Class 11: Social Movements online, in effect, dying out, and going forward

Online

Opening notes

short synopsis for final essay due Friday (17 January) (send to me via email)

Presentation groups

Presentations line-up
Date	Presenters	Method
4 Dec:	Daichi, Seongyeon, Jehyun	ethnography
8 Jan:	Ayla, Tara, Theresa, Annabelle	discourse analysis
15 Jan:	Luna, Emilene, Raffa, Sofia	TBD

Theses from an earlier age of the internet (Diani 2000)

‘computer mediated communication’ (CMC)
types of communication
features of internet tools
different organisation types and CMC

Wlan GIFfrom Wlan GIFs

Diani (2000) - CMC

‘computer mediated communication’, CMC:

interpersonal communication through the use of computers or digital devices, now typically involving internet channels
- then: (mass) email, message boards, instant messaging
- now: social media, encrypted messaging with different message types (photo, video, audio), AI-generated material, other ways??

sometimes easing how people communicate; sometimes changing it

Diani (2000) - types of communication

	Private	Public
Direct	--face-to-face between activists	--in public spaces (e.g., demos)
	--message restricted to group boundaries	--communicating to person(s) (e.g., speeches, leafleting)
		--may overlap with attempts to attract media attention (i.e. ’public mediated’)
Mediated	--messages within group boundaries but transmitted through tech	--all media-related communication (e.g., press releases, adverts, 'manipulation of media through spectacular events')
	--(e.g., email, phone calls) with varying privacy

Diani (2000) - organisations and communication

some hypotheses about CMC and different movement organisations

Organisation type	Importance of CMC	Effects?
Orgs. focusing on professional resources	high	CMC supports professionalised groups that sometimes require large mobilisation (e.g., Greenpeace), helping to 'get the word out'
Orgs. mobilising participatory resources	moderate/low	CMC reinforces already existing ties; these orgs. remain reliant on direct, face-to-face interactions to recruit, build collective identity, and maintain commitment
Orgs. mobilising participatory resources	moderate/low	"Sustained collective action is unlikely to originate from purely virtual ties if they are not sustained by previous interaction"
Transnational networks	moderate	CMC helps link (especially former) activists and militants (individuals and groups) to promote shared values, but little consequential effect for organising

Diani (2000) - theses of an earlier internet age

Broadly, internet tools (‘computer mediated communication’, CMC) allow…

greater speed (and accuracy) of communication

less cost of communication

greater connectivity across distances
- unifying different national or regional parts of a movement

Are these assertions still ‘as true’ as they were in 2000?

Diani (2000) - theses of an earlier internet age

Can CMC create new types of communities (if so, what kinds)? Can they create collective identity and enable durable/sustained activism?

can that happen with online anonymity?

most examples of personal interaction in electronic discussion groups actually miss some of the requirements usually associated with the idea of community. Participants in those lists often hide their personal identity, participate occasionally, are not tied in any sort of committed relationship and are mostly involved in dyadic or at most triadic interactions

Poll: Movements online

A QR code for the survey.

Take the survey at https://forms.gle/xwWefHu7eDAmyzvv9

most important online tool for SMs?
online organising more democratic?
online movements more individualised?
platforms amplify movements of the marginalised?

platforms not so useful since algorithms favour sensationalism?
online movement activity often encourages a “slacktivism”
movements online face greater censorship and surveillance?
should online platforms be more regulated to prevent movements (and other actors) from spreading misinformation?

md`## Poll results (Respondents: ${respondentCount})`

import { liveGoogleSheet } from "@jimjamslam/live-google-sheet";
import { aq, op } from "@uwdata/arquero";

// UPDATE THE LINK FOR A NEW POLL
surveyResults = liveGoogleSheet(
  "https://docs.google.com/spreadsheets/d/e/" +
    "2PACX-1vR7--DC-gLwhLrMYBIvigczwsp5vMxC5A93sY7PDai0NdSIBFSvjTOjKUZxxtLpl9KWTxiyxKPAGtUD/" +
    "pub?gid=2023133127&single=true&output=csv",
  10000, 1, 9); // adjust the last number to select all relevant columns 

respondentCount = surveyResults.length;

online organising more democratic?

more_democraticCounts = aq.from(surveyResults)
  .select("more_democratic")
  .groupby("more_democratic")
  .count()
  .derive({ measure: d => "" })

// Calculate the maximum count from your dataset
more_democratic_maxCountRE = Math.max(...more_democraticCounts.objects().map(d => d.count));

plot_more_democratic = Plot.plot({
  marks: [
    Plot.barY(more_democraticCounts, {
      x: "more_democratic",
      y: "count",
      fill: "more_democratic",
      stroke: "black",
      strokeWidth: 1
    }),
    Plot.ruleY([respondentCount], { stroke: "#ffffff99" })
  ],
  color: {
    domain: [
      "Strongly disagree",
      "Disagree",
      "Neutral",
      "Agree",
      "Strongly agree"
    ],
    range: [
      "red",
      "pink",
      "lightgrey",
      "lightgreen",
      "forestgreen"
    ]
  },
  marginBottom: 180,
  x: { label: "", tickSize: 2, tickRotate: -45,
    domain: ["Strongly disagree", "Disagree", "Neutral", "Agree", "Strongly agree"]
  },  
  y: {
    label: "",
    tickSize: 10,
    tickFormat: d => d,
    tickValues: Array.from(
      new Set(more_democraticCounts.objects().map(d => d.count))
    ).sort((a, b) => a - b),
    domain: [0, more_democratic_maxCountRE]
  },
  facet: { data: more_democraticCounts, x: "measure", label: "" },
  marginLeft: 140,
  style: {
    width: 1350,
    height: 500,
    fontSize: 30,
  }
});

online movement activity more individualised?

individualisedCounts = aq.from(surveyResults)
  .select("individualised")
  .groupby("individualised")
  .count()
  .derive({ measure: d => "" })

// Calculate the maximum count from your dataset
individualised_maxCountRE = Math.max(...individualisedCounts.objects().map(d => d.count));

plot_individualised = Plot.plot({
  marks: [
    Plot.barY(individualisedCounts, {
      x: "individualised",
      y: "count",
      fill: "individualised",
      stroke: "black",
      strokeWidth: 1
    }),
    Plot.ruleY([respondentCount], { stroke: "#ffffff99" })
  ],
  color: {
    domain: [
      "Strongly disagree",
      "Disagree",
      "Neutral",
      "Agree",
      "Strongly agree"
    ],
    range: [
      "red",
      "pink",
      "lightgrey",
      "lightgreen",
      "forestgreen"
    ]
  },
  marginBottom: 180,
  x: { label: "", tickSize: 2, tickRotate: -45,
    domain: ["Strongly disagree", "Disagree", "Neutral", "Agree", "Strongly agree"]
  },  
  y: {
    label: "",
    tickSize: 10,
    tickFormat: d => d,
    tickValues: Array.from(
      new Set(individualisedCounts.objects().map(d => d.count))
    ).sort((a, b) => a - b),
    domain: [0, individualised_maxCountRE]
  },
  facet: { data: individualisedCounts, x: "measure", label: "" },
  marginLeft: 140,
  style: {
    width: 1350,
    height: 500,
    fontSize: 30,
  }
});

Poll results

platforms amplify movements of the marginalised?

amplifyCounts = aq.from(surveyResults)
  .select("amplify")
  .groupby("amplify")
  .count()
  .derive({ measure: d => "" })

// Calculate the maximum count from your dataset
amplify_maxCountRE = Math.max(...amplifyCounts.objects().map(d => d.count));

plot_amplify = Plot.plot({
  marks: [
    Plot.barY(amplifyCounts, {
      x: "amplify",
      y: "count",
      fill: "amplify",
      stroke: "black",
      strokeWidth: 1
    }),
    Plot.ruleY([respondentCount], { stroke: "#ffffff99" })
  ],
  color: {
    domain: [
      "Yes",
      "No",
      "Maybe"
    ],
    range: [
      "forestgreen",
      "darkred",
      "goldenrod"
    ]
  },
  marginBottom: 80,
  x: { label: "", tickSize: 2, tickRotate: -1, padding: 0.2,
    domain: ["Yes", "No", "Maybe"]
  },  
  y: {
    label: "",
    tickSize: 10,
    tickFormat: d => d,
    tickValues: Array.from(
      new Set(amplifyCounts.objects().map(d => d.count))
    ).sort((a, b) => a - b),
    domain: [0, amplify_maxCountRE]
  },
  facet: { data: amplifyCounts, x: "measure", label: "" },
  marginLeft: 60,
  style: {
    width: 1600,
    height: 500,
    fontSize: 40,
  },
});

platforms not so useful since algorithms favour sensationalism?

algorithmsCounts = aq.from(surveyResults)
  .select("algorithms")
  .groupby("algorithms")
  .count()
  .derive({ measure: d => "" })

// Calculate the maximum count from your dataset
algorithms_maxCountRE = Math.max(...algorithmsCounts.objects().map(d => d.count));

plot_algorithms = Plot.plot({
  marks: [
    Plot.barY(algorithmsCounts, {
      x: "algorithms",
      y: "count",
      fill: "algorithms",
      stroke: "black",
      strokeWidth: 1
    }),
    Plot.ruleY([respondentCount], { stroke: "#ffffff99" })
  ],
  color: {
    domain: [
      "Strongly disagree",
      "Disagree",
      "Neutral",
      "Agree",
      "Strongly agree"
    ],
    range: [
      "red",
      "pink",
      "lightgrey",
      "lightgreen",
      "forestgreen"
    ]
  },
  marginBottom: 180,
  x: { label: "", tickSize: 2, tickRotate: -45,
    domain: ["Strongly disagree", "Disagree", "Neutral", "Agree", "Strongly agree"]
  },  
  y: {
    label: "",
    tickSize: 10,
    tickFormat: d => d,
    tickValues: Array.from(
      new Set(algorithmsCounts.objects().map(d => d.count))
    ).sort((a, b) => a - b),
    domain: [0, algorithms_maxCountRE]
  },
  facet: { data: algorithmsCounts, x: "measure", label: "" },
  marginLeft: 140,
  style: {
    width: 1350,
    height: 500,
    fontSize: 30,
  }
});

Poll results

online movement activity often encourages a “slacktivism”

slacktivismCounts = aq.from(surveyResults)
  .select("slacktivism")
  .groupby("slacktivism")
  .count()
  .derive({ measure: d => "" })

// Calculate the maximum count from your dataset
slacktivism_maxCountRE = Math.max(...slacktivismCounts.objects().map(d => d.count));

plot_slacktivism = Plot.plot({
  marks: [
    Plot.barY(slacktivismCounts, {
      x: "slacktivism",
      y: "count",
      fill: "slacktivism",
      stroke: "black",
      strokeWidth: 1
    }),
    Plot.ruleY([respondentCount], { stroke: "#ffffff99" })
  ],
  color: {
    domain: [
      "Strongly disagree",
      "Disagree",
      "Neutral",
      "Agree",
      "Strongly agree"
    ],
    range: [
      "red",
      "pink",
      "lightgrey",
      "lightgreen",
      "forestgreen"
    ]
  },
  marginBottom: 180,
  x: { label: "", tickSize: 2, tickRotate: -45,
    domain: ["Strongly disagree", "Disagree", "Neutral", "Agree", "Strongly agree"]
  },  
  y: {
    label: "",
    tickSize: 10,
    tickFormat: d => d,
    tickValues: Array.from(
      new Set(slacktivismCounts.objects().map(d => d.count))
    ).sort((a, b) => a - b),
    domain: [0, slacktivism_maxCountRE]
  },
  facet: { data: slacktivismCounts, x: "measure", label: "" },
  marginLeft: 140,
  style: {
    width: 1350,
    height: 500,
    fontSize: 30,
  }
});

Poll results

should online platforms be more regulated to prevent movements (and other actors) from spreading misinformation?

regulationCounts = aq.from(surveyResults)
  .select("regulation")
  .groupby("regulation")
  .count()
  .derive({ measure: d => "" })

// Calculate the maximum count from your dataset
regulation_maxCountRE = Math.max(...regulationCounts.objects().map(d => d.count));

plot_regulation = Plot.plot({
  marks: [
    Plot.barY(regulationCounts, {
      x: "regulation",
      y: "count",
      fill: "regulation",
      stroke: "black",
      strokeWidth: 1
    }),
    Plot.ruleY([respondentCount], { stroke: "#ffffff99" })
  ],
  color: {
    domain: [
      "Yes",
      "No",
      "Maybe"
    ],
    range: [
      "forestgreen",
      "darkred",
      "goldenrod"
    ]
  },
  marginBottom: 80,
  x: { label: "", tickSize: 2, tickRotate: -1, padding: 0.2,
    domain: ["Yes", "No", "Maybe"]
  },  
  y: {
    label: "",
    tickSize: 10,
    tickFormat: d => d,
    tickValues: Array.from(
      new Set(regulationCounts.objects().map(d => d.count))
    ).sort((a, b) => a - b),
    domain: [0, regulation_maxCountRE]
  },
  facet: { data: regulationCounts, x: "measure", label: "" },
  marginLeft: 60,
  style: {
    width: 1600,
    height: 500,
    fontSize: 40,
  },
});

movements online face greater censorship and surveillance?

challengesCounts = aq.from(surveyResults)
  .select("challenges")
  .groupby("challenges")
  .count()
  .derive({ measure: d => "" })

// Calculate the maximum count from your dataset
challenges_maxCountRE = Math.max(...challengesCounts.objects().map(d => d.count));

plot_challenges = Plot.plot({
  marks: [
    Plot.barY(challengesCounts, {
      x: "challenges",
      y: "count",
      fill: "challenges",
      stroke: "black",
      strokeWidth: 1
    }),
    Plot.ruleY([respondentCount], { stroke: "#ffffff99" })
  ],
  color: {
    domain: [
      "Yes",
      "No",
      "Maybe"
    ],
    range: [
      "forestgreen",
      "darkred",
      "goldenrod"
    ]
  },
  marginBottom: 80,
  x: { label: "", tickSize: 2, tickRotate: -1, padding: 0.2,
    domain: ["Yes", "No", "Maybe"]
  },  
  y: {
    label: "",
    tickSize: 10,
    tickFormat: d => d,
    tickValues: Array.from(
      new Set(challengesCounts.objects().map(d => d.count))
    ).sort((a, b) => a - b),
    domain: [0, challenges_maxCountRE]
  },
  facet: { data: challengesCounts, x: "measure", label: "" },
  marginLeft: 60,
  style: {
    width: 1600,
    height: 500,
    fontSize: 40,
  },
});

Poll results

most important online tool for SMs?

ImportantTools = aq.from(surveyResults)
  .select("most_important_tool")
  .filter(d => d.most_important_tool) // to exclude empty ("") strings, 0s, FALSEs, nulls, etc

ImportantTools.array("most_important_tool")

Movements changed by the Internet

Internet has changed both
- how individuals participate, and
- how movement organisations operate

Looking Around GIFfrom Looking GIFs

Examples:
- Otpor, Slobodan Milosevic, and the Bulldozer revolution
- Google bombing
Democratising impact?
- Hong Kong

Otpor, Milosevic, and the Bulldozer revolution

(bulldozers were used by protesters in one action against the state’s media agency)

USAID provides funding to opposition groups in Serbia
- especially to buy mobile phones and computers
the ‘Democratic Opposition of Serbia’ and Otpor! (‘Resistance’), use tech to…
- recruit and train election monitors,
- spread awareness,
- coordinate between groups and different parts of the country

Google bombing

manipulating a search enginge algorithm to rank highly certain websites
Examples:

Google bombing

manipulating a search enginge algorithm to rank highly certain websites
Examples:
- in 2006, Google searches for “failure” returned sites for George W. Bush’s biography

Google bombing

manipulating a search enginge algorithm to rank highly certain websites
Examples:
- in 2006, Google searches for “failure” returned sites for George W. Bush’s biography
- in 2012, UK activists got search results for “EDL” to return, instead of English Defence League, pages for the English Disco Lovers

Google bombing

manipulating a search enginge algorithm to rank highly certain websites
Examples:
- in 2006, Google searches for “failure” returned sites for George W. Bush’s biography
- in 2012, UK activists got search results for “EDL” to return, instead of English Defence League, pages for the English Disco Lovers
- in 2018, search results for “idiot” returned images of Donald Trump

Diani (2000) - CMC’s democratizing impact

the overall democratizing impact of CMC may be severely hampered by two types of resource constraints: while its contribution to networking among citizens’ organizations is undeniable, its contribution to the operations of social control agencies, the military, governments and corporations is – at least quantitatively – much greater; and access to CMC is at least for the time being heavily correlated to class and status

What do you think? Is CMC a democratizing tool?

The case of Hong Kong…

Diani (2000) - CMC’s democratizing impact

Online replacing offline activism

Volk (2021) - Political Performances of Control During COVID-19: Controlling and Contesting Democracy in Germany
- research design
  - brief intro to interpretivism
- PEGIDA online
- findings
discussion topic from the news

Boburnham Inside GIFfrom Boburnham GIFs

Volk (2021) research design

explores how political actors in Germany performed control during the first wave of the COVID-19 pandemic, comparing the performances of control by two institutional actors and one counter-institutional grassroots actor

data generated through qualitative-interpretive methodology (familiar with this?)
- online ethnography
- comparative analysis
- observation of in-person an “anti-lockdown” demonstration and virtual protest

A very brief introduction to interpretive research

Interpretivism - philosophical perspective that reality and knowledge are socially constructed
- cf. (post-)positivist perspectives: there is an ‘objective reality’ that can be measured and tested
  - Galileo Galilei: ‘Count what is countable, measure what is measurable and what is not measurable, make measurable.’
- has epistemological consequences: i.e., if reality is socially constructed, in what ways can we obtain knowledge about it?
  - ANSWER: techniques to identify and assess the meanings that people attach to events, actions, etc.
interpretivist findings dependent on researcher’s interpretation
- problematic (according to some): difficulty of replicability, easy for ‘bias’ to slant interpretation, difficult to generalise

Volk (2021) - PEGIDA ‘virtueller Abendspaziergang’

Volk (2021) - findings (1)

	Style			Intended audience	Transmission mode
Cases	Habitus	Communication modes	Emotional tone	Intended audience	Transmission mode
Merkel	informer of the people	monological, unidirectional	Empathic, caring	National media audience	Conventional media
Kretschmer	Interlocutor of the people	Dialogical, multidirectional	Engaged, brave	Local immediate audience; regional and national media audience	New media; partially immediate
PEGIDA	Enlightened leader of the people	Monological and plurilogical, unidirectional	Enraged, mocking	Regional, national, and transnational media audience	New media

Volk (2021) - findings (1)

how (if at all) do you recall Merkel’s televised address at the start of the pandemic? (https://www.youtube.com/watch?v=4YS20YQbVE4&pp=ygUXbWVya2VsIGNvcm9uYSBhbnNwcmFjaGU%3D)

	Style			Intended audience	Transmission mode
Cases	Habitus	Communication modes	Emotional tone	Intended audience	Transmission mode
Merkel	informer of the people	monological, unidirectional	Empathic, caring	National media audience	Conventional media
Kretschmer	Interlocutor of the people	Dialogical, multidirectional	Engaged, brave	Local immediate audience; regional and national media audience	New media; partially immediate
PEGIDA	Enlightened leader of the people	Monological and plurilogical, unidirectional	Enraged, mocking	Regional, national, and transnational media audience	New media

Volk (2021) - findings (2)

Styles of communication align with implicit and/or explicit understanding of democracy:

	Floating meanings of 'democracy'
Cases	Dominant meaning	Hierarchical dynamics	Safeguarded by
Merkel	Openness of the decision-making procedures	Top-down	Governmental accountability and transparency
Kretschmer	Civil rights, especially freedom of speech	Bottom-up	Dialogue between elected representatives and citizens
PEGIDA	Civil rights, especially freedom of speech; Rule of law	Bottom-up	Citizens’ activism and protest

Volk (2021) - key assertions

Political performances of control in Germany during the COVID-19 pandemic were characterised by constant appeals to the idea(l) of democracy.
Control is something that needs to be constantly (re-)articulated in political performances.
Performances are carefully staged and purposefully disseminated discursive events that aim to articulate political meaning.

Discussion point from the news

Meta (Facebook, Instagram, Threads—3 billion users worldwide) ‘drastically reduces factcheckers and recommends more political content’

Zuckerberg intended to “dramatically reduce the amount of censorship” (framing contest: ‘censorship’ vs. ‘content moderation’)
Zuckerberg to “work with President Trump to push back on governments around the world that are going after American companies and pushing to censor more”. He cited Europe as a place with “an ever-increasing number of laws institutionalising censorship and making it difficult to build anything innovative”

Reconnecting online activism to (offline) impact

Zeynep Tufekci (UNC Chapel Hill): How online social movements translate to offline results

Two recent findings from research on online movement activity

influencers on social media can have a massive impact on elections and other political events (e.g., Rezo anti-CDU video in 2019: Klüver (2024))
deplatforming from mainstream social media platforms has a major impact on movement actors and activists (e.g., Rauchfleisch and Kaiser 2024)

Any questions, concerns, feedback for this class?

Anonymous feedback here: https://forms.gle/AjHt6fcnwZxkSg4X8

Alternatively, please send me an email: m.zeller@lmu.de

References

Diani, Mario. 2000. “Social Movement Networks Virtual and Real.” Information, Communication & Society 3 (3): 386–401. https://doi.org/10.1080/13691180051033333.

Klüver, Heike. 2024. “Social Influencers and Election Outcomes.” Comparative Political Studies, December, 00104140241306955. https://doi.org/10.1177/00104140241306955.

Rauchfleisch, Adrian, and Jonas Kaiser. 2024. “The Impact of Deplatforming the Far Right: An Analysis of YouTube and BitChute.” Information, Communication & Society, May, 1–19. https://doi.org/10.1080/1369118X.2024.2346524.

Volk, Sabine. 2021. “Political Performances of Control During COVID-19: Controlling and Contesting Democracy in Germany.” Frontiers in Political Science 3 (June): 1–16. https://doi.org/10.3389/fpos.2021.654069.

Class 11: Social Movements online, in effect, dying out, and going forward

Opening notes

Presentation groups

Theses from an earlier age of the internet (Diani 2000)

Diani (2000) - CMC

Diani (2000) - types of communication

Features and facets of internet tools

Diani (2000) - organisations and communication

Diani (2000) - theses of an earlier internet age

Diani (2000) - theses of an earlier internet age

Poll: Movements online

Poll results

Poll results

Poll results

Poll results

Movements changed by the Internet

Otpor, Milosevic, and the Bulldozer revolution

Google bombing

Google bombing

Google bombing

Google bombing

Diani (2000) - CMC’s democratizing impact

Diani (2000) - CMC’s democratizing impact

Online replacing offline activism

Volk (2021) research design

A very brief introduction to interpretive research

Volk (2021) - PEGIDA ‘virtueller Abendspaziergang’

Volk (2021) - findings (1)

Volk (2021) - findings (1)

Volk (2021) - findings (2)

Volk (2021) - key assertions

Discussion point from the news

Reconnecting online activism to (offline) impact

Two recent findings from research on online movement activity

Any questions, concerns, feedback for this class?

References