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Citation: Majic, Samantha, Melissa
Ditmore, and Jun Li. 2024. 440 Sex
Workers Cannot Be Wrong: Engaging
and Negotiating Online Platform
Power. Social Sciences 13: 337.
https://doi.org/10.3390/
socsci13070337
Academic Editor: Nigel Parton
Received: 28 March 2024
Revised: 7 June 2024
Accepted: 14 June 2024
Published: 25 June 2024
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social sciences
Article
440 Sex Workers Cannot Be Wrong: Engaging and Negotiating
Online Platform Power
Samantha Majic 1, * , Melissa Ditmore 2and Jun Li 3
1Department of Political Science, John Jay College of Criminal Justice, City University of New York,
New York, NY 10019, USA
2Independent Researcher, New York, NY 10009, USA; mhd12@cornell.edu
3Criminal Justice Doctoral Program, John Jay College of Criminal Justice and the Graduate Center,
City University of New York, New York, NY 10019, USA; juli@jjay.cuny.edu
*Correspondence: smajic@jjay.cuny.edu
Abstract: Online platforms shape and facilitate our social, economic, and political activities. Sex
workers have long pioneered their use for advertising, providing services, screening clients, collecting
payments, and peer-interaction, among other activities. To learn more about the platforms sex
workers use and how they engage and resist platforms’ power, we consider the following questions:
How and to what extent do sex workers engage with online platforms? How do these platforms’
policies and practices shape the conditions of their work? And, how do sex workers negotiate
these platforms’ power? Drawing on data from a national survey of 440 sex workers, developed
in partnership with sex workers across the United States, we found that sex workers use a range
of online platforms for their work. However, platform policies and practices often remove and/or
limit sex workers’ access, thereby restricting their ability to earn income and also compromising their
safety, and these effects stratify along the lines of race, gender, and ability. Sex workers respond to
and resist platforms’ policies through various pre-emptive and pro-active actions. Our study expands
the existing research on sex work and online platforms, particularly to illuminate the consequences
of corporate-led platform policy development and implementation for marginalized workers.
Keywords: sex work; online platforms; policy and law; SESTA/FOSTA; terms of service; payment
processor; mixed methods; de-platform; shadow banning; disability
1. Introduction
Online platforms—understood broadly as the websites that host, organize, and circu-
late users’ content, ranging from Instagram to Amazon to AirBnB (Gillespie 2018)—shape
and facilitate our social, economic, and political activities. Among their users, sex workers
have long been pioneers—in navigating the potentially negative social and legal conse-
quences of their work, they are often at the forefront of adopting and adapting to new
technologies, using these to advertise and provide services, screen clients, collect payments,
and interact with their peers, among other activities (Berg 2022;Sanders et al. 2020). Yet
even as online platforms facilitate many aspects of their work, they have not made it easier
or have eliminated its attendant risks.
Emerging research, which focuses mainly on the post-2018 era, following the passage
of SESTA/FOSTA (the Stop Enabling Sex Traffickers Act (SESTA) and the Allow States and
Victims to Fight Online Sex Trafficking Act (FOSTA)), discussed more below, indicates that
online platforms often remove sex workers from their accounts and/or restrict their access,
which compromises their capacity to earn income, screen clients, and communicate with
their peers, among other consequences (see, e.g., Blunt and Wolf 2020a,2020b;Blunt and
Stardust 2021;Burns and Benz 2023;Tichenor 2020;Barakat and Redmiles 2021;Musto et al.
2021). In so doing, platforms exercise power, which, as we explain below, we understand
Soc. Sci. 2024,13, 337. https://doi.org/10.3390/socsci13070337 https://www.mdpi.com/journal/socsci
Soc. Sci. 2024,13, 337 2 of 26
as the capacity to define and enforce “the terms of access through which large numbers of
consumers access goods, services, and information” (Culpepper and Thelen 2020, p. 288).
To expand the research on platform power and learn more about the platforms that
sex workers use and how they engage and resist their power more specifically, we consider
three related questions: First, how and to what extent do sex workers engage with online
platforms? Second, how do these platforms’ policies and practices shape the conditions of
their work? And third, how do sex workers negotiate these platforms’ power? Answering
these questions is important because online platforms play a key role in the contemporary
USA’s economy, and they have significant power to develop and implement policies
governing their users because they operate in a fragmented and incoherent regulatory
environment (see, e.g., Babwah Brennen and Perault 2023;Goldman 2023;Tiidenberg
2021). Therefore, examining sex workers’ experiences with online platforms illuminates
the consequences of corporate-led platform policy development and implementation,
particularly for marginalized workers.
Drawing on data from a national survey, which we developed in partnership with
individual sex workers and community groups across the USA, we found that sex workers
use a range of online platforms to engage in and collect payment for their work, both
virtually and in person. However, platform policies and practices often remove and/or
limit sex workers’ access to them, which, in turn, restricts their ability to earn income and
compromises their capacity to live and work safely; yet sex workers do not experience
these effects equally, particularly along the lines of race, gender, and ability. At the same
time, we also find that sex workers are not passive platform users: educated about and
attuned to many platform-related policies and practices, they respond to and resist these
through various pre-emptive and pro-active actions. To illustrate this argument, we begin
by reviewing the literature describing the socio-legal landscape that regulates platforms and
sex workers’ use thereof. Next, we explain our methods of data collection and analysis and
we present our results. In our concluding discussion, we consider how our study variously
expands the existing research on sex work and online platforms and the implications of
this for policy and future research.
1.1. Literature Review
Like many other workers in the contemporary economy, sex workers operate within
the vast online platform universe, which includes the sites that host, organize, and circulate
users’ shared content or social interactions without having produced or commissioned (the
bulk of) that content (Gillespie 2018). Defined this way, platforms appear to be neutral and
egalitarian structures that do not create content but merely “host” it; however, this is not
the case in reality (Gillespie 2010;Noble 2018;van der Nagel 2021). Because most online
platforms are for-profit enterprises that depend on ad revenue and sales of user data, they
have a vested interest in moderating “the content and activity of users, using some logistics
of detection, review, and enforcement” (Gillespie 2018, p. 21).
Furthermore, online platforms in the USA have significant power to govern their
users. As Culpepper and Thelen (2020) summarize, today a handful of large technology
companies (namely, Facebook [Meta] (Menlo Park, CA, USA), Amazon (Seattle, WA, USA),
Apple (Cupertino, CA, USA), Google (Mountain View, CA, USA), and Microsoft (Redmond,
WA, USA) and their related platforms exercise enormous influence in advanced economies:
they control access to the crucial services that many of their users depend on (see also
Rahman 2018), and the direct, intimate relationship they have with their consumers confers
“platform power” to them (Culpepper and Thelen 2020, p. 290). Through this power,
they may leverage “their loyal (in many cases, captive) consumer base into an active
public narrative and political advocacy strategy to secure legislative and legal support for
their business model” (Culpepper and Thelen 2020, p. 294). This business model relies
on and benefits from platforms’ capacities to largely self-regulate, which is facilitated in
the USA by the highly decentralized law and policy environment in which they operate
(Jhaver et al. 2023).
Soc. Sci. 2024,13, 337 3 of 26
Therefore, in light of their power within a relatively weak and fragmented regulatory
environment, online platforms are constantly developing a range of their own policies
and practices that shape the conditions under which their users live and work. However,
platform companies do not have total control here: the broader socio-legal context in which
they operate also often shapes and motivates their actions. As the following discussion
indicates, even as many online platforms have pushed for self-regulation and/or resisted
or evaded state regulation, they have succumbed to public concern about state efforts to
prevent sex trafficking. As a result, not only have government agencies and technology
companies shut down multiple platforms for sex workers, but many online platforms also
now restrict access to and ban those who appear to produce sexual content.
1.1.1. Sex Work and Online Platforms
The relationship between sex work and online platforms illustrates broader and
evolving issues of platform use, power, and governance. Certainly, technological changes—
from the automobile to the telephone, to camcorders and the DVD—have always shifted the
structure of the sex industry and, by extension, increased opportunities therein (MacPhail
et al. 2015;Koken et al. 2010). But, the internet remains the most significant force in
restructuring the sex industry and related opportunities for sex workers. Consequently,
sex work today is conducted and/or provided through online technologies (Sanders et al.
2016;Bernier et al. 2021;Jones 2015b,2020), and it encompasses what Angela Jones (2015b,
p. 560) terms “any internet-mediated exchange of sexual commodities and/or services,”
ranging from actual service delivery (such as a webcam show) to marketing for in-person
services (see also Cunningham et al. 2018).
The expansion of online technologies—and platforms in particular—has potentially
increased sex workers’ power in at least three key ways. First, they have expanded access
to sex work and, hence, income opportunities (Jones 2015b,2020;Rand 2019;Nayar
2017;Koken et al. 2010;Ditmore 2023a). Second, online technologies have lowered sex
workers’ risk exposure in a number of ways: the physical risks of full-service sex work (e.g.,
pregnancy, STIs, sexual coercion, etc.) largely disappear in webcamming or other online
spaces (Jones 2015b). Third, online communities have enhanced sex workers’ solidarity
by creating more opportunities for professional networking, peer support, and collective
organization and action, and for challenging sex and gender norms more broadly (Sanders
et al. 2019;Berg 2022;van der Nagel 2021;Feldman 2014).
At the same time, online platforms and other technologies have not eliminated risks
for sex workers. For example, customers may subject online performers to trolling (i.e.,
making deliberately offensive and inflammatory comments in an online community), and
even as sex workers may use platforms to screen clients, this reduces but does not eliminate
violence against them, particularly from clients. Moreover, online technologies such as
data analytics and facial recognition software have increased law enforcement’s capacity to
investigate and arrest persons for prostitution (Jones 2016;Campbell et al. 2019). But among
these potential dangers in the expanding online/mobile sex market, human trafficking—
and sex trafficking, more specifically—has sounded the most alarm. Concerns here are
evident in the debates about what Musto and boyd (2014) term “the trafficking-technology
nexus,” which highlights how online and other connective tools may help with trafficking
investigations and disseminate anti-trafficking information; however, abusers may also
take advantage of mobile technologies and social media to reach broader audiences across
vast geographical distances (Latonero 2011;Milivojevic et al. 2020;Fukushima 2019;Musto
and boyd 2014;Berg et al. 2020;Limoncelli 2020).
1.1.2. Law, Policy, and Platforms
The socio-legal landscape in the USA has evolved in response to the current trafficking
panic, particularly since 2000, when Congress passed the Trafficking Victims Protection
Act (TVPA). As McDowell and Tiidenberg (2023) document, while this and subsequent
laws may seem somewhat recent, they are a product of a decades-long effort by so-called
Soc. Sci. 2024,13, 337 4 of 26
moral entrepreneurs “lobbying for the creation of obscenity legislation and its ‘rigorous
enforcement’ in the United States” (p. 2). Among those involved with shaping the TVPA,
anti-sex work feminists and conservative religious figures who conflated human trafficking
and sex work—and were particularly concerned with young girls’ involvement in the sex
trades—were especially influential here (Baker 2018;Ditmore 2023a,2023b;Zimmerman
2012). Many of these anti-sex work actors also emphasized the relationship between
technology and sex trafficking in public discourse, often without distinguishing between
consensual sex work and coercive sex trafficking, and they were especially concerned that
traffickers were recruiting girls and young women into the sex trades online (see, e.g.,
Farley et al. 2014). As a result, online technologies quickly became “the new battleground
spaces upon which longstanding disagreements about sex work, human trafficking, and
the sexual exploitation of youth are enacted” (Thakor and boyd 2013, p. 279).
Nowhere are these battles more apparent than in governments’ and online platforms’
efforts to moderate, control, and ban sexual content. Regarding government actions in the
USA, various agencies have taken measures to close websites that, they allege, promoted
prostitution and sex trafficking, such as the 2014 FBI raid on and closure of MyRedbook.com
and the Department of Homeland Security’s 2015 raid and closure of Rentboy.com (Majic
2020). However, SESTA/FOSTA significantly accelerated the subsequent sex work-related
platform closures and other censorious actions by amending Section 230 of the Communi-
cations Decency Act to open platforms to criminal and civil liability where there is content
related to trafficking for sex. They also amended the TVPA to include the as-yet-undefined
“participation in a venture which has engaged in trafficking” in order to hold websites
accountable for promoting sex trafficking.
In response to SESTA/FOSTA, a number of platforms developed their own policies
and practices to avoid investigations and prosecution. To name just some examples, in
2018, Craigslist’s personals closed in March, and in April, the Department of Justice’s
Child Exploitation and Obscenity Section and the US Attorney General’s Office for the
Central District of Arizona, with support from various other state-level agencies, seized
and shut down Backpage, a site hosting classified ads, including those for escorts and other
(legal) sexual service providers. Reddit also banned four subreddits that were frequented
by sex workers, including r/Escorts, r/MaleEscorts, r/Hookers, and r/SugarDaddy, and
Tumblr introduced a sweeping adult content ban in December (soon after, Apple removed
Tumblr from its app store (Bronstein 2021)). Platforms have also taken measures to avoid
prosecution. For one, they have restricted content. To illustrate, in December 2020, Pornhub
decided to remove 10 million videos alleged to contain images depicting rape and underage
sex from its platform. Platforms have also implemented practices that reduce or eliminate
certain users. One of these is shadow banning—a cross-platform moderation technique
that restricts content deemed inappropriate, often by preventing users from appearing in
a search or by hiding users in feeds (Are 2021). And another is de-platforming, which,
generally speaking, involves removing an account on social media (or other platforms) for
breaking platform rules (Rogers 2020;Molldrem 2018).
1.1.3. Sex Work Online: Safer Now?
While both government agencies and platform companies claim that the aforemen-
tioned policies and practices will help to keep individuals safe and prevent crimes such
as sex trafficking, sex workers and other affected communities have indicated otherwise.
As early as 2015, Kristen DiAngelo and Rachel Anderson from Sex Workers Outreach
Project/Safer Alternatives through Networking and Education (SWOP/SANE) surveyed
44 sex workers in Sacramento County, finding that, after MyRedbook’s closure in 2014,
many respondents returned to street-based work, where they encountered rape or arrest,
or both (DiAngelo and Anderson 2015).
Since then, research focused on the post-SESTA/FOSTA era shows that platforms’
policies and actions have greatly compromised sex workers’ capacities to live and work
safely. For one, de-platforming measures have reduced sex workers’ income, leading many
Soc. Sci. 2024,13, 337 5 of 26
to seek more clients in public spaces, accept riskier interactions, and interact more with law
enforcement (Burns and Benz 2023;Ditmore 2023a;Blunt et al. 2021;Blunt and Wolf 2020a,
2020b;COYOTE and SWOP-Seattle 2018;Musto et al. 2021). Second, platform closures
and practices related to de-platforming have also reduced sex workers’ capacities to screen
clients, communicate with their peers, and develop social capital (Burns and Benz 2023;
Musto et al. 2021;Blunt and Wolf 2020a;Bronstein 2021;van der Nagel 2021;Lake 2018).
For example, within a day of SESTA/FOSTA’s passage, platforms where consenting adults
engaged in discussions about sexual matters were closed to sexual content (Bronstein
2021), and Blunt et al. (2020) describe how de-platforming has chilled the speech of many
marginalized groups online, particularly members of LGBTQI+ communities.
Altogether, there is a growing body of research about sex workers’ experiences with
online platforms, particularly in the post-SESTA/FOSTA era, and this research shows the
various ways in which platforms’ policies and practices to date may negatively shape the
conditions under which sex workers live and work. However, much of this research focused
primarily on the time period around the 2018 passage of SESTA/FOSTA and the closure
of Backpage and generally drew from small samples, often with limited methodological
and/or demographic descriptions. As a result, we know less about the range of platforms
that sex workers use and their experiences with them more broadly, especially since the
COVID-19 pandemic and its related lockdowns potentially moved more people into online
sex work (Ditmore 2023a). Building on the existing research to capture this information
will, therefore, provide important insights into the benefits and challenges of online work,
particularly for marginalized groups in the contemporary economy.
1.2. Anticipated Findings
Given the lack of comprehensive knowledge about sex workers’ platform use and
the relatively recent emergence of research about the ways in which online platforms’
policies and practices shape sex workers’ experiences thereon, our study is necessarily
phenomenological, inductive, and exploratory. As a result, it may seem challenging (and
epistemologically inconsistent) to pose and test potential hypotheses in response to our
research questions. With that being said, existing sex work research (including that about
sex work and online platforms) certainly urges us to anticipate certain findings in response
to our research questions, which we pose and outline below.
RQ1: How and to what extent do sex workers engage with online platforms?
The research noted above indicates that sex workers have long adapted to changing
technologies, and online platforms have increased their income opportunities, as they have
for other workers throughout the contemporary economy. We therefore anticipate that
sex workers engage with a wide range of online platforms to facilitate both virtual and
in-person sex work.
RQ2: How do online platforms’ policies and practices shape the conditions of their work?
Platforms have developed a number of policies and practices that moderate, control,
and ban sexual content in an effort to avoid prosecution, and of these, research indicates
that de-platforming and shadow banning impact sex workers (and other workers) most
directly. A long line of research (Vanwesenbeeck 2013,2017) shows that—like the majority of
workers in the contemporary economy—people engage in sex work for primarily economic
reasons, and online platforms expand opportunities here and, as the aforementioned
research indicates, potentially help sex workers work more safely (or, at least feel safer).
However, as Angela Jones (2015b) notes, studies, and particularly surveys, of sexual
labor online may present an overly homogenized impression of workers and work in this
field, particularly along demographic lines. Certainly, sex workers are not a homogenous
community, as indicated by the term “whore-archy”—a term sex workers use to describe
the pyramid with street-based sex workers on the bottom, webcammers at the top, and
various indoor sex workers located in between. And as Audacia Ray documented as early
as 2007, growing online opportunities further stratified this so-called whore-archy, with
Soc. Sci. 2024,13, 337 6 of 26
distinctions between those who advertised on Craigslist (free of charge and accessible to a
less affluent clientele) and the Eros Guide, which attracts more “professional” sex workers
and a higher-income clientele (Ray 2007).
As in any other stratified profession, the research to date (even as it is often based on
small samples) indicates that sex workers at the top of the online whore-archy are more
likely to present as white cis women, earn higher incomes, and experience less violence
from clients and law enforcement (see, e.g., Van Doorn and Velthuis 2018;Velthuis and
Doorn 2020;Jones 2015a;Rand 2019;Miller-Young 2010;Moorman and Harrison 2016).
Yet, while this research indicates how race and gender privilege may variously intersect to
shape sex workers’ experiences, as Blewett et al. write, “Studies of sex workers have largely
failed to account for how disabilities shape entry into sex work and the labor experiences
of these workers” (2022, np). Articles in their symposium indicate that sex work may be
empowering for disabled persons, particularly those who identify as trans and gender
expansive (Jones 2022;Cooper 2022); however, it also indicates that non-white trans and
nonbinary sex workers with disabilities on online platforms may face violence from not
only clients and the state but also from other sex workers (Felkins 2022).
Given all of this, we anticipate that a large portion of sex workers experience de-
platforming and shadow banning. In terms of the effects, we focused only on those related
to de-platforming (for reasons we outline below), and here, we further anticipate that
de-platformed sex workers experience income loss and are or feel less safe. However,
we also anticipated inequalities in how sex workers experience de-platforming and its
related effects on their income and safety, particularly along the lines of race, gender
identity, and ability. Specifically, we anticipated that de-platforming is more likely for
non-white sex workers than for white sex workers, gender-expansive sex workers than
for cis sex workers, and disabled sex workers than for non-disabled sex workers. In
terms of the effects, we further anticipated that income loss and safety loss are more
likely for non-white/gender-expansive/disabled de-platformed sex workers than for
white/cis/non-disabled sex workers.
RQ3. How do sex workers negotiate platforms’ power?
Extending a long line of scholarship about sex workers’ agency and political activism
(see, e.g., Majic 2014;Chateauvert 2013;Mac and Molly 2018), we anticipated that sex
workers are knowledgeable about online platform-related laws and policies, and they
variously change their behavior and even resist these policies and practices.
2. Materials and Methods
We worked with sex workers across the USA to develop an IRB (Human Research
Protection Program [HRPP])-approved (#2022-0245-John Jay, 2 December 2022) national
survey of their experiences with the online platforms they use to advertise, offer, and
collect payment for sexual services. As we describe below, this collaborative, community-
based approach to our research (for more details, see Majic and Ditmore under review)
was necessary for us to ensure that our survey reached and elicited authentic responses
from our target population: sex workers who were 18 years of age or older and had ever
exchanged sex for cash or other things of value in the USA, and used at least one online
platform for any of their exchanges.
2.1. Survey Development
To ensure that our survey was accessible and legible to the widest range of sex workers
possible across the USA, we partnered with community members who brought geographic
and racial diversity, varied levels of technical expertise, and experience in diverse sex work
venues to our project. They included two individuals who are sex workers and activists in
Oregon and New York and five representatives from sex worker organizations: the Central
Ohio Sex Worker Outreach (COSWO), which works with sex workers in the mid-west; the
Heaux History Project, which is based in Chicago and focuses on Black sex workers; Red
Canary Song (RSC), which is based in New York City and works with Asian sex workers;
Soc. Sci. 2024,13, 337 7 of 26
Community United for Safety and Protection in Alaska; and the St. James Infirmary (SJI,
which closed in March 2024, but until then was located in San Francisco and served many
people of color and a gender-diverse population).
Our community partners played an integral role in our survey development, influ-
encing topics, drafting and revising survey questions, testing the online survey and its
software (Qualtrics: Provo, Utah), and offering feedback at every stage (for more details, see
Appendix A). Altogether, the final survey asked a maximum of 103 questions (dependent
upon the responses to branching questions) that included a mix of multiple-choice and
open-text formats. Topics included sex work experience, platforms used for sex work,
experiences with platforms, including account suspension or termination, experiences
with online violence and harassment, SESTA/FOSTA’s impact on participants’ work, and
demographic questions. We did not require the respondents to answer every question, and
the respondents’ time spent on the survey varied based on their responses to branching
questions (the average survey response time was 35 min). Our high completion rate, dis-
cussed below, indicates that even though the survey was long, it did not induce fatigue for
our respondents.
2.2. Sampling
Given that much of their work is criminalized and/or stigmatized in the USA, sex
workers are a difficult population to reach for obtaining a nationally representative sample
via traditional social science research methods. Put simply, we could not buy a representa-
tive sample of sex workers from Qualtrics or, alternatively, access a directory of sex workers,
randomly sample them, and then send a survey link. Therefore, our sampling strategy
involved distributing the survey through a “post-able” link that our community partners
shared through their social media and other networks.
This strategy was valuable for two reasons: First, it would help to establish participants’
trust (for example, if they trusted the SJI for their health care, then they may also trust
a survey that the SJI shared). Second, it would reach our target population. While this
distribution method may appear limited in that it would only reach sex workers who
were online, in fact, this was reasonable and appropriate for our survey, given that we
sought to reach sex workers who have experience with online platforms. We also offered a
USD 20 incentive for eligible survey respondents (the minimum amount recommended by
community partners for our long survey). The median duration of the survey was 13.2 min
(792 s) from approximately 399 data points, while the average time spent was 35 min (with
great variation).
Our first round of distribution occurred in January 2023. At this time, the COVID-19
restrictions in the USA had ended; however, given that many people’s work shifted online
across the economy and has remained there since, more people may have been engaged
in online sex work than ever before at the time of our survey. While we cannot definitely
confirm this potentially larger respondent pool, especially given the aforementioned inabil-
ity to quantify sex workers, we acknowledge this possibility here, especially since we very
quickly received 2850 responses. But, given what we know about the extent of fraud in
online survey research, we followed the advice of survey researchers who experienced this
and took a number of steps to eliminate fraudulent survey responses and preserve data
integrity to the greatest extent possible (see e.g., Teitcher et al. 2015;Storozuk et al. 2020;
Moss and Lieb 2023;Pozzar et al. 2020;Simone 2019).
These steps included reviewing the latitude and longitude coordinates to eliminate
respondents outside of the USA, examining IP addresses in the database Scamalytics.com
to determine if they were from fraudulent sources, and assessing individual responses for
inconsistencies, among other measures (see Appendix Bfor more details). We then initiated
a second round of survey distribution through our community partners and other networks
to collect more valid responses, this time with a one-question survey asking respondents
to enter an email address. Following a review of the responses we received, where we
followed the data-cleaning procedures noted above, we then sent the qualified respondents
Soc. Sci. 2024,13, 337 8 of 26
a unique, one-time Qualtrics link to our full survey, and then we reviewed the responses to
determine their eligibility (see Appendix Bagain).
2.3. Data
As a result of these survey distribution and data-cleaning measures, we collected a
total of 440 assuredly valid survey responses, with a 99% completion rate. However, given
the challenges of confirming identities and demographic information in anonymous, online
research, we acknowledge two key issues. First, survey enthusiasts may have falsified
their eligibility. For example, fraudsters motivated to take the incentive may have gotten
through our screening process, some may never have engaged in sex work in the USA,
and some respondents could be under the age of 18, even as we required them to be over
this age.
1
Second, we did not require respondents to answer every question in order to
advance through the survey (they only had to answer the screening questions and the
questions about the types of online platforms they had ever used for sex work), and many
of our questions branched. As a result, our Ns for various responses are below 440 (our
total number of survey respondents). However, as noted above, the survey has a high
completion rate overall, with only six unfinished surveys; since answers were not required
for most questions, in the findings below, we note the total number of responses for each.
Even with a high completion rate, we had to re-code some of our variables so that we
could better parse out various aspects of sex workers’ experiences with online platforms in
statistically meaningful ways. In the following paragraphs, we briefly explain our re-coding
for gender and race, as well as two other variables (income and safety), all of which are
presented further below in the Demographics and Results sections.
Regarding gender identity, we had 12 categories for this on our related survey question,
based on consultations with community partners, and 435 of our 440 respondents completed
this question. Considering the small n in many of these categories, we collapsed the smaller
n categories of nonbinary (n = 29), transmen (n = 9), intersex (n = 3), agender (n = 3),
androgyne (n = 4), demigender (n = 3), gender-queer or gender fluid (n = 10), additional
gender category/identity (n = 4), and prefer not to disclose (n = 2), into a catch-all category—
totaling 15.4% of our sample—that we term “other non-cis gender identity” (hereafter
referred to as “other non-cis”) for the purposes of data analysis.
We also re-coded race and ethnicity: First, we did this to consolidate the smallest cells
(Asian, Hispanic, multiracial, and other) into one catch-all category (17% of respondents),
labeled “other persons of color [other POC].” Second, we re-coded race to collapse all
non-white people into one category, labeled “Black and other POC” (35.7% of respondents),
when we wanted to identify the differences between our categories of race that seemed
related to the outcomes of de-platforming but which did not return statistically significant
findings with the first re-code of race and ethnicity.
For income, we asked the respondents if their income changed after experiencing de-
platforming, and they had four response options: (1) “My income dropped a lot,” (2) “My
income dropped a little,” (3) “My income did not change,” and (4) “My income increased.”
We re-coded the response options into two categories: “income dropped” (options 1 and 2)
and “income did not drop” (options 3 and 4).
Finally, for safety, we created a new, re-coded variable (“POST DEPLAT SAFETY”) by
bucketing respondents’ top three choices: “Anxiety about my online activity,” “Feeling like
I am being watched online,” and “Felt less safe”.
2.3.1. Demographic Overview
Even though sex workers are a very hard-to-reach population, we reached a demo-
graphically diverse range of individuals across the USA who use online platforms to engage
in sex work both virtually and in person. This sample reflects that of what was collected in
previous research on this topic by Teela Sanders and colleagues, who were the first to map
online sex work by conducting the largest study of the UK’s online market of sexual labor
to date. Their survey of 641 sex workers, which used similar sampling strategies to ours,
Soc. Sci. 2024,13, 337 9 of 26
also found that the majority of respondents were women, white, sexually diverse, and aged
25–44 (Sanders et al. 2017,2019;Cunningham et al. 2018;Campbell et al. 2019). These (and
our) demographics also mirror those in the Free Speech Coalition’s recent survey of 600 sex
workers (438 in the United States), which focused more specifically on their experiences
with online financial platforms (Boden et al. 2023).
In Table 1below, we present the demographic statistics of our survey respondents
in the form of frequency distributions with 95% confidence intervals (CI). Even as our
Results section only reports our findings for the identity categories where the cell N is large
enough to make meaningful claims—gender (cis women and non-cis women, combined),
race (white, Black, and other POC; or white and all POC), and disabled and non-disabled—
given the novelty of our study, we provide a full demographic overview here so that
readers may better understand our population and a number of points we make in the
Discussion section.
Table 1. Respondent demographics.
Category % CI
Gender
- Women/cis women 64.4 59.8% to 68.7%
- Transwomen 11 8.4% to 14.3%
- Men/cis men 9.2 6.8% to 12.3%
- Other non-cis 15.4 1
Race
- White or Caucasian 63.1 58.5% to 67.5%
- Black or African American 18.7 15.3% to 22.6%
- Other POC 17 1
- Black and Other POC 35.7 1
Disability
- Yes 21.1 17.6% to 25.2%
- No 74.5 70.2% to 78.4%
- Prefer not to disclose 4.4 2.8% to 6.7%
Age
- 18–25 16.6 13.4% to 20.4%
- 26–35 56.8 52.1% to 61.4%
- 36–49 24 20.2% to 28.3%
- 50–64 2.3 1.3% to 4.2%
- 65–74 0.2 0.0% to 1.3%
Education
- Less than a high school diploma 4.8 2.8% to 6.9%
- Prefer not to disclose 3.2 1.6% to 5.1%
- High school degree or equivalent (e.g., GED) 14.1 11.1% to 17.3%
- Technical school or other certification program 10.2 7.6% to 13.2%
- Some college, no degree 19.4 15.7% to 23.6%
- Currently in college 5.3 3.2% to 7.6%
- Associate degree (e.g., AA, AS) 11.5 8.5% to 14.8%
- Bachelor’s degree 22.4 18.2% to 26.3%
- Master’s degree 6.9 4.6% to 9.5%
- Professional degree (e.g., MD, DDS, DVM, JD) 0.5 0.0% to 1.2%
- Doctorate (e.g., PhD, EdD, LLM) 1.6 0.7% to 3.0%
Place of residence 2—5 most common selections
- California 15.3 12.2% to 19.0%
- New York 14.2 11.2% to 17.8%
- Florida 6.5 4.5% to 9.2%
- Texas 6 4.1% to 8.7%
- Ohio 4.4 2.8% to 6.8%
Soc. Sci. 2024,13, 337 10 of 26
Table 1. Cont.
Category % CI
Housing status
- Renting 46.5 41.7% to 51.4%
- No fixed address 11.1 8.4% to 14.6%
- Home ownership 10.9 8.2% to 14.3%
- Living with family 9.4 6.9% to 12.6%
- Living in a hotel 9.2 6.7% to 12.4%
- Living in public housing 5.4 3.6% to 8.1%
- Staying in vehicle 4.7 3.0% to 7.2%
- Living at shelter 4.2 2.6% to 6.6%
- Camping/couch surfing/other unstable housing 3.7 2.3% to 6.0%
- Living in client’s residence 3.5 2.1% to 5.7%
- In a program that includes housing 2.5 1.3% to 4.5%
- Hospitalized 1.5 0.7% to 3.2%
- Other 1.2 0.5% to 2.9%
1
As described in the text, we re-coded gender and race to consolidate multiple categories, including “Other
non-cis” and “Other POC,” respectively, in order to increase statistical power. Our software did not calculate
confidence intervals for these re-coded variables.
2
These top five selections reflect population distribution in the
United States. The least popular choices were Alaska, North Dakota, Oklahoma, Puerto Rico, South Dakota, and
West Virginia, from which we had one response each.
2.3.2. Sex Work Experience and Income
Our survey included respondents who currently engage in sex work and/or have
done this in the past, and so to capture the respondents’ past and current sex work, we
asked them about the types of sex work they “ever” engaged in and about the sex work
they may have been doing at the time of the survey; multiple answers were allowed. We
offer these descriptive statistics about the types of sex work because they relate to our first
research question. As Table 2below indicates, our respondents engaged in multiple forms
of sex work: 373 were engaging in sex work at the time of the survey, and all 440 had
engaged in this ever, at any time.
Table 2. Types of sex work ever engaged in and current.
Types of Sex Work Ever Done,
N = 440 CI Current,
N = 373 CI
Camming/phone sex/sexting/video calls 70.0% 65.7% to 74.3% 55.0% 50.1% to 59.8%
Online content creator 44.3% 39.5% to 49.3% 36.5% 31.6% to 41.3%
Pornography 36.4% 31.6% to 41.1% 29.8% 25.2% to 34.9%
Independent escort 35.2% 30.9% to 40.0% 26.8% 22.0% to 31.4%
Strip club or erotic dance 34.5% 29.6% to 38.9% 20.4% 16.6% to 24.7%
Independent BDSM/fetish, role-playing 29.1% 25.0% to 33.4% 18.0% 14.2% to 22.0%
Sugaring 26.1% 22.1% to 30.2% 8.3% 5.6% to 11.3%
Street-based sex work 25.0% 20.9% to 29.3% 19.3% 15.3% to 23.3%
Brothel, house 20.9% 17.3% to 24.5% 16.6% 12.9% to 20.4%
BDSM/fetish, role-playing in a dungeon or house
18.2% 14.8% to 21.8% 8.0% 5.4% to 10.7%
Massage parlor 15.5% 12.0% to 19.3% 10.2% 7.2% to 13.4%
Escort agency 14.5% 11.4% to 17.7% 7.8% 5.1% to 10.5%
Other 2.7% 1.4% to 4.3% 1.3% 0.3% to 2.7%
Soc. Sci. 2024,13, 337 11 of 26
2.4. Analysis
In addition to the demographic descriptions shown in Table 1, we also analyzed the
closed-end selected choice survey responses using Qualtrics, Python (python.org, version 3),
and SPSS Statistics for Mac, Version 27.0 (Armonk, NY, USA: IBM Corp). Most analyses
were conducted with Qualtrics, but for some questions with many response options and
the possibility to select multiple answers, we used Python and Excel, particularly for our
questions about the type of sex work and types of platforms used.
We conducted a three-fold analysis to answer our research questions. First, to identify
how and to what extent sex workers engage with online platforms, we ran a univariate
analysis, which gave us a frequency distribution of selected answers to the question, “Which
types of online platforms have you ever used for sex work?” The survey listed 11 types
of platforms, from which the respondents were able to select multiple options; those who
selected more than one option were then asked, “Your responses indicate that you use
(or have used) the following platform type(s). Which one of these is (or was) the most
beneficial to you, for your business?” We ran a univariate analysis, giving us a frequency
distribution of selected answers, making it possible to discern the variety of platforms used
by sex workers in our sample.
Second, to examine how online platforms’ policies and practices shape the condi-
tions of their work, we ran univariate analyses of the questions about experiences with
de-platforming, shadow banning, and the hardships that ensued as a result of these
platform practices. In order to discern variability across sex workers’ experiences with
de-platforming and other issues related to platform access, we ran bivariate analyses
(cross-tabs) with demographic information, including race, gender, disability, and others;
statistically significant findings are presented and highlighted below.
Finally, as noted above, we anticipated that sex workers are knowledgeable about
online platform-related laws and policies and that they will variously change their behavior
in response to (and even resist) these. To discern whether sex workers are knowledgeable
and/or change their behavior, we ran univariate analyses of our questions about sex
workers’ knowledge of and responses to platform-related policies and practices and how
they may have changed their behavior because of the law and in response to losing access
to a platform.
3. Results
3.1. RQ 1. Platform Use: How and to What Extent Do Sex Workers Engage with
Online Platforms?
We anticipated that sex workers engaged with a wide range of online platforms to
facilitate both virtual and in-person sex work, and as Figure 1below indicates, we found
that the respondents used a variety of platforms while also indicating that sex workers’
preferences concentrated among certain types of platforms. Among our 440 respondents,
payment processors were the most common type of platform used (65.7%), followed by cam-
ming/phone sex/sexting/video call platforms (60.0%), chatting or other communication
platforms (56.6%), and social media (55.2%).
Among the 385 respondents to the subsequent question, “Your responses indicate that
you use (or have used) the following platform type(s). Which one of these is (or was) the
most beneficial to you, for your business?”, the most common responses were advertising
platforms (20.5%) and camming/phone sex/sexting/video call platforms (15.8%). Other
popular responses included payment processors (12.2%) and social media (12.2%), followed
by feed sites (10.1%) and chatting platforms (9.9%). (We theorize that participants may have
found it difficult to determine their most beneficial platform type, and so 55 respondents
advanced without answering this question).
Soc. Sci. 2024,13, 337 12 of 26
Soc. Sci. 2024, 13, x FOR PEER REVIEW 12 of 27
3. Results
3.1. RQ 1. Platform Use: How and to What Extent Do Sex Workers Engage with Online
Platforms?
We anticipated that sex workers engaged with a wide range of online platforms to
facilitate both virtual and in-person sex work, and as Figure 1 below indicates, we found
that the respondents used a variety of platforms while also indicating that sex workers’
preferences concentrated among certain types of platforms. Among our 440 respondents,
payment processors were the most common type of platform used (65.7%), followed by
camming/phone sex/sexting/video call platforms (60.0%), chaing or other communica-
tion platforms (56.6%), and social media (55.2%).
Figure 1. Platform ever used (N = 440).
Among the 385 respondents to the subsequent question, “Your responses indicate
that you use (or have used) the following platform type(s). Which one of these is (or was)
the most beneficial to you, for your business?”, the most common responses were adver-
tising platforms (20.5%) and camming/phone sex/sexting/video call platforms (15.8%).
Other popular responses included payment processors (12.2%) and social media (12.2%),
followed by feed sites (10.1%) and chaing platforms (9.9%). (We theorize that partici-
pants may have found it difficult to determine their most beneficial platform type, and so
55 respondents advanced without answering this question).
Figure 1. Platform ever used (N = 440).
3.2. RQ2. De-Platforming and Shadow Banning: How Do Online Platforms’ Policies and Practices
Shape the Conditions of Their Work?
Given the extent of sex workers’ engagement with online platforms, we turn now to
our second research question regarding how these platforms’ policies and practices shape
the conditions of their work. As noted above, we anticipated that a large portion of sex
workers have experienced de-platforming and shadow banning. As we explain below,
we found that sex workers were more likely to experience de-platforming than shadow
banning. Overall, 78.2% reported losing access to a platform (and/or more than one type
of platform), and the breakdown of this loss is presented in Table 3.
Our survey found that many sex workers reported losing access to a range of platforms;
however, we found that sex workers were most likely to experience de-platforming on
social media (32.0%), dating and hookup sites (24.4%), and payment processors (22.1%).
Turning next to shadow banning, we present the results in Table 4a,b. In response to
the question, “On any website you are on, is your account hidden from search results?”
Table 4a shows that we found that less than half of sex workers (43.8%) found their accounts
hidden from search results. Table 4b shows that in response to our question about tag-
ability (“When people try to tag you on social media or other platforms, does your name
show up?”), only 27.4% found their name did not show up when others tried to tag them
on social media.
Soc. Sci. 2024,13, 337 13 of 26
Table 3. De-platforming across platforms (N = 344).
Type of Platform: Access Lost Percent Reporting Lost Access
Social media 32.0
Dating or hookup sites 24.4
Payment processors 22.1
Advertising 19.2
Chat or other communication 16.9
Camming/phone sex/sexting/video calls 12.8
Review or message boards 9.0
Feed sites 5.5
Content storage 4.9
Clip stores 2.9
Tube sites 1.5
Table 4. (a) Account hidden from search results (N = 436). (b) Tag-ability (N = 435).
(a)
Response % CI
Yes 43.8 39.2% to 48.5%
No 39.9 35.4% to 44.6%
Unsure 16.3 13.1% to 20.0%
(b)
Response % CI
Yes 54.5% 49.8% to 59.1%
No 27.4% 23.4% to 31.7%
Unsure 18.2% 14.8% to 22.1%
Note: Grey background indicates statistical significance.
As noted above, the existing research indicates that platform policies and practices
such as de-platforming and shadow banning shape sex workers’ experiences and working
conditions. For the purposes of this paper, we focus below only on those effects related to
de-platforming for two reasons: first, our respondents did not experience shadow banning
(whether through hidden accounts or reduced tag-ability) at nearly the same rate as they
did de-platforming, and second, and relatedly, it is much more difficult for respondents to
definitively confirm that platforms have shadow banned them, as indicated not only by
their relatively high “unsure” responses but by the fact that platforms variously deny and
otherwise “gaslight” users about their experiences with shadow banning (Cotter 2021).
Since the previous research noted above cites income loss and a feeling of being less
safe as significant hardships for sex workers who experience de-platforming, we asked
the respondents about these effects specifically. We anticipated that de-platformed sex
workers would experience income loss and or feel less safe, and our results confirmed both
of these effects. Here, we found that of the 344 respondents who reported that they were
de-platformed, 88.4% of these respondents reported their income declining as a result.
We also asked the 344 respondents who experienced de-platforming (across a range
of platforms) to indicate other resulting hardships in addition to income loss. Across
270 respondents who responded to this branched question, Table 5below indicates that
these hardships were wide-ranging, with the most common hardships related to income
loss: a loss of clients (64.1%), a loss of subscribers (53.3%), and a loss of content they
created (40.4%).
Soc. Sci. 2024,13, 337 14 of 26
Table 5. Hardships experienced after de-platforming (N = 270).
Hardship % CI
Loss of clients 64.1 58.1% to 69.6%
Loss of subscribers and/or followers 53.3 47.4% to 58.9%
I lost content that I created (videos, etc.) 40.4 34.1% to 45.9%
Anxiety about my online activity 35.2 29.6% to 41.1%
Feeling like I am being watched online 29.6 24.4% to 35.2%
Felt less safe 23.3 18.1% to 28.5%
I increased my privacy and other security precautions online 21.1 16.3% to 25.9%
Reluctance to speak out online 19.6 15.2% to 24.4%
Lost access to recreational use of the platform (fandoms, entertainment) 17.0 12.6% to 21.5%
My housing situation became unstable 14.1 10.0% to 18.5%
Difficulty finding other work 14.1 10.4% to 18.9%
Lost access to sex workers/others who helped me with client reference checks
13.7 9.6% to 18.1%
Lost access to platforms that I do not use for sex work 12.6 8.9% to 16.7%
Increased conflict with other sex workers online 11.9 8.5% to 16.3%
More social service interactions (e.g., Child Protective Services) 11.5 7.8% to 15.2%
More law enforcement interactions (e.g., the police) 10.0 6.7% to 13.7%
Approached by madams/agencies/managers/pimps 8.9 5.6% to 12.2%
I spend more time with my in-person sex worker community 8.5 5.6% to 11.9%
Experienced exploitive work conditions 7.8 4.8% to 11.1%
Experienced abusive work conditions 6.7 3.7% to 9.6%
Immigration issues 3.7 1.9% to 5.9%
Other 2.2 0.7% to 4.1%
De-platforming also affected respondents’ safety after client and subscriber loss. Specif-
ically, here, the respondents noted that, as a result of de-platforming, they most notably
experienced feeling anxious about online activity (35.2%), feeling like one is being watched
(29.6%), and as though one is less safe (23.3%)
We also anticipated inequalities in how sex workers experienced de-platforming and
its related effects on their income and safety, particularly along the lines of race, gender
identity, and ability. Specifically, we anticipated that de-platforming is more likely for
non-white sex workers than for white sex workers, gender-expansive sex workers than
for cis sex workers, and disabled sex workers than for able-bodied sex workers. However,
we found no significant relationship between ever having been de-platformed and gender,
race, or ability.
In terms of the effects of de-platforming, we further anticipated that income loss and
safety loss are more likely for non-white/gender-expansive/disabled de-platformed sex
workers than they are for white/cis/non-disabled sex workers. Regarding income loss, we
found that de-platformed disabled sex workers were less likely to see their income drop
than de-platformed sex workers in our other sub-groups. Put differently, while we found
no statistically significant relationship between income change and race (regarding both
re-coded variables) or gender, we found a statistically significant relationship between
income change and disability; sex workers who identify as disabled were less likely to
report a drop in income after de-platforming, refuting our expectation.
Specifically, as Table 6below indicates, among the 269 sex workers who experienced
de-platforming and answered our follow-up question about changes to their income, 54
sex worker respondents here identified as disabled: fully, 31.5% of these respondents
Soc. Sci. 2024,13, 337 15 of 26
(17 out of 54) reported that their income did not drop after losing access to a platform
(p-value = 0.000866764)
. These results are quite different from those for the remaining sex
workers in this sample who experienced de-platforming and did not identify as disabled:
of these, 204 or 87.7% (179 out of 204) found their income dropped after de-platforming,
while the remaining 12.3% of respondents (25 out of 204) who did not identify as disabled
and were de-platformed found their income did not drop. (All 11 who preferred not to
disclose their disability status found that their income dropped after being de-platformed.)
Table 6. De-platformed, income change, and disability (N = 269).
(p-Value = 0.000866764, Col. %) Identified as Disabled
Did Not Identify as Disabled
Prefer Not to Disclose
Income did not drop 31.5% 12.3% 0.0%
Income dropped 68.5% 87.7% 100.0%
Count 54 204 11
Note: Grey background indicates statistical significance.
Given the overall extent of income loss, we also asked 269 respondents who experi-
enced de-platforming and answered our question about income change with a follow-up
branching question: “Did your income ever recover?” Of the 228 who responded to this,
31.6% reported that their incomes did not recover. No significant relationship was found
between “Did your income ever recover?” and ability, gender, or race.
Regarding safety loss, to conduct our analysis here, we re-coded the responses to our
question about de-platforming experiences, outlined in Table 5above. Using our re-coded
variable “POST DEPLAT SAFETY,” 57.5% of respondents described feeling more anxious,
like they are being watched, or less safe after de-platforming. We then analyzed the extent
to which de-platformed respondents’ experiences with safety in this re-coded category
“POST DEPLAT SAFETY” varied, finding here significant relationships with race and
gender. Specifically, as we outline in Table 7a,b, below, we found that those in our “other
non-cis” and “other (non-Black) people of color” categories were the most likely to feel
and/or experience a loss of safety after they were de-platformed. However, we found
no significant relationship between “POST DEPLAT SAFETY” and disability or people of
color overall.
Table 7. (a) Safety after de-platforming: differential effects (POST DEPLAT SAFETY) by gender
(
N = 260
). (b) Safety after de-platforming: differential effects (POST DEPLAT SAFETY) by race
(N = 259).
(a)
(p-Value = 0.0144, Col. %) Cis Women Cis Men Trans Women Other Non-Cis
Top 3 re-coded (“POST DEPLAT SAFETY”) 56.9 42.9 47.4 78.0
Chose none of the Top 3 43.1 57.1 52.6 22.0
(b)
(p-Value = 0.0240, Col. %) Black Other POC White
Top 3 re-coded (“POST DEPLAT SAFETY”) 49.0 74.0 55.1
Chose none of the Top 3 51.0 26.0 44.9
Note: Grey background indicates statistical significance.
3.3. RQ3. Resistance: How Do Sex Workers Negotiate Platforms’ Power?
Having found that platforms’ policies and practices shape sex workers’ working
conditions, we now present our findings about how sex workers negotiate—and resist—
platforms’ power. As noted above, we anticipated that a large portion of sex workers are
knowledgeable about online platform-related laws and policies, and they variously change
their behavior and even resist these policies and practices. As we explain below, we found
Soc. Sci. 2024,13, 337 16 of 26
that sex workers are highly knowledgeable about platform-related laws and policies and
change their behavior in order to negotiate and resist these practices.
For one example of sex workers’ knowledge of platform-related policy, 434 participants
responded to our question, “Do you know about the 2018 law known as SESTA-FOSTA?”
and of these, 70.5% reported knowing about the law. The survey then branched to ask the
306 respondents who reported awareness of SESTA/FOSTA about how they may have
changed their behavior because of the law; 302 responded to this follow-up question,
and Table 8shows the variations across the twelve response choices, among which the
respondents could check all that applied:
Table 8. Behavior change after SESTA/FOSTA (N = 302).
Behavior % CI
I increased the privacy and security precautions I take online 42.4 36.9% to 48.0%
I explored alternative platforms 36.8 31.5% to 42.3%
I stopped participating in some online forums 32.5 27.4% to 37.9%
I lost screening tools 22.5 18.2% to 27.6%
I started organizing/writing/self-identifying as a sex worker 22.5 18.2% to 27.6%
I did not change anything I did 16.2 12.5% to 20.8%
I did not self-identify as a sex worker in my political work or other issue advocacy
14.6 11.0% to 19.0%
I started and/or went back to street-based work 11.9 8.7% to 16.1%
I did not experience anything different 10.3 7.3% to 14.2%
Other 8.6 5.9% to 12.3%
I did not organize or attend a meeting or conference 6.0 3.8% to 9.2%
I stopped writing letters to the editor, articles, essays, and/or blog posts 0.0 0.0% to 1.3%
Among the 302 who answered this question about how they may have changed their
behavior in response to SESTA/FOSTA, the most common actions taken were increasing
privacy and security precautions and exploring alternative platforms. Many reported being
affected by the new law, including losing tools used to screen potential clients. However,
we also found that SESTA/FOSTA motivated sex workers’ political engagement through
organizing/writing/self-identifying as a sex worker.
We also found that sex workers informed themselves about the platforms’ own specific
policies. Namely, they read the platforms’ terms of service (TOS): 81.3% of respondents
claimed to have read the TOS for the platform that was most beneficial for their business,
with 49.1% indicating that they read the terms closely and an additional 32.2% reporting
that they had skimmed them.
When sex workers were affected by de-platforming, they did not passively accept this.
We asked how those who reported de-platforming reacted to this, and for the 312 respon-
dents to this question (which listed nine choices, including “other”), the most common
responses included complaining to the platform (49.7%), starting a new account (44.6%),
and moving to another platform (41.7%). The respondents also reported speaking out about
their loss of platform access, with 23.1% posting online about their experience and 11.2%
talking to the press. A number of respondents (4.5%) also reported paying someone who
said they would be able to restore their account.
Furthermore, in addition to resisting platforms’ practices, sex workers also “voted
with their feet” by leaving platforms voluntarily when they were not meeting their needs.
Of 438 respondents to the question “Have you ever chosen to leave a platform voluntarily?”
59.6% responded yes, and 40.4% responded no. Of those 261 who responded “yes,” we
asked them to explain why they did this, and respondents (N = 261) were most likely to
Soc. Sci. 2024,13, 337 17 of 26
leave a platform voluntarily because of “Too little engagement” (41.4%) and because the
platform was “Not meeting my target audience” (38.3%).
Yet, even as they complained and contested platforms’ policies in various ways,
sex workers did not always have favorable interactions, especially regarding payment
processors: they reported varying difficulties recovering money from payment-processing
platforms. When asked, “You indicated that you lost access to at least one payment
processor (Examples include PayPal, Venmo, etc.) Did the platform keep your money?”,
of the 52 people who responded to the question, 69.2% reported that the platform kept
their money. We asked these 36 people (69.2% of 52), “Were you able to get your money
back from the payment platform?”, and 41.7% responded no, while 19.4% responded that
they were still trying. Only 38.9% reported having recouped their money. While these
findings are not statistically significant, in the discussion, we explain why our finding about
payment processors’ retention of funds from suspended accounts is still important.
4. Discussion
Our study provides the first comprehensive survey of sex workers’ platform use in
the USA, finding that sex workers here use online platforms to offer services and facilitate
various aspects of their work (advertising, arranging dates, collecting payments, etc.),
and the most commonly used platforms were payment processors, followed by those that
facilitated communication with clients (such as those for camming, phone sex, sexting,
video calls, and chatting), and social media platforms. Given the challenges of sampling
sex workers, we cannot confirm that these data are representative of all sex workers in the
USA; however, we believe these findings are credible because they reflect those of Sanders
et al. (2017,2019,2020), who found that sex workers in the UK—a similarly advanced
capitalist economy like the USA—use a similar range of platforms.
Sex workers’ use of online platforms—and payment-processing and social media
platforms in particular—further indicates the extent to which sex work has entered the
mainstream (Brents and Hausbeck 2010;Sanders et al. 2020). That sex workers reach clients
through widely popular social media sites and, in turn, collect payments through the likes
of CashApp and Venmo indicates that it is no longer a cash-only business that operates on
the fringes of the economy. Instead, our findings confirm that—similar to other workers in
the increasingly “gigified” economy (Berg 2022, p. 35)—sex workers in the USA depend on
online platforms to facilitate their work and earn income. Most (72.4%) of our respondents
reported that they took up sex work to meet their economic needs, and they earned most,
if not all, of their income from sex work, using it to support themselves and at least one
other person.
These findings about income potentially offer broader insights into the nature of work
and the possibilities for earning income during and after the emergence of the COVID-19
pandemic and its related lockdowns. Although our respondents completed our survey
between January and May of 2023—when most jurisdictions across the USA had relaxed,
if not entirely eliminated, COVID-19-related lockdowns and other work stoppages—it is
possible that they turned to online sex work in response to COVID-19-related economic
hardships. This turn to sex work may be more significant for younger workers: more than
half of our respondents were 18–35 years old, and therefore, “digital natives” who came
of age with the expansion of internet and social media technologies, the rise of the gig
economy, and the COVID-19 pandemic. We, therefore, encourage more research about the
intersection of online sex work and economic need in the (post) COVID-19 economy to
better understand the specific hardships that sex workers faced as a result of the pandemic
(see, e.g., Callander et al. 2022).
Of course, sex workers adapted to technological changes well before the COVID-19
pandemic, and, like other workers in the contemporary economy, they rely on online
platforms. However, unlike many other workers, sex workers rely on online platforms
to mitigate risks of stigmatization and criminalization in their work, which renders them
particularly dependent on platforms. As a result, they are vulnerable to platforms’ policies
Soc. Sci. 2024,13, 337 18 of 26
and practices—particularly those created in response to concerns about sex trafficking and
the platforms’ potential liability for promoting this. Here, we found an overwhelming
majority of our respondents (78.2%) experienced de-platforming, and a significant number
also experienced shadow banning. Across platforms, we found that 41.7% indicated that
they were most likely removed from these for unallowed sexual content, particularly from
social media, dating and hookup, and payment-processing platforms.
Given that some of the largest and most powerful tech companies own many of these
three platform types—and especially those that have large user bases, such as Instagram,
Tinder, and PayPal (to name just one example of each)—it is not surprising that they are
de-platforming those they suspect of engaging in any activity that may be construed as
related to sex trafficking. However, it is imperative to note here that many sex workers
who are affected by these measures do not engage in criminal activity. To name just some
examples, creating and sharing sexual content like pornography online is legal for adults;
communicating work schedules in licit sex work venues such as strip clubs is legal; and
interpersonal communication of a sexual nature between consenting adults (e.g., sexting
and chatting) is legal.
Yet, even as all of this may be true, platform-led policies and practices—which are
ostensibly meant to protect users and prevent sex trafficking—actually compromise sex
workers in many ways. Our study, like others, shows that practices such as de-platforming
and shadow banning have deleterious effects on sex workers’ safety in an already dangerous
occupation. As shown in Table 5, “Hardships experienced after de-platforming,” when
platforms remove sex workers, they often lose income (and, relatedly, subscribers and
clients), feel less safe and more anxious online, grow reluctant to speak out online, and
lose access to their peers and to reference check assistance. Moreover, platform companies
compromise and potentially increase sex workers’ economic insecurity, as reflected in the
numbers of our respondents who reported that their housing situations became unstable
and by the numbers who also lost money to payment platforms.
But as platforms are compromising sex workers’ capacity to earn income, they ap-
pear to be enriching themselves. Payment processors merit further scrutiny here. After
terminating sex workers’ accounts, almost 60% of sex workers who responded to our
survey could not get their money back from these platforms—findings that mirror those
of The Free Speech Coalition, which found that 63% of sex workers in their sample had
lost access to financial services from a bank or another payment platform like Venmo,
PayPal, or CashApp (Boden et al. 2023). Extrapolating this fund retention rate from our
440-person sample indicates that platforms retain potentially enormous sums of money
from sex workers, all of which raise questions about their business practices more broadly.
While platforms of all sorts may set policies limiting access for people in the sex trades and
for others, financial platforms may have the greatest impact on the lives of sex workers, both
for good when they are able to use payment processors for their work, and for bad, when
financial platforms shut their accounts without warning, sometimes in response to political
pressure (Bernard 2023, TIME.COM item; Stardust et al. 2023).
However, reflecting on broader patterns of inequality in the contemporary economy,
we also found that platform policies and practices (specifically, de-platforming) do not
affect all sex workers equally. Therefore, this paper advances existing research by parsing
out variations in sex workers’ experiences with online platforms. Certainly, the fact that the
majority of our respondents are white cis women seems to preclude such an examination,
and so, to create and examine groups large enough for comparison, we separated out the
respondents who identified as disabled and grouped together some race and ethnic cate-
gories, and multiple gender categories. Here, we confirmed that the sex industry supports
many gender-nonconforming individuals, persons of color, and people with disabilities.
While we acknowledge that this grouping homogenizes diverse experiences, we also
believe it provides some initial and important findings for further examination in future
studies. Namely, we were surprised to find that there were no significant relationships
between de-platforming and race, gender, or ability; losing access to platforms seems to be
Soc. Sci. 2024,13, 337 19 of 26
an equal-opportunity experience. However, we found significant disparities in people’s
reactions to de-platforming: people in our “other non-cis” and “other POC” (not Black)
categories were more likely to report feeling unsafe online after losing access to a platform.
What does it mean that people who are not in the dominant minority—for both gender
and race—feel more anxious, like they are being watched, or less safe online? We may
speculate that these feelings are a function of their membership in groups that already
face considerable inequality and disadvantages in the broader economy, but because we
cannot state this for certain based on our survey results, we hope others will investigate this
further, potentially by conducting in-depth interviews with diverse sex workers (something
we propose and discuss further in our Conclusion).
Our findings regarding disability also merit further consideration. Heeding calls from
scholars like Blewett et al. (2022), our study expands the research on sex work (and online
sex work specifically) and disability. Specifically, our findings indicate how sex workers
with disabilities may, in fact, face additional challenges in the current online platform
environment. A total of 21.1% of the 435 respondents identified as disabled, and they were
more likely to enter sex work because they sought more accommodating work (44 of 92,
or 47.8%, versus 33.1% of people who do not identify as disabled); however, they also
earned less money than other sex workers, with more than half reporting incomes below
USD 35,000. However, we also found that even as sex workers who identified as disabled
had very low incomes, they were less likely than non-disabled sex workers to see their
income decline upon de-platforming and more likely than sex workers who do not identify
as disabled to become anxious about their online activity when they were de-platformed.
Again, we can only speculate about these findings with our survey data: possibly, their
income did not significantly drop because it was already low. But, given that persons with
disabilities generally have lower incomes than those without disabilities, the prospect of
losing more income may explain their anxiety after de-platforming. As we discuss in our
conclusion, conducting in-depth interviews with sex workers who identify as disabled may
help to explain these findings in more depth.
Yet, even as online platform-related policies and practices may (unequally) compro-
mise sex workers and the conditions under which they live and work, our findings do
highlight sex workers’ ongoing resilience and agency in the face of a hostile legal and regula-
tory environment. Put simply, we find that they are aware of legislation like SESTA/FOSTA,
and they have taken various measures to read platforms’ TOS, protect their privacy online,
move to other platforms, and explore alternative platforms. Their responses to platforms’
policies and practices thus potentially complicate Culpepper and Thelen’s aforementioned
notion of platform power, which holds that platforms leverage “their loyal (in many cases,
captive) consumer base into an active public narrative and political advocacy strategy to
secure legislative and legal support for their business model” (Culpepper and Thelen 2020,
p. 294).
Sex workers—like many workers in the contemporary economy—are certainly part
of the platforms’ captive consumer base, but their experiences with de-platforming may
challenge their loyalty to them. Indeed, one may argue here that the platforms do not
“need” sex workers to support their political/regulatory advocacy, but sex workers, like
many others in the economy, use platforms for myriad activities. Many platforms also
know that their profitability relies on sex workers to drive consumer traffic to them (even if
they do not admit it). For example, in August 2021, in response to pressure from the banks,
OnlyFans.com announced that it would ban sexually explicit content on its platform, but it
backtracked within the week after both content creators and people who purchase content
voiced their opposition to the ban (Barry 2021). (The Onlyfans.com platform was initially
used primarily by sex workers.)
Attending to sex workers’ de-platforming experiences may, therefore, help us better
understand de-platforming in the broader economy. To illustrate, de-platforming initially
happened to sex workers, with financial platforms shutting their accounts without warning
(Bernard 2023); now, other non-sex workers’ bank accounts have been closed without
Soc. Sci. 2024,13, 337 20 of 26
warning or justification (Lieber and Bernard 2023a;Lieber 2023). Losing access to financial
services this way has become so common that The New York Times published articles
describing “suspicious activity reports” and explored how banks determine whether to
close an account (Lieber and Bernard 2023b). Such examinations indicate how sex workers
are often “canaries in the coal mine,” particularly about the limits and challenges of relying
on—and failing to regulate— private, online platform companies. Given sex workers’ long
history of technical savvy and adaptation, platform companies—and scholars studying and
developing theories of their power—ignore sex workers’ needs and experiences thereon at
their peril.
5. Conclusions
Our findings have stakes for law and policy development and future research. Regard-
ing the former, our research furthers arguments in favor of repealing laws that criminalize
sex work for consenting adults (particularly anti-prostitution laws). Among sex workers,
scholars, and advocates, there is an ever-growing consensus that these laws do little to
help sex workers live and work safely (see, e.g., Albright and D’Adamo 2017;Amnesty
International 2015,2016;Decker et al. 2015), and our results indicate how de-platforming
has similarly negative effects. Our study thus furthers arguments in favor of repealing state
and federal laws—and, by extension, corporate policies like de-platforming—that effectively
criminalize prostitution and other forms of sex work. Here, SESTA/FOSTA should also
be repealed: this law does not prevent trafficking, and our data are the latest in a growing
line of studies confirming that it counterproductively renders people more vulnerable to
coercive or dangerous labor, especially those from vulnerable groups.
If lawmakers are going to expand online platform-related laws and policies, our
findings support enhancing those governing platform companies. In short, platforms need
more regulations that reduce their power and prevent them from harming workers rather
than restricting content. For example, payment-processing platforms should not be allowed
to keep people’s money when they have not committed a crime or otherwise violated the platform’s
terms of service. This is important not only for sex workers—especially marginalized people,
including racial minorities, disabled, and gender-non-conforming people who rely on this
work to support themselves and their families—but for many more people who depend on
online platforms for income. However, in developing any policy related to online platforms
(and, relatedly, sexual labor), we strongly suggest that lawmakers consult with sex workers
first—they need to be key advisors on policy because they know their needs best.
Given our findings and recommendations, we suggest the following for future research.
First, we encourage scholars to engage in more in-depth, qualitative research so that we
may develop more intersectional analyses of sex work online. While our study parsed
out variations in sex workers’ experiences based on race, gender, and ability, we did not
consider how these markers of identity may interact by assessing, for example, how the
experiences of sex workers who identified as both racial minorities and disabled compared
with white, non-disabled sex workers because our numbers here were too small to draw
meaningful conclusions. We therefore encourage more qualitative work—particularly that
involving in-depth interviews, following Felkins (2022)—to capture these experiences.
Second, we also encourage more research about online sex work and disability. Our
findings that sex workers who identified as disabled have low incomes and were less
likely to report a decline in income after their de-platforming presents opportunities for
further exploration into their financial strategies and whether and to what degree sex
work supplements their other income sources, if any. Also, our survey did not ask our
respondents to specify their type of disability if they identified as such, and more data
here could be instructive. For example, how and to what extent do persons with cognitive
disabilities experience de-platforming and the effects thereof differently from those with
physical disabilities?
Third, we encourage more in-depth, qualitative research on shadow banning. While
we found that sex workers reported being shadow banned, it is difficult to draw conclusions
Soc. Sci. 2024,13, 337 21 of 26
about the extent and effects of this because platforms have denied its occurrence. Moreover,
even as users can see that their accounts and related activity are suddenly less visible to
their audiences, this may have multiple causes, including but not limited to shadow bans,
the quality of their content, and changes to platform algorithms that determine what is
shown to others.
Finally, we hope that researchers will further develop more wide-reaching, compar-
ative, and international studies of sex work online. Although we surveyed sex workers
across the United States, our survey was conducted in English; reaching those who speak
a range of languages would have further diversified our respondent pool and our data
about sex workers’ experiences online. Furthermore, given the emerging evidence of how
SESTA/FOSTA and de-platforming shape sex workers’ experiences outside of the United
States (see, e.g., Burns and Benz 2023;Tichenor 2020;Barakat and Redmiles 2021), further
studies to this end will expand our knowledge about how sex workers experience and
navigate platform power in and across different regulatory contexts.
Author Contributions: Conceptualization, S.M. and M.D.; methodology, S.M. and M.D; software,
M.D. and J.L.; validation, S.M. and M.D.; formal analysis, S.M. and M.D.; investigation, S.M. and
M.D; resources, S.M.; data curation, S.M. and M.D.; writing—original draft preparation, S.M. and
M.D.; writing—review and editing, S.M., M.D. and J.L.; visualization, M.D.; supervision, S.M.; project
administration, S.M.; funding acquisition, S.M. All authors have read and agreed to the published
version of the manuscript.
Funding: This research was funded by the Woodhull Freedom Foundation (administered by the City
University of New York [CUNY] Research Foundation as Grant #7H381-0001). We received additional
funding from the Office for the Advancement of Research (OAR) at John Jay College-CUNY and the
Professional Staff Congress-CUNY grant program (Award # 66725-00 54). The APC was funded by
the OAR at John Jay College-CUNY.
Institutional Review Board Statement: The study was conducted in accordance with the Declaration
of Helsinki. The study was approved by the Human Research Protection Program of John Jay
College-CUNY (#2022-0245-John Jay, 2 December 2022).
Informed Consent Statement: Informed consent was obtained from all subjects involved in the study.
Data Availability Statement: Data available upon request from the authors.
Acknowledgments: Amy Adamczyk, Margaret Bull Kovera, Tara Burns, Marisa Day, Angela Jones,
Mona Kleinberg, Ashley Lake, Alexandra Lutnick, Zein Murib, Andrew Proctor, Elle Stanger, mem-
bers of the Women and Society Seminar at Columbia University, participants in Cornell’s Political
Science and Sandwiches colloquium, and colleagues at the American and Western Political Science
Associations’ Annual Meetings provided invaluable feedback on this project and/or various drafts of
this paper.
Conflicts of Interest: The authors declare no conflicts of interest.
Appendix A. Community-Based Research
We used community-based research (CBR) methods to develop a national survey
of sex workers’ experiences with the online platforms they use to advertise, offer, and
collect payment for sexual services. CBR is an intentionally collaborative, change-oriented,
empowering, and decolonizing research practice that promotes understanding of intractable
issues by engaging hard-to-reach populations who are most affected by them (Strand et al.
2003;Dierckx et al. 2020). Employing CRB techniques was important to us, given not only
their capacity to increase access to research participants and data but also because they
challenge historical injustices in research.
Our community partners each signed a Memorandum of Understanding (MOU) with
the CUNY Research Foundation, detailing their anticipated contributions to the survey
creation process and their compensation for this participation. Overall, some were very
available and interested in the entire process, while others only engaged in parts thereof. We
first developed a draft of potential survey topics and sample questions for our partners to
Soc. Sci. 2024,13, 337 22 of 26
review. Based on their feedback, we refined our topics and questions and presented them in
a more formal survey format to our partners for review again. Altogether, we met remotely
with some community partners once and with others twice, and these meetings, which
focused on survey development, lasted approximately an hour (and we often followed up
with questions as they arose after the meetings).
Following this community review, we programmed our survey into Qualtrics for
testing. Four community partners recruited people to test it (COSWO, CUSP, Heaux History,
and the SJI). One partner, Red Canary Song, did not share the survey with testers because
their community largely does not communicate in English, the language of the survey.
Altogether, we tested the survey with 14 sex workers from around the country, including
every time zone in the contiguous states. We incorporated all of their feedback into the final
survey, including specific terms and questions recommended by our community partners
and the survey testers they recruited. In these substantive ways, sex workers not only
actively shaped the survey design, but in doing so, they drastically improved our survey.
Appendix B. Data Cleaning
Initially, for the first round of survey distribution, which received 2850 responses, we
used Qualtrics fraud detection, which identified nearly 1200 (of 2850 surveys) as “good,”
meaning that they were not duplicate responses or bots. We then drew on existing research
and advice about data cleaning in the age of survey fraud to further review the 1200
“good” survey responses, which involved the following steps. First, we examined all
the respondents’ IP addresses (Bowen et al. 2008) to identify the location of a person
and/or their internet service provider (ISP), excluding here the responses from identifiable
data centers and ISPs known for engaging in fraud and scams (using Scamalytics.com
scores). Next, we excluded the survey responses that took too little time to complete the
survey (Buchanan and Scofield 2018); in our case, based on our survey testing, this was
less than 7 mi. We also checked the respondents’ latitude and longitude, eliminating all
respondents outside of the United States (with the exception of respondents near the USA–
Canada border). Finally, we reviewed the remaining responses, identifying others that were
duplicates and/or inconsistent and/or non-sensical (Dupuis et al. 2020;Godinho et al. 2020).
For example, here we eliminated surveys where respondents reported that they created
online content but then did not report using any online content creation platforms. We kept
211 of the 2850 responses for the first round of distribution; this 7 percent validity rate is
similar to the 3–5% valid response rate found by others (Pozzar et al. 2020;Simone 2019).
For the second round of survey distribution (the survey collecting email addresses),
we received a total of 1066 responses to this survey over three months, and as they came in,
we met weekly to review the IP addresses, latitude and longitude, and Scamalytics.com
scores, and to eliminate blank responses and duplicates. As a result of these efforts, we sent
503 eligible respondents a full survey link and received 329 responses; of these, we kept
229 responses for a 70% validity rate.
It is also worth noting that we did not require the respondents to complete all fields,
and most omitted only their demographic information, while one stopped earlier in the
survey. We retained six incomplete surveys that included information about online platform
use but omitted their demographic information. Despite our efforts to review and clean our
data consistently, we acknowledge that we may have eliminated some valid responses that,
for example, may have been completed quickly by humans or were otherwise eliminated
through our other criteria. However, given the immense propensity for fraud in online
surveys, we believe our cautionary measures are merited.
Note
1
We believe harms any respondents under the age of 18 would be minimal, given that we did not require respondents to answer
all questions, and we anonymized our survey data (per IRB requirements).
Soc. Sci. 2024,13, 337 23 of 26
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