . . . . . . . . . . . . . 82
5.5 Representation by organizations for Idle No More networks. . . . . . . . . . 84
5.6 Model selection for Idle No More Twitter networks. . . . . . . . . . . . . . . 89
5.7 Most important factors in the ergm models for Idle No More events (replies)
(p-value < 0.05). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90
5.8 Most important factors in the ergm models for Idle No More events (replies)
(p-value < 0.05). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91
5.9 Distribution of strongly connected components of size k of Idle No More
Networks. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92
5.10 Degree and Betweenness Centralization of Idle No More Networks. . . . . . 93
5.11 Summary of Results for Idle No More . . . . . . . . . . . . . . . . . . . . . 95
6.1 Network statistics for Copyright Networks. . . . . . . . . . . . . . . . . . . 106
6.2 Global demographics for Twitter Population for Copyright networks. . . . . 107
6.3 Canadian National demographics for Twitter Population for the Copyright
Networks. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107
6.4 Professional make-up of the Copyright networks based on profiles. . . . . . 108
6.6 Representation by organizations for Copyright Networks.. . . . . . . . . . . 108
6.7 Model selection for Copyright networks. . . . . . . . . . . . . . . . . . . . . 111
6.8 Most important factors in the ergm models for copyright events (replies)
(p-value < 0.05). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111
6.9 Most important factors in the ergm models for copyright events (retweets)
(p-value < 0.05). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112
6.10 DistributionofstronglyconnectedcomponentsofsizekofCopyrightNetworks.113
6.11 Degree and Betweenness Centralization of Copyright Networks. . . . . . . . 113
6.12 Summary of Results for copyright case . . . . . . . . . . . . . . . . . . . . . 115
7.1 Network statistics for Cyberbullying networks. . . . . . . . . . . . . . . . . 129
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7.2 Global demographics for Twitter Population for Cyberbullying networks. . . 129
7.3 Canadian National demographics for Twitter Population for Cyberbullying
networks. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 130
7.4 Demographics by profession stated on Twitter profile for Cyberbullying
networks. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 130
7.5 Percentage of Organizations in Cyberbullying networks. . . . . . . . . . . . 131
7.6 Model selection for the Cyberbullying networks (see Appendix for details). . 134
7.7 Most important factors in the ergm models for cyberbullying events (replies)
(p-value < 0.05). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135
7.8 Most important factors in the ergm models for cyberbullying event
(retweets)(p-value < 0.05). . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135
7.9 Distribution of strongly connected components of size k of Cyberbullying
Networks. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 136
7.10 Degree and Betweenness Centralization of Cyberbullying Networks. . . . . . 137
7.11 Research question results summary for Cyberbullying networks . . . . . . . 138
8.1 Responses for Research Question One. . . . . . . . . . . . . . . . . . . . . . 144
8.2 Hypotheses for Research Question Two. . . . . . . . . . . . . . . . . . . . . 145
8.3 Hypotheses for Research Question Three. . . . . . . . . . . . . . . . . . . . 147
A.1 Ergm results for Idle No More reply network, January 2nd, 2013 (p.m.) . . . 184
A.2 Ergm results for January 2nd, 2013 (p.m.) retweet network. . . . . . . . . . 186
A.3 Ergm results for January 2, 2013 (a.m.) reply network. . . . . . . . . . . . . 188
A.4 Ergm results for January 2, 2013 (a.m.) retweet network. . . . . . . . . . . 190
A.5 Ergm Results for January 10, 2013 (p.m.) reply network. . . . . . . . . . . . 192
A.6 Results for January 10, 2013 (p.m.) retweet network. . . . . . . . . . . . . . 194
A.7 Ergm results for January 10, 2013 (a.m.) reply network. . . . . . . . . . . . 196
A.8 Ergm results for January 10, 2013 (a.m.) retweet network. . . . . . . . . . . 198
A.9 Ergm results for October 7th, 2013 (p.m.) reply network. . . . . . . . . . . 200
A.10Ergm results for October 7th, 2013 (p.m.) retweet network. . . . . . . . . . 202
A.11Ergm results for October 7th, 2013 (a.m.) reply network. . . . . . . . . . . 204
A.12Ergm results for October 7th, 2013 (a.m.) retweet network. . . . . . . . . . 206
A.13Ergm results for February 10th, 2012 reply network. . . . . . . . . . . . . . 208
A.14Ergm results for June 29, 2012 reply network. . . . . . . . . . . . . . . . . . 210
A.15Ergm results for June 29, 2012 retweet network. . . . . . . . . . . . . . . . . 212
A.16Ergm results for July 12th, 2012 reply network. . . . . . . . . . . . . . . . . 214
A.17Ergm results for July 12, 2012 retweet network. . . . . . . . . . . . . . . . . 216
A.18Ergm results for October 19, 2012 reply network. . . . . . . . . . . . . . . . 218
A.19Ergm results for October 19, 2012 (p.m.) retweet network. . . . . . . . . . . 220
A.20Ergm results for April 6, 2013 (“OpJustice4Rehtaeh”)reply network. . . . . 222
A.21Ergm results for April 6, 2013 (“OpJustice4Rehtaeh”) retweet network. . . 224
A.22Ergm results for April 6, 2013 (“Rehtaeh”)reply network. . . . . . . . . . . 226
A.23Ergm results for April 6, 2013 (“rehtaeh”) retweet network. . . . . . . . . . 228
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A.24Ergm results for June 29, 2012 reply network. . . . . . . . . . . . . . . . . . 230
A.25Ergm results for June 29, 2012 retweet network. . . . . . . . . . . . . . . . . 232
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