Abstracting

, 77

Academic presses

, 162

Academic publishes

, 162

Activist archives

, 123

African American Vernacular English (AAVE)

, 103–104

Agence France-Presse (AFP)

, 251–253

Algorithmic black boxes

, 77–78

Alliance. See Coalitions

American Association of University Women

, 240

American Liberty League

, 191

American Political Science Association (APSA)

, 161

American Schools of Oriental Research Syrian Heritage Initiative (ASOR-CHI)

, 84

American Sociological Association (ASA)

, 161–162

Analytical data

, 78–79

Analytical metadata

, 80–81

Animal Enterprise Terrorism Act (2006)

, 155

Animal rights

, 188

Anti-abortion movements

, 188

Anti-alcohol movements

, 194–195

Anti-extradition Fact Check

, 248

Anti-Extradition Law Amendment Bill (Anti-ELAB)

, 8, 246

event catalog

, 250–251

protests in Hong Kong (2019)

, 241, 246–247

Anti-Mask Law

, 247

Antinuclear groups

, 240

Apple Daily Hong Kong

, 251–253

Application programming interfaces (APIs)

, 107–108

Archival data

, 95

Archival research and epistemology

, 94–96

Archives

, 94–95

voices in

, 134–138

Armed Conflict Location and Event Data (ACLED)

, 221

Art festivals

, 17

Artificial intelligence (AI)

, 104

Automated event coding

, 249–250

Automated event databases

, 22–23

Belmont Principle of Respect for Persons, The

, 155

Belmont principles

, 6, 146–147

Belmont Report, The

, 146

Biases of news sources, understanding potential limitations and

, 40–42

Big data projects

, 50

Black, Indigenous, and people of color (BIPOC)

, 149

Black feminist scholars

, 171

Black rights movement

, 205–206

Boolean operators

, 43

Broken windows theory

, 218

Channel News Asia (CNA)

, 251–253

Chinese University of Hong Kong (CUHK)

, 255

Civil Human Rights Front

, 246–247

Clustering analysis

, 26

Co-appearance

, 254

Co-organizers

, 254

Coalitional relationships

, 255

Coalitions

, 240

building coalition as strategy

, 241–242

data and methods

, 247–255

formation and collapse of coalitions in response to threats

, 258–260

formation and dissolution in response to threats

, 255–260

measuring event coalition

, 254–255

threats and

, 242–245

Coercive repression

, 101–102

Cognitive process

, 243

Collection, innovations in

, 4–5

Collective action events

, 19–20

Communal projects

, 160

Communist movements

, 188

Community events

, 128

Community mobilization

, 26, 29

Computational methods

, 32–33

Computational syntactic methods

, 241

Computational text analysis

contentious events and social movement research

, 16–20

data

, 21–22

environmental movement

, 20–21

issues

, 24–25, 28–29

methods

, 22–26

newspapers as data

, 18–19

organizational type

, 25–26, 29

and potential for reducing bias in collecting data on social movements

, 19–20

protests and events

, 22–23, 26–27

results

, 26–29

tactics

, 24, 27–28

Computer-automated big data projects

, 50

Confidence intervals

, 222–225

Congressional investigations

, 196, 198

Conservative groups

, 191

Constituent data

, 78–79

Constituent metadata

, 79–80

Contentious events

, 14, 16, 19–20

Contentious politics

, 2

Count models

, 220–221

fit appropriate count models and get predicted counts for risk factor

, 222

Counter movements

, 102

Coverage

, 195–197

Criminological theory

, 218

Crisp-set QCA

, 196–197

Crowd Counting Consortium and Count Love, The

, 20

Cultural contexts

, 151–152

“Cultural Violence and Civilian Deaths” project

, 73

Cumulative diffusion

, 216

Data

data-driven clustering of topics

, 25

data-mining platforms

, 39

and modeling strategies

, 225–226

newspapers as

, 18–19

Data collection

, 107–109

bias

, 41

strategies

, 59–61

Data Documentation Initiative (DDI)

, 73

Data quality

, 74–75

provenance and data quality in satellite images

, 73–76

Data sources

, 3

aggregate as sources as possible

, 50–52

hegemon

, 52–53

selection for world-historical analysis

, 49–53

Databases

, 39–40

Deep-learning algorithms

, 250

Delta method

, 220–221, 223

Description bias

, 41–42, 48

Deviant combinations and advantages of wide comparisons

, 199–207

Diffusion

, 217

process

, 219

studies

, 217–218

Digital data sources

, 5

Digitized historical newspaper

, 39–40

Digitized news sources

, 65

use of

, 42–43

Directorate-General of Antiquities and Museums in Syria (DGAM in Syria)

, 81–82

Disruptiveness

, 195

Dissidents

, 244

Domestic news, dealing with

, 54–56

Dove satellites

, 75–76

Dramatic ramifications

, 137–138

Dummy variable format

, 57

Dynamics of Collective Action (DoCA)

, 217

articles

, 23

data

, 221, 226

dataset

, 226–227

project

, 206

Earth First! (organization)

, 20–21

EBSCO Regional Business News database

, 21

Emotional “twinges”

, 136–137

Emotional danger

, 149

Emotional exploration

, 137

Emotional risk

, 152–153

Emotions and interactions

, 134–138

Empirical analysis

, 241

Enacted policy

, 195–196

Encyclopedia of Associations

, 21

Enforced policy

, 195–196

Environmental movement

, 20–21, 200

Environmental movement organizations (EMOs)

, 15, 21

Environmental sciences

, 71

Ethical standards for student participation in protest research

Belmont principles

, 146–147

ethics in practice

, 147–158

Ethics

, 71

in practice

, 147–158

Ethnographic research

, 179

Event coalition

, 256–257

measuring

, 254–255

Event coding

, 241

Event diffusion momentum (EDM)

, 7, 216, 220, 233

calculate EDM and confidence intervals

, 222–225

count number of pre/post-event protests

, 222

diffusion studies

, 217–218

explanations of protest diffusion

, 218–219

fit appropriate count models and get predicted counts for each risk factor

, 222

identifying risk factors of protest diffusion

, 226–230

macro-micro analysis of effects of governors’ party affiliations and policing

, 232–233

proposed method for estimating EDM

, 220–225

research design

, 225–226

select event-based data

, 221

set temporal and spatial ranges of interest

, 221–222

toward inter-event approach

, 219–220

US presidents’ and governors’ party affiliations and diffusion

, 230–231

Event history analysis (EHA)

, 219

Event-based data, select

, 221

Events, protests and

, 22–23

Expansionary forms of nationalism

, 39

Facebook

, 98

Faculty research projects

, 144

False negatives, strategies to reduce

, 45–46

Feminist archivists

, 125

Feminist ethnography

boundaries and silences

, 127–134

methods

, 6

origin of social movement archives

, 122–127

voices in archives

, 134–138

Feminist organizations

, 126–127

Feminist research

, 122

Field research

, 170

insider-ness and outsider-ness in

, 170–172

Gale

, 52

Gale Cengage Learning

, 21, 39, 43

Gay liberation movement

, 126

Gentle repression

, 244

Geographic information systems (GIS)

, 78–79

Geographic sciences

, 71

Geographical selection bias

, 57

checking for effect of repeated mentions

, 57

dealing with domestic news

, 54–56

minimizing

, 53–57

tracing geographical sensitivities

, 56

Geographical sensitivities, tracing

, 56

Global Data on Events Language and Tone (GDELT)

, 19–20, 22–23, 38–39, 50

Graduate Assistants

, 173

Graduate Student Union Campaign

, 173, 177–178, 180–181

Graduate students engaged in protest research, ethical treatment of

, 147–158

Graduate training

, 144–145

programs

, 147

Green State University (GSU)

, 173

Greenpeace (confrontational EMO)

, 18–21, 200

Ground truthing

process

, 83, 85

techniques

, 71

Guardian/The Observer (G/O)

, 39

High–resolution satellite images

, 69–71

Historical connection

, 240

Historical newspaper

, 43

Historical sources

, 59–61

Hong Kong Protests (2019)

, 228

Indiscriminate repression

, 245

Indiscriminate threats

, 241, 244–245

Inmediahk. net

, 251–253

Innovations

, 216

in collection and processing

, 4–5

epistemology and reflexivity

, 5–7

novel analytics

, 7–8

Insider-ness in field research

, 170–172

Insider–outsider dynamics and identity in qualitative studies of social movements

case studies

, 172–173

graduate student union campaign

, 173

insider-ness and outsider-ness in field research

, 170–172

Latinx Millennial Student organizing

, 172–173

level of participation within movements

, 175–179

questions for future researchers

, 175, 179, 181

Ragon

, 174–175

recognizing and negotiating interplay of researcher and participant identities

, 174–175

Reyes

, 174–175

securing research approval within institutional settings

, 179–181

Instagram

, 98–99, 111

Instant archives

, 94, 96, 98

archival research and epistemology

, 94–96

data and data collection

, 105–111

data collection

, 107–109

instant archive

, 96–98

limitations of single archives and importance of triangulation and empirical approaches

, 110–111

methodological decisions

, 105–106

pace or life cycle of platform/archive

, 106

platform design and evolution

, 98–101

repression in

, 101–103

research question about individuals, communities, organizations, or discourse

, 105–106

sampling and sample size

, 109–110

understanding data

, 106–107

user innovations

, 103–104

Institution-based research on social movements

, 171–172

Institutional change

, 26, 29

Institutional context

, 240

Institutional identity

, 173–175

Institutional mediation model of social movement news coverage

, 189–193

Institutional repression

, 244

Institutional Review Board (IRB)

, 145, 179, 181

Institutional settings, securing research approval within

, 179–181

Institutions

, 216

“Insurgent Artifacts” project

, 72–73, 83–84

Insurgent groups

, 72, 245

Integrated Crisis Early Warning System (ICEWS)

, 38–39

Inter-event approach

, 7, 219–220

Inter-organizational coalitions

, 240

“Inter-protest” dynamics

, 219–220

Interactions, emotions and

, 134–138

International Crisis Early Warning System (ICEWS)

, 19–20, 22–23

Irredentism

, 39

Journals

, 162

Justice

, 157–158

Karatasli’s analysis

, 63–64

Keyword strings

, 43, 45

working with

, 43–49

Land Remote Sensing Policy Act (1992) (LRSPA)

, 75

Latinx Millennial Student

, 172–173, 176–177, 180

Latinx student organizations

, 172–173

League of Women Voters

, 240

Legal risks

, 153–155

Lesbian feminists

, 139

LexisNexis (Online platforms)

, 39, 43, 52

Liberal Arts College (LAC)

, 172–173

Log link function

, 223–225

Logical remainders

, 203–204

Looters’ pits

, 78, 81

Looting

, 72

LRT–Vuong model selection

, 226

Machine algorithms

, 73

Machine learning

, 19–20, 249

machine learning-based big data projects

, 50

machine-learning-based event coding projects

, 250

techniques

, 15

Machine-learning Protest Event Data System (MPEDS)

, 22–23

Macro-micro analysis of effects of governors’ party affiliations and policing

, 232–233

results

, 232–233

variables

, 232

Manual data collection

, 107–108

Marginalized communities

, 124–125, 129–130, 139

Marginalized social movement communities

, 122–123

Metadata

, 78–79

incorporating metadata and corroborating satellite images

, 81–86

Michigan Womyn’s Music Festival

, 126

Microsatellites

, 75–76

Ming Po

, 251–253

Mobilization processes

, 220

Music

, 17

festivals

, 126

National chauvinism

, 39

National Commission for the Protection of Human Subjects of Biomedical and Behavioral Research, The

, 146

National independence wars

, 63

National newspapers

, 18–19

National Organization for Women (NOW)

, 126–127, 240

National Research Act (1974)

, 146

National Science Foundation’s funds for emergent research

, 161–162

National US social movement organizations

, 208

National Women’s Music Festival

, 126

Nationalism

, 38

datasets of

, 38

scholars of

, 38–39

Nationalist mobilization

, 38

Nationalist movements

, 39

Natural language processing technologies (NLP technologies)

, 15, 19–20, 38–39, 47

New Left movements

, 16

New York Times (NYT)

, 15, 39

News coverage

, 188

News media

, 190, 209–210

Newspaper

boundaries of true and false positives

, 47–49

changing reporting styles of newspapers

, 46–47

data

, 14–15, 18–19

using newspaper archives for collecting macro-historical data

, 40–43

understanding potential limitations and biases of news sources

, 40–42

use of digitized news sources

, 42–43

Nexis Uni newspaper database

, 21–23

North Eastern Women’s Music Retreat (NEWMR)

, 136–137

planning documents

, 137–138

Novel analytics

, 7–8

Objectivity in satellite images, algorithms and illusion of

, 76–78

Olson method

, 77

Online ethnographies

, 110

Online platforms

, 43

Operationalization

, 106–107

Organizational strength

, 195

Organizational structure

, 240

Organizational type

, 25–26

Organizing Together (OT)

, 181

Outsider-ness in field research

, 170–172

Palestinian nationalism

, 41

Participant identities, recognizing and negotiating interplay of

, 174–175

Participation within movements, determining level of

, 175–179

Partisan political context

, 195–196

PATRIOT Act (2001)

, 155

People for the Ethical Treatment of Animals (PETA)

, 20–21

Periodization

, 257–258

Personal transformation

, 26

Planet (private commercial satellite company)

, 75–76

Platform design and evolution

, 98–101

Platform/archive, pace or life cycle of

, 106

Policing

, 232–233

Political mediation models

, 192

Political opportunity theory

, 230

Political Organization in the News (PONs)

, 189

Political right

, 195

Political sociology

, 207–208

Post-event protests, count number of

, 222

Pre/post-event protests, count number of

, 222

Pro-democracy activists

, 243

Processing, innovations in

, 4–5

Professional associations

, 161–162

Professional organizations

, 160–162

sections of

, 162

Professional risks

, 153

ProQuest (Online platforms)

, 39, 43, 52

Protest diffusion

, 215–216

explanations of

, 218–219

forms of action

, 227

identifying risk factors of

, 226–230

method

, 228

results

, 228–230

size of protest

, 227

social movement organizations

, 227–228

studies

, 219

variables and operationalization

, 227–228

violence

, 228

Protest research

beneficence

, 148–155

benefits

, 148–149

emotional risk

, 152–153

ethical treatment of graduate students engaged in

, 147–158

individual researchers

, 158

journals and academic presses

, 162

justice

, 157–158

legal risks

, 153–155

physical risks

, 150–152

practice

, 158–163

professional organizations

, 160–162

professional risks

, 153

respect for persons

, 155–157

risks

, 149–150

sections of professional organizations

, 162

throughout profession

, 162–163

Protests

, 16, 19–20

for Black Lives

, 144

events

, 18, 22–23, 26–27, 31, 255

Provenance

, 74

concept of

, 74

Public education programs

, 14

Public health and social science perspectives

, 217–218

QAnon

, 110–111

Qualitative comparative analysis (QCA)

, 7, 189, 193–194

data, methods, and measures

, 193–196

four hypotheses and QCA results

, 196–199

institutional mediation model of social movement news coverage

, 189–193

truth tables, Venn diagrams, deviant combinations, and advantages of wide comparisons

, 199–207

Qualitative methods course

, 177–178

Reagan conservative regime

, 200–202

Recognition

, 2–3

Regional Public University (RPU)

, 172–173, 176–177

Repression

, 243–244

in instant archive

, 101–103

Republican conservative regime

, 200–202

Research

, 145

participants

, 146

process

, 122, 148

securing research approval within institutional settings

, 179–181

Research design

, 225–226

DoCA data

, 226

zero-inflated poisson models

, 226

Research in Social Movements, Conflict & Change (RSMCC)

, 1

Research University (RU)

, 172–173, 176

Researcher, recognizing and negotiating interplay of

, 174–175

Researcher bias

, 45–47

Resolution

, 75

Resource mobilization theory

, 188, 233–234

Resources

, 240

Risk assessment

, 159

Rule-based programming

, 249

Rule-based text analysis

, 241

Russian military

, 69–70

Safety

, 144

Satellite imagery

, 3

Satellite images

, 70, 86

algorithms and illusion of objectivity in

, 76–78

case studies and methods

, 71–73

incorporating metadata and corroborating satellite images

, 81–86

provenance and data quality in satellite images

, 73–76

responsible practices for satellite research

, 86–88

satellite metadata

, 78–81

Satellite sensors

, 77

Scale shift

, 219–220

Science and technology studies (STS)

, 73

Search strategy of SSNM dataset

, 46

Selection bias

, 40–41

Selective repression

, 245

Selective threats

, 241, 244–245

Severe repression

, 244

Shared identity

, 240, 242

Shared ideology

, 242

Smith College library website, The

, 123–124

Social, Political, and Economic Event Database (SPEED)

, 19–20

Social identities

, 169–171, 174

Social media

, 3, 93–94, 111–112, 241

companies

, 103

data

, 94, 108–110

mobilization

, 93–94

platforms

, 98, 100, 102

Social movement organizations (SMOs)

, 18–19, 215–216, 227–228

Social movements

, 14, 17, 31, 38, 41–42, 144–145, 158, 161–162, 171–172, 188, 227, 240

computational text analysis and potential for reducing bias in collecting data on

, 19–20

institutional mediation model of social movement news coverage

, 189–193

origin of social movement archives

, 122–127

research

, 16–20

researchers

, 94, 105, 107, 153, 219, 230

scholars

, 14–18, 144

South China Morning Post

, 251–253

SPEED

, 22–23

Standpoint concept

, 171

State Actions

, 255

State repression

, 243–244

State-induced threats

, 240

State-led nationalism

, 39

State-seeking nationalism

, 39

State-Seeking Nationalist Movements (SSNM)

, 4, 61–62

controlling for increasing number of pages over time

, 57–58

data source selection for world-historical analysis

, 49–53

dataset I

, 43

dataset II

, 39

minimizing geographical selection bias

, 53–57

using newspaper archives for collecting macro-historical data

, 40–43

reliability of SSNM dataset I

, 58–64

strategies to reduce false negatives

, 45–46

working with keyword strings

, 43–49

State-seeking nationalist movements

, 39

Strategies

, 20

Structural topic modeling (STM)

, 24–25

Supervised machine-learning methods

, 249–250

Syntactic rule-based methods

, 8

Syrian civil war

, 86–87

Tactics

, 20, 24, 27–28

Telegram

, 8, 241

comparing events extracted from Telegram and Newspaper sources

, 251–253

Telegram Broadcasting Posts

, 247–249

Threats

, 242–245

Threshold effect

, 40–41, 48–49

TikTok

, 98–99, 111

Topic models

, 24–25

Toronto G20 Summit Protests (2010)

, 228

Trans-exclusionary radical feminists (TERFs)

, 132–133

Triangulation and empirical approaches, limitations of single archives and importance of

, 110–111

Truth tables and advantages of wide comparisons

, 199–207

Twitter

, 98

United Kingdom (UK)

, 39

UK-based newspapers

, 56

United States (US)

, 39

method

, 230–231

party affiliation

, 230

presidents’ and governors’ party affiliations and diffusion

, 230–231

results

, 231

US social movements

, 193–194, 206

US-based newspapers

, 56

variables

, 230

Unmanned Aero Systems (UAS)

, 74

Uppsala Conflict Data Program (UCDP)

, 73

UCDP/PRIO Armed Conflict Dataset

, 221

Venn diagrams and advantages of wide comparisons

, 199–207

Veterans

, 194–195

Violence

, 228

Web scraping

, 107–108

Web-crawling techniques

, 20

Wen Wei Po

, 251–253

White supremacists

, 188, 191

Women’s Music Archives

, 6, 124–125, 135

case of

, 125

World Labor Group database (WLG database)

, 52

World Wildlife Fund (nonconfrontational EMO)

, 18–19

YouTube

, 111

Yusin Constitution

, 243

Zero-Inflated Poisson Models (ZIP models)

, 226