“Nothing will stop the sluts now”: Analysing women's support for image-based abuse websites on social media

Abstract

The abrupt closure of a popular website which hosted image-based abuse in April 2012 triggered a robust social media response. Most posts on Twitter expressed a positive opinion about Is Anyone Up? (IAU) and its “revenge porn” business model. These tweets were not just posted by men, with around one-third of the 2,967 tweets about the website on the day of its closure linked to the profiles of women. This article assesses the 1,030 tweets posted about IAU by identifiably female accounts in the 12 hours after the website shutdown. It assesses the levels of support for image-based abuse among women and compares the nature of this support with responses of Twitter users who are identifiably male, or those whose gender could not be determined. It considers factors such as the impact of online disinhibition on the prevalence of online mockery, especially within pre-existing misogynistic frames observable on social media. It also discusses the perception among women that image-based abuse served as an informal control on sending “nudes” and, on that point, how women were divided as to whether the closure of the site should be treated as a positive or negative development.

Keywords

Image-based abuse sexual violence cyberdeviance cybercrime online harms revenge porn

In the Internet era, it has become easier than ever to victimise people via the non-consensual distribution of sexual images and/or video, now recognised as a form of “image-based sexual abuse” (McGlynn & Rackley, 2017). In the past, this practice was colloquially referred to as “revenge porn”—a misleading descriptor because it does not accurately reflect the real breadth of reasons that underpin perpetration (Henry et al., 2021). The term revenge porn became established in the public discourse in the late 2000s and early 2010s, assisted by the rise of websites like Is Anyone Up? (IAU). Owned and operated by online entrepreneur Hunter Moore, IAU's business model was based on users submitting sexual content of themselves or, often, others—typically, without their consent (Jacobs, 2016). IAU's initial cult following soon transitioned into more mainstream popularity, with an estimated 240,000 visitors each day at the peak of its notoriety in early 2012 (Dodero, 2013). Just as its ascendance was rapid, so too was IAU's decline. With no warning, the website went offline at noon on 19 April 2012, after Moore sold the domain to anti-bullying organisation Bullyville. The closure prompted a robust reaction on social media, with users flocking to platforms like Twitter¹ to express their opinions, both on the end of the website and its sociocultural impact more generally. In the 12 hours after IAU was closed, a total of 2,967 tweets referencing Is Anyone Up or IAU were posted, offering a snapshot into public sentiment towards not just this specific website, but also perspectives on image-based abuse.

In this article we explore the response of a specific group to IAU's closure: women. Out of the 2,967 tweets about IAU posted on 19 April 2012, a total of 1,030 were posted from accounts in which the person was identifiable as a woman, amounting to 34.72% of the full data set. The full sample of tweets was thematically coded to determine how women felt about IAU and, where positive sentiment was expressed for the website, what motivated this support. Codes were divided based on whether they were applied to posts that came from Twitter accounts operated by individuals who identified as women, with this subsection then compared against the full data set, and the sample of codes applied to posts from those not identifiable as women (either posters who were identifiable as men, or where it was not possible to ascertain gender identity). Gendered estimates about the prevalence of image-based abuse vary significantly as a function of how the associated behaviours are defined (see Eaton et al., 2018; Powell et al., 2022a, 2022b). However, there is a consensus in the literature that image-based abuse has a greater impact on women than men (Bates, 2017; Ging & Siapera, 2018; Henry et al., 2019; McGlynn et al., 2021). Despite women experiencing considerable affects from image-based abuse, a high percentage of the tweets included in this research from women were positive towards IAU: 733, or 71.17%, of tweets posted by identifiably women were coded as being supportive towards IAU.

In this article, responses from posters identified as women are compared against the full data set to develop a better understanding of the way women interacted with the website, and how this differed from men. The role played by popular media in normalising image-based abuse, as IAU did in the early 2010s, is also considered. Normalisation, even commodification, of image-based abuse is important to consider because of the potential impact this has on shaping norms around what constitutes appropriate social behaviour. As Suler (2004) theorised, this is a matter which has been increasingly destabilised since the internet and new communication technologies like social media platforms have become ubiquitous. The findings reveal a complex relationship with image-based abuse among women, who conceptualised IAU as a form of entertainment or source of sexual enjoyment at generally equal rates as men. However, the data also indicates that women were more likely to see IAU as a platform which served a social purpose as an informal control on the sending of nudes, predicated on mocking and body-shaming those who were posted—men and women alike. These findings have implications not just regarding nuances in support for websites like IAU, but also the specific ways in which an understudied group like female consumers interact with image-based abuse content.

Literature review

Image-based abuse is broadly defined as “the non-consensual creation and/or distribution of private sexual images [or videos]” (McGlynn & Rackley, 2017, p. 534). This practice has historically been referred to using the colloquial term revenge porn based on the belief that non-consensual distribution of sexual material was “typically done in ‘revenge’ following the breakdown of a relationship” (Salter & Crofts, 2015, p. 233). While the conceptualisation of image-based abuse as revenge porn remains prevalent in the public discourse, McGlynn et al. (2017) argue that “by focusing only, or mainly, on the paradigmatic case of the vengeful ex-partner, legislatures have failed to consider the range of abusive practices resulting from [image-based abuse]” (p. 26). While the victims of image-based abuse may identify as any gender, the research is in general agreement that a “sexual double standard prevails as the abuse meted out typically castigates women for traversing expected norms of femininity and sexuality” (McGlynn et al., 2017, p. 30). Building on McGlynn et al.’s (2017) construction of image-based abuse as a behavioural continuum, as well as the earlier work of Powell and colleagues (2018), Mortreux et al. (2019) developed a typology of image-based abuse based on qualitative interviews conducted with both perpetrators and other stakeholders. Their categorisation acknowledges that the most common form of image-based abuse is relationship-based, in line with traditional perceptions of revenge porn. However, they also identify several other forms of image-based abuse such as sharing images and/or videos where a victim is identifiable (not relationship-based), where a victim is not identifiable (such as the forwarding of “dick pics”), child sexual abuse material (CSAM), or sharing of images and/or videos of strangers taken without consent (“upskirting” or “downblousing”).

The work of Mortreux and colleagues provides further insight into the diversity of motivations for sharing image-based abuse, including on websites like IAU. However, it does not explain the popularity of image-based abuse for consumers of this material, where the motivations are naturally distinct. In their ground-breaking study of image-based sexual abuse perpetration, Powell et al. (2019) found that one in 10 participants in a large Australian sample self-reported having engaged in at least one of 24 related behaviours, ranging from taking non-consensual images and/or video to distribution of (or the threat to distribute) image-based sexual abuse material. A similar multinational study found the self-reported image-based abuse perpetration rate to be even higher with one in six self-reporting one or more related behaviours, with the odds of perpetration increased if a person was a man or boy, expressed attitudes that minimised the impact of image-based abuse, or had experienced image-based abuse themselves, among other factors (Powell et al., 2022a). Research on the response of “bystanders” suggests that although witnessing image-based abuse online may be common, relatively few individuals reported taking action to intervene (Flynn et al., 2022a). Further, there were distinct gendered differences in who was more likely to intervene, with men far less likely to take action because they do not generally perceive the abuse as being as severe as women do (Flynn et al., 2022b).

This provides a possible gendered explanation for inaction, but not for the proactive enjoyment of image-based abuse. In their research on a popular image-based abuse website, MyEx.com, Hearn and Hall (2018) found that “consumers who enjoy this material are able to displace responsibility, since it is not they who have humiliated the pictured [person] … it is not they then who are the monsters, but other [people] who are posting these images” (p. 868). In additional work on the same website, Hall and Hearn (2019) make connections between the rationalisation of image-based abuse and acts of male peer support referred to as “manhood acts”—whether framed explicitly as a way to “get back at” the person featured in the image and/or video or presented as “no big deal”, this act becomes a method of hurting or controlling women while, at the same time, protecting or rehabilitating a perpetrator's manhood. Consumption of image-based abuse is thus characterised as an acceptable form of homosocial exchange and the harm being committed is normalised, or even affirmed, within a predominantly male community (Hall & Hearn, 2019).

Ging and Siapera (2018) observe “that digital technologies do not merely facilitate or aggregate existing forms of misogyny, but also create new ones that are inextricably connected with the technological affordances of new media … and the individuals and communities that use [it]” (p. 516). They go on to argue that, aside from the clear continuities online misogyny has with traditional “in-person” versions, “it is also intensified and amplified in online environments … [and] we can observe new dimensions of or additions to misogyny, that may end up spilling over to other domains of life” (Ging & Siapera, 2018, pp. 518–519). Research into the rates of misogyny on Twitter emphasises that abuse is often not limited to gendered slurs and posting abusive content (like image-based abuse material), but also the “discrediting [of] reports of violence against women” as a means of minimising legitimate complaints about online violence against women and girls (Dehingia et al., 2021, p. 1). Using a data set of tweets from the same general period as this research, Fulper et al. (2014) found that increased rates of misogynistic language by users on Twitter correlated with higher rates of sexual violence in the same locations that posters came from. This suggests there may be a direct link between online misogyny and offline attitudes and/or behaviours, which is important when considering how perceptions of an image-based abuse website like IAU is important in a broader social context.

Jane (2012) uses the term “e-bile” to describe the specific form of misogyny that has emerged in cyberspace, characterised as “the extravagant invective, the sexualised threats of violence, and the recreational nastiness that have come to constitute a dominant tenor of Internet discourse” (p. 532). On this, Huber (2022) concurs with Hall and Hearn (2019) in relation to the importance of manhood acts in reinforcing and maintaining misogyny online. Referencing the similar work of Dekeseredy and Schwartz (2013), Huber notes that deterrence of online misogyny is especially challenging in cases where communities of male peer support exist and is “particularly the case when friends condone or overlook forms of abuse, rather than calling men out, alongside the knowledge that they are unlikely to [be] arrested for such behaviour” (2022, p. 14). When considered in conjunction with Flynn et al.'s (2022a) work on bystander responses to image-based abuse, it becomes clear that the reluctance to intervene when image-based abuse occurs perpetuates a cultural silence that allows misogynistic online communities to flourish, potentially contributing to the widespread popularity attained by websites like IAU.

Most literature on image-based abuse is focused on male perpetration and consumption of sexual material that is distributed without consent. However, this study is primarily concerned with women's responses to IAU—a subject not covered to the same extent in the current research. Examining how frequently misogynistic words like “slut” and “whore” were used across 1.46 million Twitter posts, think tank Demos found that around half came from accounts operated by women and girls, suggesting an overarching “cultural and societal issue of women and girls using this language” (Laville, 2016). Further, the Demos research specifically notes that, when misogynistic language was used by women and girls, it was often paired with body-shaming language (e.g., “fat slag” and “skinny bitch”). This is notable for the current research, considered that much of the discourse centred on IAU was tied to mocking the physical appearance of those posted on the website, most of which could be characterised as body-shaming (Morczek, 2017).

Suler's (2004) online disinhibition theory asserts that the dissociative anonymity and interpersonal mediation provided by online platforms often result in people acting in ways online that they would not ordinarily in an “offline” context. Though this may, to some extent, explain a willingness to deviate in cyberspace, it does not explain the specific misogynistic nature of this deviation—especially in the context of women's support for image-based abuse websites like IAU (Ging & Siapera, 2018). Moloney and Love (2018) addressed the question of women as perpetrators of online misogyny, noting that women who participate in this behaviour “tend to replicate … prescribed and highly cisnormative and heterosexist patterns” (p. 5). Speaking directly to the issue of image-based sexual abuse, Salter and Crofts (2015) assert that—within the aforementioned framework—victims are seen “as a small group of ‘dumb’ women who failed at the neoliberal project of self-management” and are judged more critically as a result, including by other women (p. 235). Flynn et al. (2023) also identified a sexual double standard observable in this area: their research highlighted a trend wherein “women were pressured and expected to engage in sexting, but then blamed and punished for doing so” and that this was not a social response experienced by men. Gendered constructs around sex are foregrounded by Henry and Flynn (2019), who argue that image-based abuse “is a vehicle for the construction, performativity, and negotiation of hypermasculinity and heteronormativity, within the bounds and structures of existing gendered power relations” (p. 1932). Although these dynamics undoubtedly favour men, this does not mean that they are not also propped up or reinforced by women, like those who expressed support for IAU and its operational model. The extent to which the women represented in the data that is explored in this article reinforce misogynistic power structures will be a key focus, with the goal of contributing to a currently weak evidence base on this subject.

Methods

Data collection

Data was collected from the social media platform Twitter using the website's name (Is Anyone Up) and widely used acronym (IAU) as search terms. Although a simplistic approach that may not have captured every tweet related to the website, the benefits of using these parameters were that the results also captured any tweet referencing or responding to the official IAU Twitter account (@is_anyone_up) or using the hashtag #IAU, which added to the overall number of tweets returned. Twitter was selected based on the platform's relative popularity during the period being studied (2012), as well as due to the fact that IAU's official account was highly active on Twitter as a means of promoting the website, which resulted in a strong following (Patchin, 2011). The date that IAU closed (19 April 2012) was chosen as a focal point to search for social media responses about the website, with the presumption that a major event like this would prompt both a considerable response rate, and one that was more about the website itself, rather than about the content it was posting. Initially, the intent was to capture tweets for a five-day period after IAU closed down; however, during the initial process of data collection, it became apparent that saturation would be reached long before that based on the extremely high response rate in the immediate wake of IAU's closure. The website was shutdown at 12 p.m. (U.S. Eastern Time) on 19 April 2012 and, in the 12 hours that followed this, a total of 2,967 tweets were collated.

Data analysis

All tweets were copied-and-pasted into a Microsoft Excel spreadsheet to undergo further analysis. During this process, a series of notes were made in the column next to the tweet where further context was required. This occurred in cases where tweets were accompanied by an image and/or video, with the notes describing what additional material was included with the tweet. Notes were also made where a tweet was posted by an identifiably female user. This was determined on a case-by-case basis through further exploration of a user's social media profile, and only noted where gender was made explicit by the respondent—whether in the tweet itself, or on their profile page (e.g., in the biographical section). Admittedly, this is an interpretive process, and it is impossible to be exact in the identification of women on social media, for a variety of reasons—for example, a considerable number of Twitter profiles are anonymised, and users often do not provide personal information such as gender identity. There is also the potential that a user's gender identification has changed in the decade since posts about IAU were made in 2012, in which case the gender expressed on a user's profile may no longer reflect that of the same user in 2012. Nonetheless, it was possible to assess gender identity in many cases, with 1,030 tweets were identified as having been posted by user's identifying as women—34.49% of the total sample.

The tweets in the full data set were thematically coded as a means of capturing the “core consistencies and meanings” related to the response to IAU's closure (Patton, 2002, p. 264). For the most part, the first round of thematic coding was inductive, with the first author performing hand-coding all tweets and creating a bespoke “codebook” as the process continued. Beginning with inductive coding was the most appropriate approach considering the robustness of the data set, and the high probability that a diversity of subthemes would emerge as a result (Cascio et al., 2019). There was only one instance in which codes were deductively applied on initial coding: the code femaleposter was applied to all tweets that were annotated as being made from identifiably “female” users during the initial data collection. This code was applied deductively to allow for filtering later in the process, providing the opportunity to isolate responses based on gender and identify differences based on this variable. After initial coding was completed, a secondary coding process took place wherein the second author used the codebook that was developed during the initial coding to deductively cross-check all code applications, with any changes and/or queries resolved via peer consultation following the secondary coding process (Scharp & Sanders, 2019).

Percentage agreement between coders was 99.4% across the full data set, with 46 specific code applications flagged, and resolved in consultation between the coders at this point. After this process was complete, a master list of 46 individual codes was finalised, including the femaleposter code which is most relevant to this article (see Appendix). Within the femaleposter subset, the remaining 45 codes were applied a total of 2,388 times across the 1,030 tweets. Once coded, data was categorised into a variety of thematic groups based on individual codes with identifiable similarities, such as codes expressing a positive sentiment towards IAU versus those expressing a negative sentiment towards the website, as well as other subcategories (e.g., mocking and/or discriminatory tweets; tweets about nudes during and after IAU shutdown; tweets referencing boredom). These thematic groupings allow for clearer analysis of the data, and identification of trends and patterns in responses to IAU's closure. Not all codes were categorised into one of the five thematic groups; however, this is not a reflection on their relevance to the data analysis. Several codes were important to understanding sentiment towards IAU but nevertheless eluded classification into a broader thematic category. These notable individual codes will be dealt with in the result section under “Additional Observations”.

Ethics

Because this research was based on open-source data, not direct interaction with participants, it was treated as exempt from full ethics review by the researcher's home institution. Even so, there are several ethical considerations that must be considered in this type of research into online behaviours, regardless of institutional exemptions. The research conducted took the form of a non-participant digital ethnography, an emergent qualitative method where the ethical landscape is unsettled. As Thompson et al. (2021) observe, critical questions remain as to whether digital ethnography constitutes the study of documents (i.e., written product and publicly available online) or people (i.e., the creators of those products). They note that “machine learning algorithms and artificial intelligence tools may pose particular risks for vulnerable [Internet] consumers due to a lack of ethical decision-making framework” (Thompson et al., 2021, p. 1). This was a consideration in the decision to not use machine learning techniques in data collection or analysis, with each tweet collected manually by the researchers, and sanitised to remove any identifiable information, including Twitter usernames. With limited exceptions, most tweets were produced by a unique user, with very little repeat commentary from the same accounts. Because of this, it was considered unnecessary to allocate pseudonyms to users, as there were no patterns of behaviour and/or rhetoric that were being analysed, and each tweet stood on its own as a piece of data without needing to be connected to an individual person.

No data were collected from Twitter profiles that were locked, archived, or otherwise private—all material is freely available to any person, with or without a Twitter account. Despite this material being public, steps were taken to minimise identifiability when it came to use of quotations. Quotes were used sparingly and, where they are used to provide context to the coding process, have either been parsed slightly or selected to come from accounts where users’ offline identities are not easily discernible. Two researchers conducted interpretive coding. The first is a white cisgender and heterosexual man who was a young adult when IAU was active and, consequently, had prior knowledge of the website's existence. The second coder is a white cisgender and heterosexual woman who was several years younger at the time IAU was active, and unaware of the website until research commenced. Both coders were also users of Twitter prior to this research, and as such were aware of platform-specific norms and language before commencing data collection and analysis.

Results

In the full data set of 2,967 tweets, a total of 8,214 applications were made based on a master list of 46 distinct codes. When categorised based on commonalities, several thematic groups were formed out of these codes. Table 1 outlines the thematic groups, which codes were a part of each grouping, and the difference in frequency between the full data set and the subset of femaleposters.

Table 1.
Thematic groups and frequencies in full data set and femaleposter subset.

Thematic group Codes included Frequency in femaleposter subset (n = 2,388) Frequency in non-identifiable and/or male subset (n = 5,826) Frequency in full data set (n = 8,214)

Positive towards IAU proIAU; proHunter; sad; endoftheworld; wherewilligetpornnow; wasfun; mad; whatwillidonow; continue + newsite; continue + Twitter; leavingtheInternet; neverforget 1,304 (54.6%) 2,733 (46.91%) 4,037 (49.15%)

Negative towards IAU antiIAU; antihunter; getoverit; abouttime; happy; disappointedinIAU; CSAM 241 (10.1%) 435 (7.47%) 676 (8.23%)

IAU as an informal control on sending nudes morenudesnow; notsubmitted + relief; blamesubmitters 70 (2.93%) 120 (2.1%) 190 (2.31%)

Mocking and/or discriminatory mocking; misogynistic 129 (5.4%) 260 (4.46%) 389 (4.74%)

Boredom boredom; whatwillidonow 108 (4.52%) 136 (2.33%) 244 (2.97%)

Note. IAU = Is Anyone Up?

Thematic groups: positive and negative towards IAU

The high rate of women offering support for IAU was simultaneously one of the simplest and most noteworthy findings in the data. Whereas the percentage of codes in the positive towards IAU thematic group came to 49.15% in the full sample (men, women, and gender undetermined), this rose to 54.6% after being adjusted to only include posts from women. The rate of positive towards IAU codes was much lower for identifiable men or posters of undetermined gender identity, registering at 46.91% of that sub-sample. For example, in the women's subset, 10.1% of codes were in the negative towards IAU thematic group compared with 7.47% in the men or undetermined gender subpopulation. While women recorded different rates to the men/undetermined sample in other thematic groups as well, this was typically held to a difference of 1 to 2%, making an almost 8% disparity notable. This runs counter to the logical hypothesis that women would be less likely to demonstrate positive sentiment towards a website trading in image-based abuse, with one study suggesting that as many as 90% of victims are women (Ging & Siapera, 2018). The rate is even higher when a direct comparison is made between the singular proIAU code and women: the proIAU code was applied a total of 733 times in the femaleposter data set, out of the total 1,030 (71.17%) posts from women. With most women expressing explicit support, this is actually higher than the men and/or unidentified category where there were 1,170 proIAU codes applied across 1,937 tweets for a rate of 60.4%–10.77% lower than it was for women.

Thematic group: IAU as an informal control

Comments that conceptualised IAU as an informal tool that disincentivised people from sending nudes were captured in a separate thematic group, IAU as an informal control on sending nudes. For this theme, the rate of codes applied in the women's subset (2.93%) was far closer to that in the men and undetermined gender population (2.1%). When each individual code in this thematic group is considered, the most frequently applied code was where a poster expressed relief at not being featured on IAU (notsubmitted + relief). This was included in the thematic group, as it implies that the poster themselves had a concern or fear of the implications of their nudes being posted on the website, thereby indicating a recognition of IAU's role as a social control. From a total of 61 tweets coded notsubmitted + relief, 33 were posted by women, or 54.1%. Tweets with this code included “now I can sleep better knowing I wouldn’t see myself on the site” and “I [w]as juuuust talking about how I’m afraid I’m next [to be posted]”. One pattern that emerges within this thematic group is a suspicion from women that IAU's closure may not be legitimate and, instead, could be a scam intended to incite women to send nudes again. One woman speculates that “I feel like @is_anyone_up going away is just a ploy to make people feel safe, send noods [nudes] and then BAM jk [just kidding] EVERYONE GETS POSTED!” Another concurs, stating “What if @is_anyone_up is pretending to shut down so nudes can be sent freely, only to be put on the site again. #conspiracy IT'S NOT SAFE”.

When exploring the differences between men and women who posted tweets that were coded morenudesnow, a pattern emerges which reflects a difference in perspective as to whether an increase in nudes is a good thing or not. Only 25 posts from women referred to there being more nudes sent without IAU's repressive effect, out of a total of 89 (28.1%). For men or posters whose gender could not be determined, morenudesnow was frequently applied in cases where posters were positive about the increased ease of soliciting nudes from others. For women, the morenudesnow code was mostly applied to tweets where posters made explicit reference to feeling freer to participate in sexting themselves, showcasing an acknowledgement that IAU had prevented them from engaging previously based on a fear of being posted. For example, one poster writes that “the only good thing about @is_anyone_up being shut down is not having the fear of being posted on it” while another says that “now, the world can send nudes again without being terrified anymore”.

The final code in this thematic group, blamesubmitters, also demonstrates a disparity between the rate of application to tweets from women, compared to the overall data. In the overall data, 30 tweets were coded as blaming the people who submitted sexual images (with or without consent) for being featured on the website. A trend in the tweets coded in this thematic group was for women to make a comment about the people who were submitted (or submitted themselves) to the website, offering a cynical take on this group. In a refrain that was repeatedly observed, one poster writes that “hopefully ppl [people] learned a damn lesson not to send nudez to sketchy ppl in the first place”. In the women-only subset, there were only 12 tweets that were coded this way representing 17.14% of the tweets posted by women featured in this thematic group. This indicates a relative lack of focus on those involved in the non-consensual distribution of images, and a potential lack of recognition of the experiences of victims of image-based abuse—if, indeed, the practices engaged in on IAU were perceived as “abuse” at all, which was not observed among the posters in this sample.

Thematic groups: mocking and/or discriminatory and boredom

It is not just in the areas where the data on women diverge from the complete data set that inferences can be made, but also in places where it is reflective of the complete data set even where it may not be expected to be. This is certainly the case when it came to the mocking and/or discriminatory thematic group, where the rate of tweets linked to women (4.52%) was in close alignment with the percentage for this thematic group in the men and undetermined gender subset (4.46%) as well as the full sample (4.74%). What must be considered is whether there is an expectation that women would be underrepresented in this thematic group, since it might be reasonably assumed that men would be far more likely to use misogynistic and discriminatory language targeting women. If this is the assumption, the fact that the representation of women in this thematic group was largely in alignment (in fact, slightly higher) than the men or undetermined gender subset is notable because it suggests that women in the sample engaged in misogynistic language at a similar rate to even though such rhetoric is, by definition, designed to demean and disempower people of their same gender.

Another thematic group where there was a notable difference between the women-only subset and others was Boredom, where women accounted for 108 posts out of 244 total, whereas the men and undetermined group accounted for 136 posts. Tweets in this thematic group often expressed concern that IAU had shut down for pragmatic reasons, posing questions such as “what the fuck do I do from when I wake up until I go to sleep now?!” or “how am I supposed to pass my time now that Is Anyone Up? is gone?” For many, it appears that IAU performed a defined role at some point in their day as a means to help users “get through” some kind of tedious activity—for example, some asked “What am I going to do in class #officiallydepressed” or “What am I going to do at school now” with others identifying different activities that would be impacted by the closure such as “now I have to find something else to kill my boredom at work” or “now what am I supposed to do on the morning bus ride”. While the men and undetermined gender group outpaced the women's group in raw terms when it comes to Boredom-related posts, this observation flips when the numbers are considered as a proportion of the total subsets. For women, Boredom codes made up 4.52% of the total subset, but for the men/undetermined group, this rate was just 2.33% of the total, indicating that women saw IAU as a source of entertainment at a rate almost double that of the comparative sample.

Additional observations: Complex feelings about IAU among women

The code revengeporn was not included in any thematic group; however, it was applied to tweets where (1) the term was explicitly used; or (2) there was a direct reference to revenge as a motive for submission. Overall, just 97 tweets in the full sample were coded revengeporn, accounting for 1.19% of all codes applied. Of these 97 code applications, 20 were linked to women—just 0.84% of codes applied to tweets from women, and slightly lower compared to 1.32% of the men or undetermined gender subset who made reference to this term and/or concept. This is an important observation, as it is linked to the uneven perceptions of what IAU represented, with a strong percentage of the sample not connecting the website to image-based abuse directly. Notably, even though the difference is admittedly small, a lower percentage of women seemingly made this connection than the men or undetermined gender group, providing additional context to the discussion of how women interacted with and perceived IAU at the time the data was produced.

A total of 35.3% of tweets posted by women did not express a clear sentiment towards IAU, positive or negative. However, a closer reading reveals that, rather than no sentiment whatsoever, these tweets reflect complex feelings about the website's closure. One reflective example of a tweet where sentiment could not be firmly established reads “Its kinda bittersweet that @is_anyone_up is gone. Definitely one of those things this generation won’t forget”. Another tweet reflecting mixed feelings about IAU closing states “Dangggg @is_anyone_up is gone now. Never thought the day would come”. Others did not express a sentiment one way or another, but posted to make a comment about whether or not they were posted on the website—most from women expressing a sense of surprise (or relief) that their sexual images were never featured on IAU before it closed. One such tweet simply reads “I somehow never got posted on isanyoneup before it shut” whereas another tweet reveals that the poster “escaped being posted on @is_anyone_up”. Even though use of the term “escaped” implies that the poster feels that being featured on IAU would be a negative thing, this only speaks to their own desire not to be submitted to the website, rather than constituting a value judgement on the website itself, and as such negative sentiment cannot be ascribed to comments adopting this tone, which were common within the women-only data subset.

Another area where women expressed mixed opinions on IAU's closure was when it came to their views on never having their sexual images submitted to and/or posted on the website. As noted above, notsubmitted + relief was applied to 33 tweets posted by women, meaning that women represented a slim majority of posters who expressed this sentiment (54.1%). However, this was not the only code that was applied related to not being submitted: notsubmitted + regret was applied to tweets where the poster expressed disappointment or some form of unhappiness that IAU closed before they could be featured. Overall, there are 44 tweets coded with notsubmitted + regret in the data set—20 of these tweets (45.45%) came from women expressing regret that they were not submitted or did not submit themselves to IAU. Again, this is lower than the proportion of women who expressed relief at not being submitted, indicating that women were more likely than men to acknowledge the negative implications of being posted on IAU and take a position that they were relieved to have avoided this prior to the website's closure.

The code waitingtosubmit was applied to a niche subgroup of tweets where the poster said they were disappointed that IAU was shutting down because they were waiting until they had turned 18 years old to self-submit nudes. Overall, there were 20 tweets where this code was applied (0.24% of the full data set). When broken down by gender, 12 of these 20 tweets were identified as coming from accounts belonging to women under the age of 18, or 60% of all posters who stated they were waiting to submit to IAU. Typical examples of this include “you [Hunter Moore] couldn’t have waited until I was 18 to shut it down? My dreams of a shirt [in return for submission] are gone” and “now that @is_anyone_up is shut down I have nothing to look forward to on my 18th birthday damn you hunter”. This should be considered in conjunction with another code, selfsubmit + female, which was applied to those tweets where a woman referenced having submitted themselves to IAU at some point. Only 17 posts from women were coded in this way, compared to 31 coded selfsubmit + male. This means that the percentage of women who claimed to have self-submitted to IAU (35.42%) was significantly less than the percentage of women in the waitingtosubmit who expressed an intention to send their nudes into the website when they reached legal age. This may speak to a gap between stated intention and action, with many of those expressing their desire to submit doing so in a low-risk context where IAU was closed, and they would never be required to follow-through on their tweet.

Discussion

The results of this research suggest that the social relationship that women had with IAU was distinct from men, and the total population in general terms. Of note was the higher rates of support expressed by women on Twitter, which far exceeded the support for IAU expressed by the men or undetermined gender subpopulation. This finding alone demands further examination, as conventional expectations would be that men would express greater levels of support for image-based abuse (DeKeseredy & Schwartz, 2013). This is based on previous studies showing that men are by far more likely to perpetrate and consume image-based abuse (e.g., Mortreux et al., 2019; Powell et al., 2019, 2022a), which runs somewhat counter to the observations made here about the gendered differences in support for such content in the specific context of IAU.

The rationale for the higher rates of women's support for IAU in this sample is difficult to determine; however, it is possible that Suler's (2004) online disinhibition theory may provide some broad guidance. Suler offers several factors that impact online interactions differently than face-to-face contact, including conditions such as “dissociative anonymity” and “dissociative imagination”. With the former, Suler does not refer to real anonymity in the sense that peoples’ identities are completely obscured, though this does play a role in fomenting dissociative anonymity. Instead, he refers to a mediated separation between the online persona and reality. Even if their name and general location are known to others in cyberspace, there is less of a chance that their actions will be connected back to their real lives, allowing them to essentially “hide in plain sight” online. Dissociative anonymity is notable for this sample because for tweets to be filtered into the female subset, they could not be totally anonymous, and their perceived gender (at the very least) had to be known. As such, all statements about IAU were made with at least some personal characteristics (name, image, location) identifiable.

Suler (2004) suggests that dissociative anonymity allows people to express often controversial or deviant sentiment online because there is a psychological disconnect, and because there is little chance of consequences in their “real life”. It is possible that the positive sentiment expressed by women towards IAU online is a product of this disinhibition. Whereas mocking and judgement of women's bodies may be more socially acceptable among men (Jane, 2012), there is a certain expectation for women to support other women and, for those who wish to express a contrary view, social media offers a sense of distance from reality which permits them to express views that may not otherwise be acceptable in face-to-face social interactions. Suler also discusses dissociative imagination, which has almost a converse effect to dissociative anonymity—whereas dissociative anonymity is focused on the individual's ability to create a cognitive distance between their online self and real self, dissociative imagination is linked to the individual's ability to create a cognitive distance between themselves and other users, conceptualising them as not real (Suler, 2004). This emerges from the physical separation between interlocutors in online communication, as well as the mediated nature of the interaction in which a user can literally “switch off” whenever they would like the interaction to end. This combines to create a game-like atmosphere in which the usual exhibition of interpersonal empathy is suspended, giving people permission to act in harmful ways to each other.

This is not just a condition affecting woman, and could also apply to other groups who showed support for IAU in the sample. However, it does provide a potentially persuasive explanation as to why a group as heavily impacted by image-based abuse as women (Bates, 2017; McGlynn et al., 2021) tended to demonstrate greater support for IAU than was observed in the men or undetermined gender subset. If women were subject to dissociative imagination, as Suler (2004) suggests, it would indicate that the image-based abuse taking place on IAU and, importantly, the victims of that behaviour, may have assumed an “unreal” state in the minds of female consumers, leading to a deficit in empathy and inability to conceptualise the real harm being done to other women. This does not entirely explain the high rate of women's support for IAU but provides a useful framework for understanding the rationalisation of image-based abuse among the women supporting IAU and their willingness to overlook the victimisation of other women in service of other concerns, such as entertainment.

Another major undercurrent throughout the data was the perception that IAU served a social purpose as a mechanism of informal control, which worked to prevent people (both women and men) from sending nudes out of a fear of being posted on the website. While this thematic group captured the general belief that IAU was an informal control, the actual tone (and sentiment) of these comments differed, with women split on whether the website's closure was a good or bad thing. Many commented that the website shutting down was a net positive, as it meant they and others could share nudes now without risk, whereas others expressed a negative opinion about IAU's closure because of the impact it would have on permitting people to send more nudes. In the comments reflecting the latter view, this was almost exclusively focused on nudes sent by women, with misogynistic female-centred language like “sluts” and “whores” used to describe the people who posters in this subset felt would now be allowed to distribute sexual content with fewer constraints.

The perspective that IAU may have a prosocial purpose is supported in the work of Salter and Crofts (2015), who discuss societal views that the women victimised by image-based abuse on websites like IAU are “dumb” and ended up in the predicament of having their sexual images exposed because they are seen to have “failed at the neoliberal project of self-management” (p. 235). From this point of view, the onus is placed on women not to send sexual content in the first place, with any image-based abuse or non-consensual distribution that occurs after that point being a natural consequence of their “bad choices”. This is further supported by Flynn et al. (2023) work on blame attribution in image-based abuse, which found that minimisation of harm and victim-blaming was closely tied to broader sociocultural attitudes (particularly, sexual double standards) related to abuse, both offline and online. This was a thread that was observable in the tweets featured in this thematic group, but far less so than those tweets which had a positive perspective on IAU's closure in the sense that it would offer them a greater latitude of sexual freedom.

Though these tweets acknowledged that IAU served a role as an informal control on sending nudes, this was not seen as a positive development. To some extent, this reflects an approach that Naezer and van Oosterhout (2021) refer to as “problematic”. As they note, most efforts to prevent both formal and informal image-based abuse have focused on the potential victims and dissuading them from producing the sexual content which may put them at risk of becoming victimised. However, Naezer and van Oosterhout note that this “limits young people's sexual freedom, encourages victim-blaming in case of incidents, and makes perpetrators invisible” Naezer and van Oosterhout (2021, p. 79). This is essentially the same perspective adopted by many of the women who responded to IAU's closure, who saw the removal of this informal control more as liberation than a problem. Even so, the total number of tweets which made comments about IAU as an informal control constituted a relatively small percentage of the overall data set, and so while there is enough data to make some observations on this, further research would be needed to determine to extent to which this opinion prevailed.

There is also ample potential to use Suler's online disinhibition theory to contextualise the behaviour of women who support IAU and perceived mocking those who appeared on the website as entertainment, or a way to address boredom. If the mediated online environment facilitates a sense of dissociation that serves to minimise the experience of the people featured on the website (with or without consent), it becomes easier to contribute to mockery for the purposes of entertainment, something which was encouraged by IAU staff like Moore. That the rhetoric used adopted the tropes of misogyny, even when used by women themselves, is also not as surprising as it initially may seem. As Moloney and Love (2018) said in their discussion of online misogyny, women “tend to replicate” prescribed patterns of cisgendered, heteronormative language in this space and, in doing so, can be seen to prop up misogynistic dynamics in online discourse (p. 5).

It is worth noting that, even though it hosted sexual images and videos, IAU was not marketed as a website for users to seek sexual gratification, like a traditional pornography business. Instead, a major focus was on the communal mocking of those featured, from which most of the entertainment (and community-building) was derived (Salter & Crofts, 2015). In this sense, women were not self-generating mockery for the sake of it, but rather falling into line with patterns of behaviour encouraged by the IAU community, which aligns with the comments made by Moloney and Love (2018) on the reinforcement of online misogyny being a more passive process for the women who participate, and facilitate, this rhetoric. Research from parallel fields suggests that some women may feel that, in a social or professional context, participation in ritualised mocking of other women will contribute to them being perceived as “the cool girl” or otherwise accepted into the in-group (Greer, 2000; Mavin, 2006).

Participation in these rituals can contribute to the normalisation of misogynistic language, or behaviours, in a social context, including online. This is important for various reasons, not the least of which being the impact that higher rates of discriminatory language have on the people who are targeted, in this case those posted on IAU who (in many cases) are already being victimised via the non-consensual posting of their private sexual images. Beyond that, however, the normalisation of misogynistic language has broader implications in that is contributes to propping up traditional patriarchal structures and norms which operate to repress women, including women's sexuality. When women are engaged as “allies” in the use of misogynistic language (for the reasons discussed above, and others) this acts to sanction the conduct in some sense, providing men with the ability to neutralise their own misogyny by observing that women are not universally offended by this rhetoric. While the impetus in combatting misogyny can and should not be placed on women, in cases like this wherein women appear to reinforce misogynistic practice, efforts to reduce gendered abuse in society are undermined, and fewer barriers are placed to prevent unacceptable conduct.

Supporting the interpretation that women used IAU for social entertainment rather than sexual gratification comes from the results observed in reference to a related code, judgementpost. This code was applied wherever a user was commenting directly on an image shared by another user, usually a woman. Typically, when this code was applied, the critique offered was a positive one offered by a male poster to a woman who self-submitted. Women were highly underrepresented in this code compared to the other codes related to mocking or discriminatory language. What this indicates is that women were not interested in commenting on the images hosted in IAU for positive reasons, but rather derived their entertainment or participation in the IAU community from the aspect of mocking which the website was known for, and in turn fell into the misogynistic patterns that were par the course for IAU without consideration for the people they were commenting on—supported, at least in part, by the dissociative conditions that Suler (2004) outlines.

Limitations

The IAU website was identified as a viable case study because it provided a tangible opportunity to better understand the response of female consumers to image-based abuse. However, the website ceased operations in 2012—more than a decade before this research was conducted. Nevertheless, IAU was considered a relevant case study because of its notoriety in the sociocultural zeitgeist of the period, and high rates of visitor traffic (Salter & Crofts, 2015). Examining attitudes towards revenge porn at a time when the consensus that this behaviour is a form of abuse had yet to be reached is also helpful, as the views elicited are less impacted by consumers’ adoption of social scripts in place of their actual views (Weissman, 2021). The generalisability of these results in the present context is a limitation of this approach: although this data provides clear insight into the attitudes of women towards image-based abuse in 2012, it remains to be determined how much these attitudes persist in the modern era. This is a potential area for further research, which may be able to assess how perspectives on this behaviour have changed over time, and what has driven any observable changes.

Another limitation is the challenge faced by researchers in categorising the gender identity of posters accurately—a difficult if not impossible feat when exploring not only social media profiles (which are naturally prone to greater levels of anonymity), but social media data from more than a decade ago. While efforts were made to ensure that only Twitter accounts where gender was readily identifiable were included in the femaleposter subset, this is an imperfect science open to interpretation and, as such, error. Future research should seek to strengthen the method so that gender identity can be more accurately ascertained, which can then be compared against this research to determine whether the results are in alignment.

Conclusions

Summary of findings

There have been a multitude of studies exploring the motivations for perpetrating and consuming image-based abuse by men, yet far less research has focused on the reasons why women would also participate in such behaviours. Examining the response from women on Twitter to IAU's closure in 2012 can offer a snapshot into how women perceived a popular website which based its business model on the peddling of image-based abuse. In turn, it also provides some insight into how image-based abuse can become so normalised online that it is able to gain support within the very population that is most likely to become victims themselves. With women disproportionately impacted as victims of image-based abuse (Ging & Siapera, 2018), this support for IAU among women is a factor which demands targeted attention, beyond the simple aggregation of women within the data set. This was borne out in the sentiment analysis carried out to determine whether tweets in this sample perceived IAU as a positive or negative, overall. This revealed that women were disproportionately positive towards the website, at a rate that was more than 10% higher than the level expressed by the comparison group of men and posters whose gender could not be determined. Ultimately, 71.17% of tweets posted by women included in this sample were coded as positive to IAU, revealing a robust level of support within this group that indicates that the popular view of image-based abuse as the almost exclusive purview of men may require some re-evaluation.

Breaking down the data further, it appears that for the most part, women who supported IAU did so for similar reasons to men. The percentage of codes related to mocking and/or discriminatory rhetoric linked to tweets from women was proportional to the number of women in the overall sample, indicating that women were just as likely to engage in the mocking rhetoric and, often, online misogyny that IAU was notorious for as men were. Women were also marginally more likely to pass comment on other women's bodies, reinforcing the position that online misogyny is not just something that is carried out by men, but is also reinforced by women who fall into comparable discursive patterns. This supports Moloney and Love's (2018) position about the role women play in the reinforcement of misogynistic frames online, including via websites like IAU. Further, women were also likely to see IAU as an informal control preventing individuals (in particular, women) from producing and sending consensual nudes. However, while some women did see this informal control process as a positive, more saw the closure of IAU as a positive in enabling greater levels of sexual freedom, taking risk away from the consensual exchange of self-generated sexual content.

Implications

The implications of this research are that—in the case of IAU, at least—women and men expressed similar sentiments about image-based abuse and its social role. Both engaged in similar rates of mockery targeted at those who were featured on the website and were comparable in their belief that IAU served as a purpose as an informal control repressing the sending of nudes (albeit, with differing outlooks on if this was a positive or negative). Notably, women were disproportionately overrepresented in expressing positive sentiment towards IAU comparative to both the full data set and, more so, the men or undetermined gender subset. This indicates a pattern of women supporting IAU that should be explored in future research pertaining to other sources of image-based abuse to determine if this response was specific to the context of IAU (a sociocultural phenomenon in its own right), or if it can be applied to the consumption of image-based abuse content in more general terms.

In all, this research serves to complicate the conventional perspective that image-based abuse is a cultural product almost exclusively consumed by men and offers insight into the nuances of positive sentiment expressed towards IAU by women. From a conceptual standpoint, this research adds a unique dimension to the existing research on image-based abuse thanks to its purposeful emphasis on the behaviour of women, which has been neglected in the literature to this point. It makes a case that women can be active (often, enthusiastic) consumers of image-based abuse who engage with this content in a generally similar way to men—albeit with a range of subtle, yet crucial, distinctions. The findings have practical implications, as well. By rejecting the assumption that women do not consume image-based abuse in the same way that men do, this article reinforces the need to focus education programmes and other interventions at all genders in equal measure, constructing this not as a “boy problem” but as an issue experienced (and perpetuated) by a diversity of bad actors in the online space. This is especially important when the findings related to women's use of misogynistic rhetoric and their view that image-based abuse can serve as a prosocial informal control on sexual behaviours are considered, which are two key points raised in this work that must be addressed going forward if the core values and beliefs that underpin image-based abuse are to be challenged effectively on a sociocultural level.

Thematic group	Codes included	Frequency in femaleposter subset (n = 2,388)	Frequency in non-identifiable and/or male subset (n = 5,826)	Frequency in full data set (n = 8,214)
Positive towards IAU	proIAU; proHunter; sad; endoftheworld; wherewilligetpornnow; wasfun; mad; whatwillidonow; continue + newsite; continue + Twitter; leavingtheInternet; neverforget	1,304 (54.6%)	2,733 (46.91%)	4,037 (49.15%)
Negative towards IAU	antiIAU; antihunter; getoverit; abouttime; happy; disappointedinIAU; CSAM	241 (10.1%)	435 (7.47%)	676 (8.23%)
IAU as an informal control on sending nudes	morenudesnow; notsubmitted + relief; blamesubmitters	70 (2.93%)	120 (2.1%)	190 (2.31%)
Mocking and/or discriminatory	mocking; misogynistic	129 (5.4%)	260 (4.46%)	389 (4.74%)
Boredom	boredom; whatwillidonow	108 (4.52%)	136 (2.33%)	244 (2.97%)

Footnotes

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Paul Bleakley

Notes

Appendix

Full list of codes with definitions

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