The Study

Our project explores sentiments of public safety in New York City’s Subway system grounded on four pillars: policy, data, media, and notions of the public. This research emerges from the heightened reporting around high-profile random acts of violence at the tail end of 2024. Despite historic reductions in transit crime (NYPD, 2025) and the low statistical probability (about 1 in 500 (Chalfin et al., 2024)) of falling victim to a crime in the Subway, fear mongering has bolstered the feeling of unsafety underground justifying the resurgence of broken windows policing. The incongruence between crime data and militarization call into question policy responses (what/who is being securitized or criminalized and why) and the role of mass media in manufacturing consent (Herman and Chomsky, 1988) and representing the public. According to MTA’s Fall 2024 Customers Count survey, 56% of customers indicated they felt safe on trains, an increase from 45% in the spring. Regardless of the data, the new year and tailwind of news headlines from 2024 presented an opportunity for the mayoral office and NYPD to crack down on crime, directing over 200 officers underground, in addition to the 2,600 cops already stationed in the Subway (Lane, 2025) and 1,000 National Guardsmen (Heyward, 2024), “to do speciality train patrols” as “part of a strategy to refocus our Subway efforts to the places where crime is occurring” (Tisch, 2025).

If: “The Subways will be a bellwether for the perception of public safety in New York City” (Tisch, 2025), the statistical data in crime reporting alone cannot explain the atmosphere of un/safety, nor do they validate the responses in policy programming and the weaponization of carceral tactics. Given Police Commissioner Tisch’s insistence on a data-driven approach to policing, we investigate transit crime and ridership data over a 3-year period and how these are interpreted and communicated through policy-making and news outlets to inform and govern public space and sentiment. This study seeks not to determine whether the public believes the Subway system is safe. In reality, the reviews are fairly split fluctuating with shifts in news cycles and policy agendas. Rather, we present a narrative of safety that is governed by policy, data, media, and (manufactured) sentiments of the public. Our research is thus guided by the following questions: what are the real causes of the perception of un/safety and how do they accommodate for the militarization of NYC’s Subway system?

Public Order... For Whom?

Public transit has been understudied in urban planning and design, invisibilized underground as public infrastructure left to the attention of engineers and economists (Tuvikene et al., 2023). However, as North America’s largest transportation network with over 3 million riders daily (MTA, n.d.), embracing the MTA Subway system as infrastructure and public space opens up opportunities to explore the social significance of spaces – “what is, can be, or should be public in the city” (Tuvikene et al., 2023:2964). While public space “is as much present as always in becoming in (contested) processes” (Iveson, 2007 in Tuvikene et al., 2023), the carceral control of underground terrain raises questions over who has the right to the city (Harvey, 2019)? More specifically, who has the right to “claim some kind of shaping power over processes of urbanization” (ibid.,:5), the extent of a space’s publicness, why it matters, and for whom?

Our study draws upon a longer history regarding the role of the police in relation to the public considering recent momentum to securitize the transit system through carceral techniques. In the 1990s, patrolling public (dis)order occupied the central agenda of the NYPD where untended property became the site of securitization under the broken windows theory (Manguel, 2025). Conceived of by Kelling and Wilson (1982) and popularized by then Mayor Rudy Giuliani, broken windows theory punishes low-level “crime” suggesting that “untended behaviour” would lead to rising, especially violent, crime. Policing dis/order thus became the logical response to quell perceptions of rising threat while justifying the diversion of public resources into the department as the means and ends to maintain public order, effectively criminalizing poor, working-class, racialized communities.

This is of particular concern today with the crackdown on low-level quality-of-life “crimes” (aggressive panhandling, smoking or drinking alcohol in the Subway, lying on Subway seats, fare evasion) (Lane, 2025). Broken windows theory works hand-in-hand with deterrence theory where increased police presence is posited to increase perceptions of risk and apprehension, thus deterring disorder, danger, and crime (Roberts et al., 2024). The effects of deterrence theory have been critiqued (ibid.), conflating increased arrest rates, through the increased exposure and interaction of and with police, as improvements in perceptions of safety. As congestion pricing is expected to further increase ridership, the slippage between public order and public safety raises concerns over class and race inequities in controlling, accessing, and creating public space.

A Trip Through Time

Our study is situated in the reported Subway happenings between January 2022 and April 2025, a time period that avoids the bulk of COVID chaos and coincides neatly with the start of Eric Adams' tenure. In so doing, we provide a survey of events in a manner that begins to blend epistemologies of public order. While we cannot speak to causality in the web that is public policy formation, policing, journalism, and social media, even an unearthing of (dis)agreements are an effective way of probing the sculpting of public opinion and mechanisms of state power.

The interactive window below pulls from various multimedia to paint a temporal trajectory of policing in the Subway system and public perceptions of safety. As you scroll down, the column on the left cycles through every New York Times headline since 2022 covering the Subway. Headlines that are more alarmist are highlighted in orange (the next section contains more detailed methodological information and an infographic summary). The column on the right contains synopses of key events juxtaposed with related footage from citizen videos and institutional news outlets. The sources of these short clips are listed in the references section, and are not limited to the New York Times.

Media Mania

Institutional media and law enforcement are chicken and egg, so attempting to decouple them is a neverending distraction. They reference one another perpetually, creating a feedback loop that is both key in disseminating information publicly, but also prone to excluding said public in the processes of publishing stories or formulating policies.

In this study, the New York Times is used momentarily as a proxy for institutional media writ large. The authors acknowledge the limitations of this choice. In a longer-form project, the perspectives of other journalistic outlets would be considered. Here, the Times is chosen because of its ubiquitous and purported neutral stance (whether or not this is valid is debatable).

In order to systematically create an overview of Subway sentiment, every archived local or regional New York Times article published between January 2022 and April 2025 is scanned via the NYT API , and the following key metadata are saved to a table: timestamp of publication, headline, abstract, and banner image URL. From this collection, articles whose headline or abstract contain the word “Subway”, “MTA”, or “transit”, are saved as a subset. Then, headlines from this subset are manually combed through and tagged if they seem to stoke a sentiment of fear. This designation comes from an admittedly subjective emotional response heuristic. Generally though, if an incident is graphic in nature and/or public safety is mentioned in a headline, it is marked.

A time series collapsed bar chart below visualizes this media data, and select callouts earmark some of the more sensationalized stories of the last few years. It is perhaps no surprise that the isolated and horrific acts of violence have more sustained news cycles and eye-catching headlines. The widest blocks of orange in the companion visualization tend to follow such stories. In contrast, sparser media coverage follows policy announcements around increased police in the transit system, the deployment of the National Guard, and even the September 15th, 2024 incident where police opened fire on a fare evader at a Brooklyn station, gravely injuring an uninvolved bystander. Many orange streaks following this latter incident are unrelated to it; rather, they are court appearance rehashings of the May 1st, 2023 murder of Jordan Neely.

Speaking of Jordan Neely, his murderer Daniel Penny was acquitted of all charges and widely celebrated by factions of the right for his self-claimed handling of a public threat (Schnitzer & Pelletier, 2024). The truth is that Jordan Neely was the exact victim of systemic discard that rendered him vulnerable to public hatred in the first place (Chan, 2023). While “mentally ill people are more likely to be the victim of a violent crime than to commit one” (Harris et al., 2023), law-and-order rhetoric has in many cases re-invigorated public support of broken windows theory. Just this year, Brooklyn District Attorney Eric Gonzalez said “quality-of-life issues, when left unaddressed, can erode public confidence and fuel a sense of disorder,” (NYC.gov, 2025), and it is exactly that word, disorder, that seems to be the media’s master key into facilitating the paradox of simultaneous increases in police presence and alleged decreases in violent incidents according to the NYPD.

The Dec 22nd, 2024 immolation of Debrina Kawam was in a sense the culmination of manufactured public sentiment that had been festering since the worst of COVID lifted. Some painted her as the face of the unhoused and parroted the sentiment that people using the Subway system for shelter should be forcibly removed. Others used the Guatemalan perpetrator as a springboard into broad strokes diatribes against Latin American migrant populations.

In both Neely and Kawam’s cases, it is clear that the media capitalized on the magnitude of the event, stoking slippery and unproductive public discourse, while doing little to foster a forum of dialogue around modern policing and its dearth of compassionate methods.

Big Data Policing

The NYPD has increasingly used urban informatics to justify their decisions, especially around ballooning budgets and hiring (Vera Institute, n.d.). These statistics often take the form of rushed self-congratulations, depicting a decrease in serious index crimes over some chosen month year over year (Kuntzman, 2025). While terms like "crime", "arrests", and "disorder" are often used in these reports, they are not clearly defined. As a result, they move from being numerical instruments to metonymic sleights of hand - for instance, "disorder" might be construed to signal the unhoused or migrant populations (Chronopoulos, 2017). The catch-22 of urban policing is bulldozed by the following rationale: we see a decrease in crime as we define it, we attribute this to police work, therefore, we hire more police as a precautionary measure. Such weaponized "precautions" lead to more liberal and casual uses of force by the police. As with the cycle of broken windows policing in the late 20th century, a lack of experimental control renders associations between police presence and reported crime prone to being spurious (Chronopoulos, 2017). To prod at some of the less visible data infrastructure underpinning the mainstream narrative, some spatial analysis follows.

Arrests are taken to be a proxy for police activity in this study, because other ancillary citizen information is either out of date or unavailable. This is a systemic limitation. Arrest data spanning 2022 through 2024 are downloaded from the NYPD’s data portal as well as the City of New York’s historical arrest records. These are stitched together in ascending order and filtered to the subset of arrests where the jurisdiction code is 1.0, signifying transit. These transit records are then categorized into quality-of-life (comprising violations and misdemeanors) and felony arrests.

Dividing the arrest count by the MTA’s averaged daily ridership volume between 2022 and 2024 normalizes patterns across the city. This aggregation is performed at the community district level to strike a balance between data point counts and granularity. After further roll-ups to month-level precision, we generate a time series choropleth of both quality-of-life and felony arrests across our 36-month study window. Visible in the below video, the number of quality-of-life arrests broadly increases across New York's community districts over time. This is most pronounced in areas like East Brooklyn or the South Bronx, which are already sites of perpetual disinvestment (Susaneck, 2024). They are also geographically far from the high-traffic stations of Manhattan Hochul so keenly deployed the National Guard to (Allen, 2024). The left two still maps in the frame are provided for visual context around the demographic nature of the areas of New York that see the highest rates of transit over-policing. Data is presented on a generic low to high spectrum - the left two maps use Jenks natural breaks, while the third uses normalized quantiles across its temporal range, so as to fairly assess the 2-year evolution.

According to the row-wise NYPD data, quality-of-life arrests went up 77% from 2022 (4864) to 2023 (8617) and 96% from 2023 to 2024 (16929) respectively, citywide. At the same time, felony arrests went up 29% from 2022 (1834) to 2023 (2374) and 22% 2023 to 2024 (2887). Given Subway ridership has been between 1 and 1.2 billion yearly since 2022, the relatively accelerated progression in policing statistics is notable. In addition, it is bizarre that the official crime statistics offered by the MTA deviate from tabulations of the disaggregated NYPD records. Looking only at felonies between 2023 and 2024, their summary claims a decrease from 2337 to 2211 (NYPD, 2025), while this study tallies an increase from 2374 to 2887.

In a recent statement from Hochul celebrating the one year anniversary of her "Safer Subways" initiatives, she boasts that major transit crimes are down 29% while arrests are up 71% year to date and that major transit crimes are down 28% compared to the same period in 2019 (Governor Kathy Hochul, 2025). This period of analysis is not defined, the supposed correlation between crime reduction and arrest increase is taken for granted, and the nature of said arrests is left open - given the magnitude of the statistic, it almost certainly includes quality-of-life arrests. Is this really about public safety, or is it about trying to reconcile two pieces of self-serving information - that the police are effective in the Subway system, and that we need more of them to make sure it stays that way.

Again, because the authoritative summary statistics do not offer a definition of “crime”, incongruences are likely not methodically resolvable. They do add to a concerning trend of data cherry-picking by the NYPD in their high-level reporting (Baker, 2017 and Dyson et al., 2024). Thus, it takes a frankly privileged level of systems thinking to critique the effectiveness of police at stopping actual violence on the Subway, and the simultaneous but unrelated uptick in quality-of-life arrests in New York's more disenfranchised neighborhoods.

Kareem's Subway Takes guest in the opening video asks such questions, but many other people don't, and this is not necessarily their fault. We are all fed competing narratives, often ones that don't benefit us, and the only way to disentangle this web of plural truths is by talking to each other.

Citations

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Baker, A. (2017, December 13). City Police Officers Are Not Reporting All Street Stops, Monitor Says. The New York Times. https://www.nytimes.com/2017/12/13/nyregion/nypd-stop-and-frisk-monitor.html
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Data Sources

Clips used in the opening video are as follows:

CNBC Make It. (2023, March 5). I Make $86K A Year as a Subway Conductor in NYC | On the Job. [Video]. Youtube. https://www.youtube.com/watch?v=qrtUToXqbCE
Governor Kathy Hochul. (2022, October 22). Governor Hochul Makes a Subway Safety Announcement. [Audio]. Youtube. https://www.youtube.com/watch?v=gReTbZuvFko&t=1s
Governor Kathy Hochul. (2025, May 1). Governor Hochul Announces Budget Investments to Protect Subway Riders and Transit Workers. [Video]. Youtube. https://www.youtube.com/watch?v=gC_cM3ZDrYw&t=4s
Hambrecht, P. [peterhvideo]. (2024, March 6). The National Guard searching bags at the entrance to the Grand Central subway station. [Video]. X. https://x.com/peterhvideo/status/1765553068823675048
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Jay-Z. (2021, December 4). Empire State of Mind ft. Alicia Keys. [Video]. Youtube. https://www.youtube.com/watch?v=vk6014HuxcE
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SubwayTakes with Kareem Rahma. (2024, October 26). Cops on the subway makes us LESS SAFE! [Video]. Youtube. https://www.youtube.com/watch?v=hcrvRlHwL08
The Tonight Show with Jimmy Fallon. (2025, January 13). Subway Busking with Bad Bunny. [Video] Youtube. https://www.youtube.com/watch?v=kj_c4bOA7-4
Worrell, G. (2024, November 16). Meet the woman who blows kisses to unsuspecting subway riders in NYC - see how they react. [Video]. New York Post. https://nypost.com/2024/11/16/lifestyle/meet-the-woman-who-blows-kisses-to-unsuspecting-subway-riders-in-nyc-see-how-they-react/

GIFs in interactive timeline tool are, from top to bottom:

Tenor Gifs, Giphy News, CBS New York, NBC New York, CBS 2 New York, coolchickslovemike on YouTube, ABC 7 New York, The New York Times, FNTV, Forbes, WPIX New York, Forbes, Spectrum News New York, ABC 7 New York, FOX5.

Arrest data on transit for the video triptych of maps is from:

City of New York. (2024, April 26). NYPD Arrests Data (Historic). Retrieved from https://catalog.data.gov/dataset/nypd-arrests-data-historic
NYPD. (2025, January 27). NYPD Arrest Data (Year to Date) for the Year 2024. Retrieved from https://data.cityofnewyork.us/Public-Safety/NYPD-Arrest-Data-Year-to-Date-/uip8-fykc

The Subway ridership data used to normalize the arrest data is from:

MTA. (2023). Subway and bus ridership for 2023. MTA. https://www.mta.info/agency/new-york-city-transit/subway-bus-ridership-2023
MTA. (2025, March 5). MTA Subway Hourly Ridership: 2020-2024. Retrieved from https://data.ny.gov/Transportation/MTA-Subway-Hourly-Ridership-2020-2024/wujg-7c2s

Demographic data for the triptych is from:

NYC Opportunity. (2019). Data Tool - NYC Opportunity. Www.nyc.gov. https://www.nyc.gov/site/opportunity/poverty-in-nyc/data-tool.page
NYC Department of the Aging. (2020). Demographics by Neighborhood Tabulation Area (NTA). https://www.nyc.gov/assets/dfta/downloads/pdf/reports/Demographics_by_NTA.pdf

* The New York Times archive is scraped using API access and Python tools, but no particular article is singled out as a source because the aggregate is what we analyzed. For now, the Times is credited generally as a publisher.