> For the complete documentation index, see [llms.txt](https://cultural-physics.gitbook.io/n/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://cultural-physics.gitbook.io/n/cultural-physics-wiki/digital-media-and-shared-perception.md).

# Digital Media and Shared Perception

### Overview

Digital media has fundamentally altered the physics of shared perception. Prior to the internet, shared perception required physical co‑presence: bodies in the same room, same street, same time zone. Cultural transmission was bounded by geography, transportation infrastructure, and the speed of word‑of‑mouth or broadcast media. Digital platforms have collapsed those constraints. A single video, recorded on a smartphone, can now synchronize the nervous systems of billions of people across all seven continents within days.

In Cultural Physics terms, digital media enables **planetary‑scale amplitude collapse**—the rapid, distributed, real‑time synchronization of perception across previously isolated fields. The digital platform functions as a **planetary gate**, controlling which amplitude peaks are amplified, which are suppressed, and which are allowed to pass through to billions of observers simultaneously. The algorithm is an **automated Gatekeeper** with no somatic stake, optimizing for engagement, not coherence.

The conundrum: digital shared perception is faster, broader, and more volatile than any prior transmission medium. But it is also shallower, more fragile, and more easily hijacked. A viral video can produce a global Heartstream in hours. That same Heartstream can decohere just as quickly, leaving behind fragmented attention, unresolved elevation, and exhausted participants.

This research brief synthesizes the external scholarship on digital media and shared perception, provides a framework for understanding the digital conundrum, and develops a research agenda for Cultural Physics.

***

### Part 1: Core Concepts – Digital Media as Perceptual Field

#### 1.1 From Physical to Digital Co‑Presence

Traditional sociology and anthropology understood shared perception as a product of physical co‑presence. Émile Durkheim’s *collective effervescence*—the intense emotional energy generated when bodies gather in ritual—required bodies in the same space, breathing the same air, hearing the same sounds, touching the same objects. Erving Goffman’s *interaction ritual* assumed face‑to‑face encounter. Randall Collins’ *interaction ritual chains* extended this framework but remained grounded in physical co‑presence as the primary mechanism of entrainment.

Digital platforms disrupt this assumption. A 2026 study integrating Interaction Ritual Chain theory and Social Identity Theory proposes a **“Three‑Stage Evolutionary Model”** explaining how individuals coalesce into cohesive “ephemeral groups” around hashtags. Shared digital content creates a **common focus of attention** that can, under certain conditions, generate group solidarity comparable to physical interaction. However, the study also identifies critical differences: digital groups are more ephemeral, require lower affective investment, and are more vulnerable to fragmentation.

**Cultural Physics translation:** Digital co‑presence is **attenuated entrainment**. The common focus of attention can be achieved across distance, but the somatic channels—breath, heart rate, electromagnetic field coupling, pheromonal exchange—are partially or entirely absent. The Heartstream is shallower, and the resulting coherence is more fragile.

#### 1.2 Digital Connective Narratives

A 2026 article in *Culture & Psychology* introduces **Digital Connective Narratives (DCN)** as a framework for explaining how large‑scale meaning‑making emerges in digital environments where group boundaries are fluid and participation is fragmented. DCNs, the authors argue, are the primary mechanism by which distributed individuals construct shared reality online.

Traditional theories of narrative assumed bounded groups with stable membership, shared history, and face‑to‑face interaction. DCNs operate differently: they are built through fragmented participation (users may engage with only a subset of the narrative), algorithmic mediation (platforms shape which narrative elements are surfaced), and temporal compression (narrative arcs unfold in hours or days, not years).

**Cultural Physics translation:** DCNs are **algorithmically mediated amplitude fields**. The narrative is not authored by a single Originator but emerges from millions of distributed contributions, shaped by platform algorithms that amplify certain peaks and suppress others. The collective collapse is not directed; it is emergent.

#### 2.3 Algorithmic Gatekeeping

The traditional gatekeeping model of journalism—editors decide what is news, what is not—has been superseded. A 2026 study on power asymmetries in the algorithmic formation of public opinion notes that “they all share the ultimate goal of influencing online visibility and shaping public opinion”. Algorithms now perform the gatekeeping function, but their criteria are not editorial judgment; they are engagement metrics: clicks, shares, watch time, comments, and the downstream behaviors these predict.

A 2025 theoretical exploration develops a framework to reconceptualize gatekeeping in the AI era, integrating classic media theories (gatekeeping, agenda‑setting, framing) with contemporary insights from algorithmic news recommender systems, LLM‑based news writing, and platform studies. AI‑driven content curation systems increasingly mediate what news is visible, sometimes reinforcing mainstream agendas while, at other times, introducing new biases or echo chambers.

**Cultural Physics translation:** Algorithmic gatekeeping is **automated basis selection**. The platform chooses which amplitude peaks to present to which users, not based on journalistic judgment or democratic legitimacy but on optimized engagement. The measurement basis is hidden, and users cannot contest it.

***

### Part 2: The Mechanics of Digital Shared Perception

#### 2.1 Viral Amplification as Phase Transition

The George Floyd video’s trajectory is paradigmatic. Darnella Frazier’s 17‑year‑old bystander recorded the murder on her cell phone. Within hours, the video had been shared millions of times. Within days, it had been viewed **over 1.4 billion times** on Twitter alone. Between May 25 and June 5, 2020, race‑ and BLM‑related videos were watched over 1.4 billion times on Twitter.

A 2026 study on “Viral Attention and Campaign Durability in Online Issue Advocacy” measures virality through the size, speed, and decay of attention spikes around trigger events. The George Floyd video produced an attention spike unlike any previously recorded: the hashtag #BlackLivesMatter was used 47.8 million times from May 26 to June 7, 2020. On May 27, just two days after Floyd’s death, the hashtag was tweeted more than 1.7 million times. The growth was exponential—not linear—indicating a **phase transition** in the amplitude field.

**Cultural Physics translation:** Viral amplification is a **phase transition in the amplitude field**. Below a critical threshold, the signal is noise; above it, the signal becomes self‑reinforcing. The George Floyd video crossed that threshold within hours. The mechanism was not top‑down broadcast but peer‑to‑peer sharing—each share was a collapse event that reinforced the amplitude peak for the next observer.

#### 3.2 Collective Emotion and Attentional Scaffolds

Social media platforms are not neutral conduits; they actively shape collective emotion through what a 2025 article calls **attentional scaffolds**. The concept draws an analogy between social media platforms and slot machines: both are “hostile attentional scaffolds” designed to capture and hold attention through variable rewards.

The article examines phenomena such as **emotional contagion** and the **emergence of group emotions**, illustrating the transition from individual experiences to shared collective outcomes. Using online moral outrage as a case study, it shows how negative emotions serve as scaffolds for individuals’ attention, propagate within social groups, and give rise to collective attitudes. The rapid spread of anger on social media platforms consumes collective attention and can lead to disproportionate shaming and bullying campaigns.

**Cultural Physics translation:** Attentional scaffolds are **synthetic Heartstream engineering**. Platforms do not merely transmit emotion; they *amplify* it through design features (likes, shares, trending notifications, algorithmic ranking). The result is a collective emotional field that is more intense but less stable than organic collective effervescence—more likely to spike and then crash.

#### 3.3 Shared Attention to Others’ Pain

A 2022 study on “The Affiliative Power of Others‘ Pain Online” found that collectively attending to others’ pain promotes affiliation among those with whom it is attended online. The George Floyd video exemplifies this mechanism: millions of people, separated by geography, simultaneously attended to the same act of violence. This shared attention generated a sense of collective solidarity that transcended physical distance.

The study identifies several mechanisms: joint attention creates a sense of shared experience; witnessing injustice together increases moral outrage; and shared outrage, in turn, motivates collective action. Importantly, the effect does not require physical co‑presence—digital joint attention is sufficient, though the study notes that the effect size is smaller than for in‑person joint attention.

**Cultural Physics translation:** Shared digital attention is **attenuated but real entrainment**. The common focus of attention synchronizes the nervous systems of observers, even without physical co‑presence. However, the synchronization is primarily cognitive and emotional, not fully somatic. The body does not entrain to the same degree; the Heartstream is shallower.

***

### Part 3: The Algorithmic Infrastructure

#### 3.1 The Attention Economy as Field Structure

Social media platforms operate on an attention economy model: user attention is the product, and engagement is the currency. This structure fundamentally shapes the amplitude field of digital content. As a 2025 analysis notes, “the algorithm rewards confrontation over construction, the chant over the policy paper, and the performance of moral certainty over the hard work of repairing reality”.

This is not a neutral design choice. It is an **optimization function** that systematically weights certain amplitude peaks over others:

| Content type              | Algorithmic weight | Cultural Physics translation                                                     |
| ------------------------- | ------------------ | -------------------------------------------------------------------------------- |
| **Confrontation**         | High               | Conflict increases engagement; amplitude peaks for outrage are amplified         |
| **Constructive nuance**   | Low                | Complexity reduces engagement; amplitude peaks for nuance are suppressed         |
| **Emotional intensity**   | High               | Strong emotions (anger, fear, joy) generate more engagement than neutral content |
| **Moral certainty**       | High               | Certainty drives sharing; ambiguity reduces it                                   |
| **Repair/reconciliation** | Low                | Resolution reduces engagement—the algorithm prefers unresolved tension           |
| **Outrage**               | Very high          | Outrage is the most engagement‑driving emotion                                   |

**Cultural Physics translation:** The attention economy is **field capture for extraction**. The platform’s algorithm does not optimize for collective coherence, social repair, or democratic legitimacy. It optimizes for the duration and intensity of user collapse—because each collapse generates data, ad revenue, and platform lock‑in. The result is a field that is perpetually elevated, never descending, and increasingly polarized.

#### 3.2 Algorithmic Activism and “Squatting the Algorithm”

Activists have learned to work within—and against—algorithmic structures. A 2026 study on “Squatting the Algorithm” examines how platform‑specific political participation on TikTok uses the platform’s unique algorithmic architecture to create new forms of digital activism. The thesis suggests that users act as **“playbourers”** who repurpose their unpaid digital labor for collective action, representing an attempt to **“squat the commodified space of social media”** and challenge platform affordances within the system.

A 2026 study on algorithmic governance and digital activism found that “activists strategically employ algorithmic affordances—such as optimized hashtag usage, multimedia content, and cross‑platform coordination—to enhance reach and engagement”.

**Cultural Physics translation:** Algorithmic activism is **counter‑field engineering**. The activist cannot exit the platform’s field (the platform controls the membrane). Instead, they learn to operate within its logic, using the algorithm’s own optimization functions to amplify their amplitude peaks. This is an arms race: the platform updates its algorithm; the activist adapts.

#### 3.3 Algorithmic Resistance

A 2026 study on Global South feminist activists’ algorithmic practices argues that “activists’ algorithmic practices serve as a form of grassroots algorithmic resistance and creative literacy, grounded in lived experiences, needs, and community‑based practices rather than formal instruction”.

The study emphasizes that marginalized communities develop distinctive algorithmic literacies that are not taught in formal settings but emerge from necessity. These include practices such as strategic blocking, coordinated reporting, hashtag hijacking, and visibility policing.

**Cultural Physics translation:** Algorithmic resistance is **decentralized field stewardship**. Without central authority or formal training, communities develop distributed practices for maintaining the coherence of their amplitude field against noise, hijack, and platform suppression. This is a form of cultural repair (Riley Mechanic) operating at the algorithmic level.

***

### Part 4: The Disinformation Counter‑Field

#### 4.1 The Fabric of Disinformation

Viral amplification is not limited to truth. A 2025 analysis of social media misinformation during protests noted that “the powerful algorithms that fuel social media platforms are feeding users days‑old and sometimes completely fake content about the recent unrest”. During the George Floyd protests, conspiracy theories circulated that Floyd was still alive, that the protests were funded by George Soros, and that Antifa was responsible for violence.

The Atlantic Council’s Digital Forensic Research Lab called the situation **“a perfect storm for disinformation”** because the same viral channels that enabled protest coordination also enabled the rapid spread of false narratives. The platform’s algorithm, optimized for engagement, could not distinguish between accurate information and disinformation—and often, disinformation was more engaging because it was more extreme or more novel.

**Cultural Physics translation:** Disinformation is **amplitude hijack**. The disinformation campaigner does not create new amplitude peaks; they *capture* existing ones, attaching false content to a charged node (the Floyd video, the protest hashtag) and using the node’s gravity to pull their own amplitude peaks into collapse.

#### 4.2 The Misinformation‑Disinformation Distinction

A 2025 analysis distinguishes between **misinformation** (false information, not necessarily intentionally so) and **disinformation** (intentionally false, intended to deceive). This distinction matters for Cultural Physics because the mechanism of collapse differs.

* **Misinformation:** The amplitude peak is false, but the Observer collapses it in good faith. The collapse is genuine, but the field is inaccurate.
* **Disinformation:** The amplitude peak is intentionally engineered to deceive. The disinformation designer is a **malignant Originator** who introduces a false amplitude peak knowing it will be collapsed by trusting Observers.

#### 4.3 Infodemics and the Pandemic Context

The COVID‑19 pandemic created what the World Health Organization called an **“infodemic”**—a massive burst of misinformation and rumors that significantly preceded the outbreak of the infection itself. In 2020, 42% of users spent more time on social networks than before the pandemic. The growth of information consumption was accompanied by this infodemic.

**Cultural Physics translation:** The infodemic is **field saturation**. When the volume of signals exceeds the field‘s processing capacity, coherence collapses. Observers cannot distinguish between legitimate amplitude peaks and noise, so they either collapse randomly (fragmentation) or retreat from the field entirely (news avoidance, disengagement).

***

### Part 5: The Positive Case – George Floyd and Digital Coordination

#### 5.1 From Hashtag to Street Protest

The George Floyd protests demonstrate the full arc of digital shared perception: from individual video to global field to coordinated physical action. As one analysis notes, “social media have become powerful tools. They allow people to connect with protest movements around the world without being physically present in the same place. That was unthinkable before”.

The Digital Forensic Research Lab documented how protesters used social media to share **operational information** throughout the protests, repurposing content from international mass‑mobilization movements. Platforms were used to coordinate logistics (protest locations, police presence, bail funds), amplify demands (policy changes, accountability measures), and document police violence in real time.

**Cultural Physics translation:** Digital coordination is **hybrid field engineering**. The digital field (hashtags, videos, posts) is not separate from the physical field (protests, marches, occupations). They are coupled: digital content entrains physical action, and physical action generates new digital content that further amplifies the field. The Floyd protests were the clearest demonstration of this hybrid mechanism.

#### 5.2 Weak Ties and Cross‑Cleavage Mobilization

Simonson and colleagues’ *Black Networks Matter* (2024) provides quantitative evidence for how social media enabled the protest explosion. The survey data show that “weak and cross‑cleavage ties among outsiders enabled the movement to evolve from a small provocation into a massive national mobilization”. Black people mobilized one another through social media and spurred their non‑Black friends to protest by sharing their personal encounters with racism.

This finding is crucial: the digital field did not merely amplify an existing movement. It **restructured the network**, connecting individuals who were not previously connected and enabling information to flow across social boundaries that had limited prior interaction.

**Cultural Physics translation:** Weak ties are **low‑resistance transmission pathways**. Strong ties (family, close friends) are high‑fidelity but low‑reach; they transmit amplitude peaks deeply but slowly. Weak ties (acquaintances, friends‑of‑friends) are lower‑fidelity but higher‑reach; they transmit amplitude peaks broadly but shallowly. The Floyd protests activated weak ties at an unprecedented scale, enabling planetary transmission at the cost of shallower individual collapse.

#### 5.3 Instagram as Node Network

A 2022 analysis of **1.13 million public Instagram posts** during the 2020 protests mapped the platform‘s role as a node network. The study found that Instagram functioned not as a broadcast medium but as a **distributed node network**: each post was a node, and the network’s structure determined which amplitude peaks were amplified. Influential nodes (popular accounts, verified users) had disproportionate power to shape the field, but even low‑visibility nodes contributed to the aggregate amplitude distribution.

**Cultural Physics translation:** Instagram was a **planetary node network**. Each post was a node, and the network’s topology determined transmission pathways. Influencers were high‑gravity nodes; ordinary users were low‑gravity nodes. The aggregate field emerged from their interactions, not from any central broadcast.

***

### Part 6: The Decay – Why Digital Fields Don’t Hold

#### 6.1 Shallow Collapse

The most persistent critique of digital shared perception is its shallowness. A 2020 analysis of the Floyd protests noted that while the protests achieved unprecedented reach, the resulting policy changes were limited. States passed nearly 300 police reform bills, but many were later rolled back. The George Floyd Justice in Policing Act passed the House but died in the Senate. The consent decree for the Minneapolis Police Department was dismissed by the subsequent administration.

**Cultural Physics translation:** Digital collapse is **somatic shallow**. The observer watching a video on a screen does not entrain as deeply as the observer marching in a protest. The heart does not race as fast; the breath does not sync as fully; the chill‑state is less intense. Shallow collapse produces shallow commitment, which produces shallow policy.

#### 6.2 Attention Decay

The 2026 study on “Viral Attention and Campaign Durability” found that attention spikes around trigger events decay rapidly—exponentially, in fact. The George Floyd attention spike peaked within days and had decayed by 90% within weeks. By the time of Derek Chauvin‘s trial, attention had declined so significantly that the verdict, while widely reported, did not produce a second spike of comparable magnitude.

This decay pattern is not accidental; it is structural. Platforms are optimized for novelty, not persistence. The algorithm surfaces new content, not old. An amplitude peak that is not constantly regenerated will decay, regardless of its importance or truth.

**Cultural Physics translation:** Attention decay is **gravity attenuation without active maintenance**. The digital field has no built‑in mechanism for reinforcement. No ritual density, no intergenerational transferability. Without active maintenance—repeated sharing, ongoing discussion, sustained organizing—the amplitude peak decays back toward the baseline.

#### 6.3 Hijack and Capture

Digital fields are not only shallow; they are permeable. A 2025 analysis of Los Angeles protest misinformation found that “algorithms that fuel social media platforms are feeding users days‑old and sometimes completely fake content”. The counter‑field is not separate from the field; it is *inside* it. Disinformation campaigns operate on the same platforms, using the same algorithms, targeting the same users.

**Cultural Physics translation:** Digital fields are **permeable without selectivity**. The membrane of a digital platform cannot distinguish between legitimate and illegitimate amplitude peaks. It admits everything, and the field must fight for coherence against competing peaks. The platform does not have a built‑in repair mechanism (Riley) for disinformation; it relies on users to report, moderators to review, and fact‑checkers to correct—all of which are slower than the spread.

***

### Part 7: The Industry Transformation

#### 7.1 Platform Hegemony

Digital platforms are no longer intermediaries; they are **field owners**. They control the membrane (content policies, community guidelines), the gate (algorithmic curation, trending mechanisms), and the amplifier (engagement optimization, viral distribution). News organizations, activists, and ordinary users are tenants on platform‑owned fields.

This shift has profound implications for shared perception. As a 2026 analysis of public opinion formation notes, “the technological infrastructure is radically changing how we access information”. News organizations that once controlled the gate (editors, producers) have lost that control to platforms. Users who once relied on trusted sources now rely on algorithmic recommendations whose basis they cannot see.

**Cultural Physics translation:** Platform hegemony is **field capture by extraction**. The platform does not steward the field for collective coherence; it extracts value from user collapses. The platform‘s optimization function is not aligned with the user’s well‑being, the community‘s coherence, or democracy’s health. It is aligned with engagement. This is not a conspiracy; it is the inevitable consequence of the attention economy business model.

#### 7.2 Algorithmic Personalization as Field Fragmentation

Algorithmic personalization delivers different amplitude fields to different users based on their past behavior. A user who clicks on outrage content receives more outrage content; a user who clicks on cat videos receives more cat videos. The result is **field fragmentation**: different users inhabit different amplitude fields, even when using the same platform.

A 2026 study on power asymmetries in algorithmic opinion formation notes that algorithms now determine “online visibility” and shape public opinion through mechanisms that users cannot see or contest. The user does not know why a particular post was shown to them or why another was hidden. The measurement basis is opaque.

**Cultural Physics translation:** Algorithmic personalization is **field fragmentation without awareness**. The user does not know they are in a different field from their neighbor. They assume their feed reflects objective reality, not a personalized amplitude distribution. This is the digital equivalent of solipsism: each user collapses their own field and believes it is the only field.

#### 7.3 The Promise and Peril of Decentralized Platforms

Decentralized platforms (Mastodon, Bluesky) have emerged as alternatives to platform hegemony. They offer greater user control, open algorithms, and community‑based moderation. However, they face significant challenges: smaller user bases, higher friction, less sophisticated features, and the same vulnerability to disinformation.

**Cultural Physics translation:** Decentralized platforms are **experiments in field democracy**. They attempt to distribute gatekeeping power across users rather than concentrating it in a single algorithmic gatekeeper. However, they have not yet achieved the scale or coherence of centralized platforms. The question remains: can a democratically governed field maintain coherence without a central Gatekeeper?

***

### Part 8: Research Agenda for Cultural Physics – Digital Media

| Research Area                             | Questions                                                                                                                                                                             | Methods                                                                                                                                     |
| ----------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------- |
| **Digital co‑presence fidelity**          | What is lost and what is gained when shared perception is mediated by screens? Can we measure the difference in Heartstream coherence between physical and digital collective events? | Comparative physiological monitoring (HRV, EEG, EDA) of in‑person vs. remote participants; cross‑platform comparison of entrainment metrics |
| **Viral phase transitions**               | What are the critical thresholds for a digital amplitude peak to transition from noise to self‑reinforcing signal? Can we predict which content will cross the threshold?             | Time‑series analysis of viral content; agent‑based modeling of sharing dynamics                                                             |
| **Algorithmic bias in field shaping**     | How do different platform algorithms (engagement‑optimized vs. chronological vs. community‑ranked) affect amplitude distributions? Which algorithm produces the most coherent field?  | Platform comparison studies; controlled exposure experiments with algorithm variation                                                       |
| **Digital field decay**                   | What is the half‑life of a digital amplitude peak? What reinforcement mechanisms (ritual density, intergenerational transfer) can extend it?                                          | Longitudinal tracking of hashtag persistence; A/B testing of reinforcement strategies                                                       |
| **Disinformation counter‑field dynamics** | How does the disinformation field interact with the legitimate field? Does disinformation accelerate decoherence, and if so, how?                                                     | Network analysis of information sharing; experimental exposure to disinformation with field measurement                                     |
| **Algorithmic activism effectiveness**    | Which algorithmic strategies (hashtag optimization, cross‑platform coordination, visibility policing) are most effective at maintaining field coherence under platform pressure?      | Comparative case studies of successful vs. failed algorithmic campaigns; platform ethnography                                               |
| **Digital shared reality measurement**    | Can we operationalize “shared reality” as a measurable field property? What are the digital equivalents of coherence, resonance, and gravity?                                         | Survey‑based shared reality scales with behavioral validation; cross‑platform field measurement                                             |

***

### Summary: Digital Media and Shared Perception in One Page

\| **Core Insight** | Digital media enables planetary‑scale shared perception without physical co‑presence—but at the cost of somatic fidelity and durability | | **Core Mechanic** | Viral amplification as phase transition; emotional contagion as attentional scaffolding; shared digital attention as attenuated entrainment | | **Algorithmic Infrastructure** | Platforms are field owners, not neutral conduits; attention economy optimizes for engagement, not coherence; algorithmic gatekeeping is basis selection without transparency | | **Disinformation** | Disinformation captures existing amplitude peaks; infodemics cause field saturation and decoherence | | **Positive Case** | Floyd protests: hybrid field engineering (digital → physical → digital), weak ties as low‑resistance transmission, Instagram as planetary node network | | **The Conundrum** | Digital fields are fast but shallow; broad but fragile; high‑amplitude but low‑gravity | | **Decay Mechanisms** | Attention decay (exponential), shallow collapse (low somatic encoding), hijack (permeable membrane), fragmentation (personalization without awareness) | | **Industry Shift** | Platform hegemony (field capture by extraction); algorithmic personalization (field fragmentation); decentralized platforms (experiments in field democracy) | | **Key Scholars** | Dobos (algorithmic squatting), Simonson et al. (Black networks matter), Prodnik (algorithmic power asymmetries), Journal of Digital Media & Society (viral attention decay), Oxford University Press (digital public opinion), Cambridge University Press (public opinion formation), Taylor & Francis (shared reality testing) |

***

### Plain Text Source List (Digital Media)

Beramendi, M. R., Morselli, D., Durrheim, K., & Torres, A. M. (2026). Beyond groups: Meaning‑making through Digital Connective Narratives. Culture & Psychology.

Bowman Williams, J., & Mezey, N. (2021). #BlackLivesMatter: From Protest to Policy. Georgetown Law Faculty Publications.

Chan, M. (2020). Digital Reality: The Body and Digital Technologies. Bloomsbury.

Dobos, E. (2025). Squatting The Algorithm: Platform‑specific Political Participation on TikTok. Dutch Art Institute.

Durkheim, É. (1912). The Elementary Forms of Religious Life.

Oxford University Press. (2025). The construction of public opinion in a digital age.

Prodnik, J. A. (2026). Power asymmetries in the algorithmic formation of public opinion. Sage Journals.

Rennung, M., & Göritz, A. S. (2019). Facing Sorrow as a Group Unites. PLOS ONE.

Simonson, M. D., et al. (2024). Black Networks Matter: The role of interracial contact and social media in the 2020 Black Lives Matter protests. Cambridge University Press.

Taraktas, B., Duran, K. C., & Uskudarli, S. (2025). Activists‘ strategic use of hashtags kept justice for George Floyd in the spotlight. LSE United States Politics and Policy.

Taylor & Francis. (2026). Shared reality theory: empirical test.

University of Vermont. (2022). Say Their Names: Resurgence in collective attention toward Black victims of fatal police violence.

Vann, S. (2026). Viral Attention and Campaign Durability in Online Issue Advocacy. Belmont University.

Wulf, T. (2025). Digital Slot Machines: Social Media Platforms as Attentional Scaffolds. Topoi.

Zhang, H. (2026). From bodily to digital co‑presence: Unpacking the Interaction Ritual Chains of hashtag‑driven group formation. ScienceDirect.