America is Split on DeFlocking Cameras

Since the Patriot Act, Americans have adjusted to additional surveillance, including cases of government overreach.Over two decades, a series of disclosures has revealed federal agencies and law enforcement building the capacity to identify, locate, and profile citizens suspected of nothing at all.

The first of those disclosures arrived in 2013, when Edward Snowden leaked thousands of National Security Agency documents to the press detailing the program PRISM, a program that collected the contents of emails, chats, and other web activity as well as another effort that gathered the telephone records of millions of Americans who were suspected of nothing at all. Then, the authority of Section 702 of the Foreign Intelligence Surveillance Act let the government collect communications of foreigners located outside the United States without a warrant and those of any American contacting them. The result is a vast repository of American communications gathered, without ever requiring the warrant the Fourth Amendment would otherwise demand.

A declassified opinion from the Foreign Intelligence Surveillance Court found that the FBI largely ignored its own rules for the use of this repository. Analysts queried the database for people connected to the January 6th Capitol breach; for participants in the 2020 racial-justice protests; donors to a single congressional campaign; journalists; political figures; ordinary protesters in recent anti-ICE protests – all queried without the required justification because their names were already in a system built for foreign intelligence and were therefore convenient to search.

The government has also purchased Americans' commercially available bulk location and behavioral data from private data brokers — information capable not only of identifying individuals and inferring their activities, but of reconstructing where they have been and predicting where they will go next. The common thread is that surveillance infrastructure built and justified for one narrow purpose becomes a general-purpose tool for looking up Americans in practice.

The boundary between privacy and trackability continues to erode through convenience. Whenever a new program or capability surfaces, Americans take to social media to argue about most every aspect: the legality, the precedent, how their neighbors should interpret it, the implications both theoretical and painfully concrete.

Figure 1: Records captured by Infegy Starscape and projected total social conversation volume regarding American privacy and government surveillance (June 2013 through August 2026); Infegy Social Dataset.

Enter the Flock

From 2025 into 2026, via social conversations as well as news one name came to dominate that conversation: Flock Safety.

Flock's automated license plate readers began as a neighborhood product, sold to homeowners' associations to help manage local security. They are now national infrastructure. By July 24, 2026, Flock's own blog claimed more than 120,000 cameras across 49 states.

This article uses post volume, sentiment, emotional analysis, and demographics to answer a question the coverage has mostly skipped. Not how many cameras exist — but who the Americans arguing about them actually are. The answer? Perhaps more similar than they realize.

This conversation didn’t take flight - it exploded

If you're a regular reader, you know our first stop is always post volume — how often people post about a topic over time, and the closest thing social data has to a measure of raw attention.

Figure 2: Post volume by month regarding Flock Safety across six audience segments (August 2025 through August 2026); Infegy Social Dataset.

Across our full window we captured 931,548 posts about Flock Safety, projecting to a social universe of 8,161,736 — Starscape's estimate of the true conversation volume once ingestion sampling is corrected for. But the shape matters more than the total:

July 2026 alone accounts for 36% of the entire year. At least five independent Flock storylines broke inside thirty days:

• The Los Angeles Police Department let its Flock contract lapse on July 11, first reported by TechCrunch on July 13. The third-largest police department in the country walked away, with its CIO citing "serious concerns around civil liberties and civil rights issues" — and a city Inspector General audit that found hot-list hits were accurate only about one time in three.
• The Supreme Court decided Chatrie v. United States on June 29, 2026, ruling 6–3 that obtaining location history through a geofence warrant is a Fourth Amendment search — undercutting the core legal defense of location-tracking infrastructure.
• CNN published a two-part investigation on July 26 and July 30 documenting roughly two dozen officers who resigned or were arrested for using Flock to stalk people. One Milwaukee officer had looked up his partner 124 times.
• Two Republican members of Congress introduced defunding bills — one on July 21 naming Flock explicitly, another announced July 25 — turning a left-coded privacy fight into a bipartisan one.
• A vandalism wave and a viral influencer moment put cameras being sawed down, painted over, and rammed with a truck onto millions of feeds.

This kind of surge isn't good or bad on its face — it signals that something significant is going on. But it carries a warning for anyone reading a sentiment chart from this period, which we'll come to shortly.

Pulling six audiences out of the flock

Figure 3: AI Personas widget describing author groups in Flock discussion; Infegy Social Dataset.

Starscape has no native "persona" field, but there is a handy AI Personas feature that we can use to quickly get a handle on the groups of people speaking out on social. We used this feature, plus some other topical information about hashtags and phrases that cropped up regularly in posts to derive 6 audiences to compare in the Flock saga.

Figure 4: Topics word cloud, sample entities, and a topics size graph in Flock discussion; Infegy Social Dataset.

Using these sources, we built out six audiences to study by self-identifying vocabulary we saw repeated and which seemed to be largely mutually exclusive. For example, an audience saying "my city council" is made of different Americans from one saying "Fourth Amendment," who is different again from one saying "sheriff's office." Here’s some of the terms used to create distinct segments:

Figure 5: Criteria used to establish six audience segments.

Birds of a feather…

After deciding on the terms, we applied each on top of the Flock subject filter. These segments overlap and do not partition the conversation — a post can belong to more than one. Here are how these groups measure out in terms of their total posting volume, and some age/gender demographic info*.

Figure 6: Audience comparisons across post volume, gender, and age (Aug 2025-Aug 2026); Infegy Social Dataset.

Size

The top two audiences are on opposite sides of the debate and within 7% of each other. Together they account for roughly 45% of the entire conversation; the other four combined are smaller than either one alone; a genuine two-sided fight between two roughly equal blocs, with four smaller constituencies pulling in different directions around them.

Age and Gender

To corroborate our hypothesis about these audiences, we analyzed the age and gender distribution of the accounts posting in each.We expected the demographic data to separate them. It does the opposite.

Male share spans 73.1% to 78.3% — a five-point range across six audiences that disagree about everything. Median age spans 34.1 to 36.9, a gap of under three years. The immigrant-rights left and the constitutional right have identical median ages of 35.3 and male shares within 1.7 points of each other.

There is no demographic axis in this fight. The Americans arguing about license plate cameras — for and against, left and right, urban and suburban — are one population: overwhelmingly male, clustered in their mid-thirties, split roughly evenly above and below 35.

Regarding the age and gender share of sampled posts, there are several caveats to highlight about these numbers:

• Age and gender are inferred from account bios and referring pronouns, and inference succeeds on only a minority of accounts — between 8.1% and 19.9% for gender and 5.7% and 17.0% for age, depending on segment.
• Some segments must be handled carefully.
  • The immigrant and crime-affected audiences are not publishable on gender, and the immigrant audience not on age either. We display it above because the sentiment and emotion metrics are so fitting.
    • • Local Government is thin enough that its figures should be rounded to whole percentages.
• Only Law Enforcement, Civil Liberties, and the Constitutional Right are comfortably measured.
• We have also omitted non-binary percentages for four of six segments, where they rest on between one and seven records.

Despite the limitations, these demographics tell us the people having the conversations share far more similarities than dissimilarities in terms of the are the same people. Let’s take a look at their tone, though.

… definitely flock together.

For a controversy this heated, we expected the anti-camera audiences to be the negative ones. That is not what the data says.

The figures below use the pre-event window, August 2025 through June 2026. That choice is deliberate and the next section explains why: only the pre-event window describes actual citizens, rather than reactions to news coverage.

Figure 7: Sentiment and emotion by audience segment regarding Flock Safety (August 2025 - June 2026); Infegy Social Dataset.

Sentiment

The two most negative audiences in the entire dataset are the pro-camera crime-affected residents (68.10%) and the immigrant-rights community (67.42%) — people who want more cameras and people who want none, statistically indistinguishable in how negatively they post, and the only two segments above 67%. Meanwhile the civil-liberties advocates, the audience a reporter would expect to be angriest, sit second-from-last.

That inversion is the most durable finding in this analysis. It holds in both windows we measured, and it should reorder how anyone reads this controversy: negativity here tracks proximity, not ideology. The people living beside the cameras — whichever way they want the policy to go — are angrier than the people arguing about the principle.

Local Government & Civic Process has by far the highest positive share at 39.38% and the narrowest negative-positive gap of any segment. The people actually sitting through procurement votes are the closest thing in this data to a genuinely undecided audience. If anyone here is still persuadable, it is them.

Emotions

Infegy IQ detects ten emotions in text: joy, trust, love, surprise, anticipation, anger, disgust, sadness, hate, and fear. Because a post can carry several, these shares don't sum to 100%.

Five of six audiences are led by anger, not hate. The exception is the civil-liberties audience, and it is the exception in an instructive direction — the segment most fluent in the language of principle is the one whose posts read as contempt rather than grievance.

The Immigrant-Rights community is the genuine outlier, and for a specific reason: it is the only audience where anticipation nearly ties anger (28.11% against 29.18%), and it carries the highest fear of any segment at 9.88% against 3.4–6.0% elsewhere. Anger plus anticipation plus fear is not the profile of an ideological opponent. It is the profile of a community that expects something to happen to it and is waiting.

We are not reporting a horseshoe, and we want to be explicit about that, because it is the conclusion this data most invites and does not support. The anti-ICE left and the anti-government right are not emotional twins: 29.18% anger against 27.43% is close, but the right's second emotion is hate at 21.37% where the left's is anticipation at 28.11%, and the left carries 9.88% fear against the right's 5.97%. They arrive at the same opponent from genuinely different emotional places.

How the news cycle flocked with the data

We measured all six audiences twice — once on the pre-event window above, once on the full year including the July–August news flood. All six changed their top-five emotion ranking. Not one was stable. And they changed in the same direction, on the same four emotions, simultaneously: Hate and Surprise both rose across all six audiences. Anger and Anticipation both fell across all six audiences.

Figure 8: Sentiment and emotion by audience segment regarding Flock Safety after July's news reports broke (July 2026 - August 2026); Infegy Social Dataset.

Six ideologically opposed communities moving in lockstep on four emotions at once. On the full year, five of six audiences appear hate-led; on the pre-event window, five of six are anger-led. Sentiment moved the same way. Every audience is more negative pre-event and more neutral across the full year, without exception.

This kind of uniform overlay is produced by tens of thousands of near-duplicate syndicated news records entering every segment at the same time. The coverage inverted the apparent emotional register of the entire debate. And enough neutral-language news content makes any negative talk seem neutral and impersonal.

The practical lesson: a volume spike driven by syndication does not just add noise, it applies a systematic and directional distortion to every emotional metric you have. Any alerting threshold built on sentiment or emotion share would have reported that this conversation was cooling during the worst six weeks of the crisis.

What this means for brand strategists and public-sector communicators

• Anger is the register, and anger is answerable. Five of six audiences lead with anger rather than hate. That distinction matters operationally: anger is directed at a decision and can be addressed through process, while the one hate-led audience is expressing a settled judgment about the category. Only the immigrant-rights segment pairs anger with high anticipation and the highest fear in the dataset — people waiting for something to happen to them.
• The demographic playbook does not apply. These audiences are one population — 73–78% male, median age mid-thirties. Segmenting this fight by age or gender will produce six identical briefs. Segment by motivation instead: principle versus proximity.
• Volume spikes driven by syndication will lie to your dashboard. July 2026 quadrupled volume while negativity appeared to drop 20 points. Sentiment did not improve; wire copy diluted it. Any alerting threshold built on sentiment share alone would have reported relief during the worst month of the crisis.

The next test arrives on a fixed date. On August 13, an announced Flock mandatory platform overhaul — retention cut from 30 days to seven, case numbers required for every search, offense-type filtering to block immigration-related queries — takes effect January 1, 2027. Whether that satisfies six audiences who cannot agree on what the problem is, we'll be watching in Starscape.