#Me(n)Too? Online Social Support Toward Male and Female Survivors of Sexual Victimization

Abstract

Much has been written about the difficulty of sexual victimization survivors to disclose their experiences to others and about the crucial role social support play in their recovery process. However, the vast majority of the literature has focused on face-to-face interactions, while in recent years, more and more victims are turning to online self-disclosure, whether privately or as part of proactive network protests such as the #MeToo hashtag campaign. The few existing studies that examined online responses to disclosures of sexual victimization have focused on female survivors only and didn’t examine whether men and women elicit different responses based on gender stereotypes. The current study addresses this lacuna through a quantitative content analysis of 2,635 responses to 734 self-disclosures of male and female survivors of sexual victimization published on Facebook and Twitter during the first 3 weeks of the #MeToo and #WhyIDidntReport protests in Israel (October 2017 and October 2018, respectively). The findings indicate that social networks, despite some of their affordances, such as lack of eye contact or physical gestures, are supportive environments for survivors of sexual victimization of both sexes. However, women who self-disclose online are more likely to receive emotional support and network support, whereas men are more likely to receive retributive support—a new support type that was found in the current study. The conclusion is that users’ reactions to sexual victimization disclosures are mainly supportive but are also affected by gender stereotypes. Practical and theoretical implications are discussed.

Keywords

social support self-disclosure feminist hashtag campaigns sexual victimization #MeToo #WhyIDidntReport

Introduction

The rise of digital technologies and social media has created a new space for survivors of sexual victimization to connect and share their stories and received wide scholarly attention (Bogen, Bogen, Millman, et al., 2018; Dworkin et al., 2016; Lokot, 2018). Much of this literature is focused on the disclosures’ contents and construction processes. However, the social responses to these exposures have been less investigated. What are the most prevalent types of support that disclosures of sexual victimization invoke? Do online disclosures invoke relatively high rates of unsupportive responses due to the medium affordances such as a-synchronicity and lack of physical cues? These questions relate to survivors of sexual victimization from both sexes, but are even more relevant for male survivors, who contradict normative perceptions of what it means to be a “man” (Hlavka, 2017; Javaid, 2017), and therefore might encounter different response patterns compared with women (Andalibi et al., 2016).

Keeping in mind survivors’ particular sensitivity to feedback and the influence that social reactions have on their recovery process (Ahrens, 2006; Hosterman et al., 2018; Lokot, 2018; Ullman, 2010; Ullman & Peter-Hagene, 2014), the current study explores how social support is communicated online and whether male and female survivors of sexual victimization vary in the nature of social support they receive. By so doing, we wish to shed light on the utilities and limitations of computer-mediated environments as coping resources. The comparison between reactions toward male and female survivors will also make it possible to identify when and why particular types of support messages are more or less likely to be encountered. Such information may contribute to theory-building efforts about social support and gender both online and offline.

Self-Disclosure of Sexual Victimization in Offline Environments

The persistent negative consequences of sexual victimization¹ are well-documented. In addition to depression, anxiety, insomnia, suicidal thoughts, and anger (for a meta-analysis, see Dworkin et al., 2017), survivors of sexual victimization are also prone to feel shame, guilt, and embarrassment (Moors & Webber, 2013). These feelings are reinforced by stereotypical social beliefs about the culpability of survivors, the innocence of perpetrators, and by the social tendency to minimize assault severity (Hlavka, 2017; Kennedy & Prock, 2018). In light of that, it is no surprising that falling a victim to sexual abuse is the least reported of all crimes (James & Lee, 2015).

The difficulty in exposing the violation doesn’t only apply to formal authorities, but also to informal support sources such as friends and family members (Orchowski et al., 2013). Disclosing sexual victimization is a complicated process, which can take a long time, if it happens at all, and is characterized by uncertainty about who can be trusted and what the consequences of reporting will be (Hakimi et al., 2016; Jacques-Tiura et al., 2010). Survivors of sexual victimization who chose to disclose have described the decision as placing them in a vulnerable position and as causing them additional emotional distress (Andalibi et al., 2016; O’Neill, 2018).

In the case of male survivors of sexual victimization, the difficulty to disclose also derive from a set of stigmatizing cultural narratives that contributes to a unique sense of shame (Du Mont et al., 2013). In many patriarchal societies, where the dominant form of masculinity identifies it with supremacy, control, and power (Javaid, 2017), male sexual victimization is nearly incomprehensible because it contradicts cultural ideas of what it means to be a “man”—strong, powerful, self-sufficient, and impenetrable (Hlavka, 2017, p. 487). Within this context, men cannot be forced to have sex against their will and are always welcoming sex opportunities (Lowe & Rogers, 2017). Hence, male survivors of sexual victimization are viewed as having failed in their masculine duty to protect themselves (Turchik, 2012).

These sociocultural beliefs also permeate the victims: A repeated finding in interviews with male survivors of sexual victimization is that normative expectations about masculinity act as additional barriers for their disclosure and help-seeking (Alaggia et al., 2019). Easton et al. (2014) who focused on male survivors of childhood sexual abuse noted three primary domains of barriers that deter, obstruct, and discourage men from disclosing: (a) sociopolitical, (b) interpersonal, and (c) personal. These barriers, as identified by the survivors, reflect a complex, multilevel interaction between the person and the environment. Gruenfeld et al. (2017) examined the perceptions of nine therapists who specialize in the treatment of men who were sexually abused in childhood and found that therapists also recognized social milieu (e.g., internalized social stigma, negative responses, and masculine identity dissonance) as a barrier for their clients’ disclosure. However, a wide body of research suggests that nondisclosure is detrimental to health, and that appropriate disclosure and help-seeking decreases psychological distress and aids recovery among both men and women (Dworkin et al., 2019; Easton, 2019; Gruenfeld et al., 2017). In other words, disclosure on its own is not necessarily associated with improved mental well-being, despite the potential benefits of disclosing trauma; it is having a supportive reaction that reduces the discloser’s risk of mental health challenges (Ahrens et al., 2010; Orchowski & Gidycz, 2015).

Social Support: Conceptual Framework, Measurement, and Effect on Survivors of Sexual Victimization

Social support is a multifaceted concept, which can be classified in different ways, such as by disposition, direction, structure, or content (Li et al., 2015). Measures of social support can also be made in terms of global experiences, such as general assessments of the number of confidantes and support available in one’s network, or in incident-specific terms, such as social reactions to sexual assault disclosures (Mason et al., 2009). The current study adopts a functional perspective, which refers to the particular functions interpersonal relationships serve and distinguishes between different types of social support to self-disclosure of sexual victimization (Zhang, 2017).

Social support behaviors have been classified using a variety of coding schemes. One of the most popular is the five-category Social Support Behavior Code (SSBC) developed by Cutrona and Suhr (1992) to measure the frequency of supportive behaviors. The SSBC comprises 23 supportive behaviors that are encompassed by five broad categories of support: informational, emotional, esteem, network, and tangible support. Informational support refers to messages that provide facts, guidance, or advice; Emotional support messages involve expressions of caring, concern, and empathy; Esteem support is defined as the messages that help to promote one’s skills, abilities, and intrinsic value; Network support is defined as the messages that help to enhance one’s sense of belonging to a specific group; finally, Tangible support involves offers of physical or monetary assistance.

Although Cutrona and Suhr’s (1992) conceptualization is not free of criticism (for a comprehensive review of measurement and methodological issues, see Cohen et al., 2000), a steady stream of studies have been published that used SSBC or a commensurate coding scheme to examine the prevalence of support messages in a wide array of contexts, ranging from friendship dyads to mental health issues (Zhang, 2017). The use of the SSBC has also been very common in the context of disclosure of sexual victimization, accompanied by other categories—specifically unsupportive social reactions—which did not appear in Cutrona and Suhr’s original typology.

For example, the Social Reactions Questionnaire (SRQ) developed by Ullman (2000), which is the most widely used measure of reactions to sexual victimization disclosures (Ullman et al., 2017), integrates Cutrona and Suhr’s (1992) categories of instrumental support, emotional support, and information support, with additional aspects of negative social reactions, such as victim blaming and egocentric behavior. The SRQ was developed by using qualitative data and existing literature to generate a set of reactions commonly received by sexual assault survivors. Survivors are asked to indicate how often they received each reaction from others following victimization (Dworkin et al., 2019).

Several studies have shown that social support is essential to maintaining psychological well-being (Ullman & Peter-Hagene, 2016). Specifically, in the context of sexual victimization, it was found that “positive social reactions” (Ullman, 2010) to self-disclosure of sexual victimization, that is, reactions that express emotional or informational support, offer tangible aid or sense of belonging and are associated with enhanced self-worth and lower levels of psychological distress (Littleton & Breitkopf, 2006; Orchowski et al., 2013; Orchowski & Gidycz, 2015). In contrast, unsupportive reactions, for example, victim blaming, doubting, disinterest, or minimalizing the abuse severity, might harm the discloser’s well-being and psychological adjustment and are strongly associated with higher levels of post-traumatic stress (Dworkin et al., 2019; Ullman & Relyea, 2016).

Since the appearance of new media platforms and online social networks, the SSBC typology was found to be applicable for studying the prevalence of support messages shared in computer-mediated environments as well.

Affordances of Online Platforms and Self-Disclosures of Sexual Victimization

The rise of new media and online social networks has provided new venues for self-disclosing, and substantial research has demonstrated that sexual violence survivors’ reluctance to disclose tends to reduce in online settings (Moors & Webber, 2013). Survivors of sexual victimization may turn to online platforms to disclose sensitive experiences when they feel inadequate in-person social support, are seeking tailored information, or are hoping to influence policy (Bogen et al., 2019). This decision mostly derives from the technical affordances of the web (i.e., features of technological media that users perceive as impacting their ability to fulfill their goals and needs), and particularly, a-synchronicity, the absence of nonverbal cues and anonymity, which portrays it as safer in the eyes of survivors than offline environments (Fawcett & Shrestha, 2016; Sills et al., 2016).

The networked structure of social media enables communities of similar others to gather around a shared experience. Hence, they are perceived to be safe spaces to talk about sensitive experiences (Gallagher et al., 2019). In addition, in online settings, survivors of sexual victimization shouldn’t worry about gestures, facial expressions, voice, or physical appearance. Online platforms are also not being constrained by time due to the possibility of asynchronous communication. Therefore, survivors of sexual victimization can better control and articulate both their messages and the time of reading the responses they provoke (O’Neill, 2018). Finally, the anonymity afforded by the internet allows individuals to share painful experiences without fear of negative evaluation from others (Andalibi et al., 2016; Bogen, Bleiweiss & Orchowski, 2018; Loney-Howes, 2018).

Unlike the first two characters mentioned above, the main benefit of anonymity might be expressed in more “private” disclosures, such as those taking place in online rape victims’ communities, Subreddits, Facebook groups, forum websites, and dedicated Tumblr accounts (O’Neill, 2018; Powell, 2015). However, in recent years, movements of feminist activism have been encouraging survivors of sexual violence to disclose their personal experiences publicly and not anonymously.

Online Self-Disclosure of Sexual Victimization and Social Support

Adopting a bottom-up approach to communication, many contemporary sociopolitical movements use online media as a “counter-public,” an alternative public sphere, which suggests new terrains of political struggle for voices and groups excluded from the mainstream media (Lokot, 2018). Many of these initiatives—for example, hashtag protest campaigns such as #MeToo, #NotOkay, #WhyIstayed, #WhyIDidntReport—rely on disclosing personal experiences of violence, which hold the capacity to challenge victim-blaming narratives and responsibilization of violence, making way for new narratives to emerge (Loney-Howes, 2018; Salter, 2013).

Despite the growing scholarly interest both in hashtag campaigns that involve disclosures of sexual victimization (Lokot, 2018) and in online social support (Rains et al., 2015), there is scant empirical research that combined the two, that is, focused on social support to online disclosures of sexual victimization. Among the few existing studies in this context are Moors and Webber’s (2013) descriptive analysis of replies to disclosures of sexual victimization on a Yahoo! Answers thread, which found most of the replies to be encouraging or recommending action to obtain help, but a little more than 14% to include negative feedback. Bogen et al. (2019) examined in what ways Twitter users used the hashtag #NotOkay as response to online disclosures of sexual victimization and concluded that online forums may offer a unique context for disclosing violence. Hosterman et al. (2018) content-analyzed 2,782 twits containing the hashtag #MeToo and found that individuals and organizations use informational support messages with significantly greater frequency than other social support messages. Finally, Andalibi et al. (2016) examined the role of anonymity in online sexual abuse–related disclosures published on Reddit and found it as key to both seeking and providing social support.

However, despite their important contribution to establishing a body of knowledge in the field of online disclosures and social support, all of these studies haven’t differentiated between male and female survivors of sexual victimization, despite the different social norms that are attributed toward them. Adding an explanatory variable such as gender in a context in which gender plays a significant role is of high value and may contribute to better understanding discloser–response relations.

We address this empirical gap by analyzing 2,635 online responses to male and female survivors of sexual abuse who disclosed their personal experiences during the hashtag campaigns #MeToo and #WhyIDidntReport in Israel (October 2017 and October 2018, respectively).

The research questions, therefore, are as follows:

Research Question 1: Which types of support are elicited to online self-disclosures of sexual abuse victimization?

Research Question 2: Do online self-disclosures of male survivors of sexual abuse elicit different types of support compared with women?

Method

Context of the Case Study

As in other Western democracies, in recent years, a lively public debate has been taking place in Israel regarding the status of women in general and sexual abuse in particular (Kamir, 2019). In 2013, in light of the exposure of several cases of sexual harassment by Israeli public figures and 4 years prior to the #MeToo campaign, a project called “One from One” was established in Israel (www.facebook.com/oneofone1), which published thousands of anonymous testimonies of female survivors of sexual victimization to raise public awareness of the issue.

Against this background, the global protests #MeToo and #WhyIdidntReport have won Israeli media attention and public cooperation, and hundreds of men and women survivors of sexual abuse have exposed their personal stories. The #MeToo campaign has generated about 85,000 entries in the Israeli network (in general sites and social media), most of them by women (Tuvman, 2019), and the #WhyIdidntReport movement, where the weight of the male participants was greater, prompted 1,100 social networking debates that attracted 5,970 responses and more than 47,000 likes (Liel, 2018). In light of the centrality of these campaigns both locally and globally, they were chosen to serve as case studies in the current study.

Data Collection and Sampling

The data were retrieved using an automated tool of the Vigo Media Monitoring Company, a commercial company for monitoring and analyzing media information, which developed an algorithm that scans all social media public accounts’ content in Israel and retrieves data based on search terms. First, we searched for the #MeToo and #WhyIDidntReport hashtags on Facebook and Twitter during the first 3 weeks of each campaign (October 16–November 8, 2017 and September 30–October 20, 2018, respectively). This search yielded 10,404 results. Of these results, irrelevant data—that is, posts/tweets that included the #MeToo and #WhyIDidntReport hashtags but weren’t self-disclosures (e.g., trolling posts, jokes, general statements about the campaigns, hashtags only, paraphrases)—were eliminated from the data set. During the coding procedure, we discovered 22 posts/tweets that guided readers to a certain type of reaction, for example, disclosers who asked their friends/followers to share their own stories of sexual victimization in the comment section (i.e., encouraged network support) or disclosers who asked for emotional support such as a hug, and were therefore removed. After filtering the initial data set, there were 734 self-disclosures left, with 26,350 comments associated with them.

Although women were more prone to disclose than men (551 of the disclosures, approximately 75%, were published by women), male disclosers received relatively more responses than females (10,067 vs. 16,283, respectively, an average of 55 responses per disclosure, compared with an average of 29.5 responses per disclosure in the case of women). To represent this stratum in the analysis, a stratified random sampling was conducted. The sample was divided into two subsamples: comments received to self-disclosures of women and comments received to self-disclosures of men. Every 10th comment was sampled from each subsample separately. The ratio of 1:10 was chosen because it allowed the sample to be reduced to a size that, on one hand, would be manageable, while, on the other hand, large enough to yield valid findings. Most responses were unrelated to each other. In cases of threads, only the first response in a thread was sampled, although the research assistants were instructed to apply on threads the same sampling ratio that characterized the rest of the sample. The reason is that the other replies in each thread were irrelevant for analysis, either because they were “off-topic” (e.g., expressed general statements in regard to the value of hashtag campaigns or discussed the legitimacy of “shaming” the perpetrators) or because they referred to the first respondent and not to the discloser, and hence couldn’t be classified to one of the support categories analyzed in the study. In total, the sample consisted of 2,635 responses to 734 online self-disclosures: 1,628 of them were responses to women and 1,007 to men disclosers.

Coding and Procedure

To analyze the comments, and in accordance with similar studies (Andalibi et al., 2016), we employed the Social Support Behavioral Code (SSBC; Cutrona & Suhr, 1992), which categorizes messages as emotional support, informational support, esteem support network support, and tangible support. During the coding process, we discovered another support category, which we called “retributive support,” as it was expressed mainly in calls for punishing the perpetrator and for restoration of justice.

As findings from offline settings indicate that self-disclosures might also lead to unsupportive reactions (Hakimi et al., 2016; Nikulina et al., 2016), the analysis included this category as well: comments that criticized the discloser and expressed disbelief, blaming, or minimization of the abuse severity as well as “trolling” responses aimed at provoking controversy, were all coded as unsupportive. If a comment did not meet any of the above-mentioned categories, it was coded as “other.” Table 1 defines all coding categories and illustrates them with examples taken from the sample.

Table 1.

An Illustration of the Coding Categories.

Category	Definition	Example
Emotional support	Expressions of care, concern, empathy, and sympathy	“I’m sad to read this. I feel so sorry for you. I do not know you but I hug you” “Exciting. I believe you. Thanks.” “Identifying with you, feel you, understand you. with you”
Esteem support	Messages aiming at bolstering one’s self-esteem by compliments or expressions of confidence in his or her abilities	“You’re brave and thank you for revealing it” “Trust me, you are stronger than you know, and day by day you’ll start to feel it more.” “How amazing and brave you are. And how beautiful you wrote. I strengthen you and congratulate you on the words and the courage.”
Network support	Communicating belonging to a group of people with similar experiences	“I am here by your side!” “It is amazing how the paths of all women are similar, and I’m not writing it with joy” “Your story overwhelms me all the dozens of times I’ve been sexually harassed. In the last few days, I think to myself when I will sit down and write mainly for my girls. When will the fear and embarrassment change and allow me to let go. When will this reality of women and girls experiencing violence and disrespect for their dignity and freedom of living be reversed and ignored by the world.”
Informational support	Providing useful information or advice, as well as factual input and feedback on actions	“I remind you that there is a hotline for men victims of sexual assault. Call 1203” “If you want to continue processing it, I know someone great”
Tangible support	Instrumental assistance, such as the provision of financial aid, material resources, and needed services	“I would be glad to assist you in funding the judicial process”
Retributive support	Calls for punishing the perpetrator and for restoration of justice	“With the help of god, may the perpetrator be punished. Amen” “You have to take this Rabbi and all the sexual abusers, tie his arms and legs and just abuse him every day for the rest of his life” “If you can also share the name of the bastard—maybe his sentence will finally come.”
Unsupport	Comments that criticized the discloser, expressed disbelief, blaming or minimization of the abuse severity as well as “trolling” responses aimed at provoking controversy	“With all due respect, if you don’t file an official complaint you cause more children to be hurt” “Sorry to tell you that you just do not do right. He moved forward and you remained scarred” “Don’t believe you at all. It’s not a way to get attention”
Other		“I have just read a book about sexual abuse”“it’s time for a ‘whyIassault’ hashtag, and not ‘whyIdidntreport’”

The coding was done by the author and by two research assistants, and graduate students who had previously experienced content analysis. The coding process was conducted in two stages: First, after a few joint meetings in which the coding scheme was developed, 50 comments were coded independently by each of the three coders. Then, they discussed the cases where discrepancies were found between them and sharpened the coding procedure. After that, another 150 comments were coded. The inter-coder reliability at this stage was high: Krippendorff’s alpha statistic of .92 for emotional support, .91 for esteem support, .87 for network support, .88 for informational support, .90 for retributive support, .94 for unsupport, and .89 for other. Hence, the three coders continued to code the entire data set (which was randomly divided between them) according to the agreed coding procedure. They were instructed to share any doubts that arose for a joint agreement, but at that point, it was hardly necessary (~15 comments). Instrumental support was found in three responses only and has therefore not been included in the statistical analysis.

Ethical Considerations

The study doesn’t involve human subjects directly, but the content they produce on social media. Data collection procedures followed the ethical merits of internet-based research using publicly available data only and keeping users’ anonymity (Bogen, Millman, et al., 2018). As Vigo’s algorithm collects only posts/tweets that are available on Twitter’s and Facebook’s public API streams, this study was considered exempt from institutional review board (IRB) approval and no formal informed consent process was required (for a discussion of the topic see, Andalibi et al., 2016; Bruckman et al., 2015). In addition, all identifying information of both disclosers and respondents (except for the disclosers’ gender) was removed from the database to maintain ethical standards of online data and to protect users’ anonymity.

Results

The vast majority (98.8%) of the responses were supportive and included different expressions of support such as “I believe you,” “it is so frustrating!,” “you are amazing,” and “I’m by your side.” Table 2 displays the support types distribution for both male and female survivors. The data add up to more than 100% because most comments included more than one response type.

Table 2.

Distribution of Response Types to Online Disclosures of Sexual Victimization.

Category	Frequency (%)
Emotional support	61.8
Esteem support	51.9
Network support	10.4
Other	8.3
Retributive support	6.8
Informational support	3.1
Unsupport	1.2

As indicated in Table 2, the most frequent types of support—with a considerable difference from the others—were emotional support (61.8% of responses) and esteem support (51.9% of responses). Retributive support is more than twice as frequent as informational support (6.8% vs. 3.1%, respectively)—the least frequent of all support types. Unsupportive responses were very rare—only 1.2% of all comments, for both male and female disclosers.

During the coding process, it was found that nonsupportive responses often caused strong resentment among other respondents, who called the nonsupporting respondent to stop publishing his or her comments, nicknamed him or her in derogatory pronouns, and advised the discloser to ignore him or her. For example, one of the respondents asked the discloser “Why didn’t you complain to the police?” and concluded that “women who get drunk up to loss of control and memory run the risk of assault, in an accident, and a thousand more problems. Take responsibility and don’t get drunk anymore.” This comment aroused a backlash of other commenters who expressed shock from its content and condemned it. “You read this story, and what you see is a narrative of female irresponsibility and loss of control?” asked one of the respondents, and another one wondered: “What would you say if your daughter drank and raped after being given a rape drug?” In a similar case, the replies to the nonsupportive respondent were sharper and included derogatory pronouns such as “flat-out loser,” “douchebag,” and “troll.” Although this is a qualitative finding, which was found inductively and is not included in the coding scheme of the present study, we find it helpful to situating the quantitative findings in a broader context.

The second research question deals with the differences between responses to men disclosers compared with women. To answer RQ2, a chi-square test of independence was performed. Male survivors of sexual victimization received more responses per disclosure compared with women (55 vs. 29.5, respectively), but their internal distribution was different. Table 3 demonstrates the frequencies of each support type divided by the discloser gender and the relevant chi-square test values.

Table 3.

Distribution of Response Types by Discloser Gender.

Category	Frequency of Responses to Women Disclosures (N = 1,628)	Frequency of Responses to Men Disclosures (N = 1,007)	χ² Test of Independence
Emotional support	64.6%	58%	χ²(1) = 13.70p = .001
Esteem support	53.4%	49.9%	χ²(1)= 3.147p > .05
Network support	12.8%	7%	χ²(1) = 23.817p = .001
Retributive support	3.4%	11.5%	χ²(1) = 65.255p < .001
Informational support	2.7%	3.8%	χ²(1) = 2.366p > .05
Unsupport	1.2%	1.2%	χ²(1) = 0.003p > .05
Other	8.4%	8.2%	χ²(1) = 0.064p > .05

As demonstrated in Table 3, the relation between discloser’s gender and support type was found significant for three variables: Emotional support, χ²(1, N = 2,635) = 13.70, p = .001; Network support, χ²(1, N = 2,635) = 23.817, p = .001; and Retributive support, χ²(1, N = 2,635) = 65.255, p = .000. Based on these results, women who self-disclose online are more likely to receive emotional support (φ = .076) and network support (φ = .095). Men are more likely to receive retributive support (φ = .157).

Discussion

Through a content analysis of 2,635 user comments, the present study sought to map the nature of social support expressed toward men and women survivors of sexual victimization who disclosed their stories online. All in all, the findings suggest that social networks, despite technical affordances such as lack of physical gestures and eye contact, which might encourage unsupportive responses, are supportive environments for survivors of sexual victimization of both sexes. Although men received the same support rate as women (98.8% of all responses), the differences found in the types of support directed toward them (i.e., significant higher rates of retributive support and lower rates of emotional and network support) may indicate that responses to self-disclosure of sexual victimization are influenced by gender stereotypes.

While recent research suggests that utilizing social media to disclose sexual victimization may leave individuals exposed to “trolling” behaviors intended to aggravate, annoy, or harm (Bogen, Bleiweiss, & Orchowski, 2018), the rate of nonsupportive responses among all responses in the current study was very low, at only 1.2% for both male and female survivors. Moreover, the few nonsupportive responses aroused strong opposition from other respondents who called on the discloser to ignore them and condemned the unsupportive respondent. This is a characteristic that does not exist in offline environments, in which self-disclosures are usually conducted intimately and therefore the impact of negative responses they involve may be more severe. Given that empirical evidence consistently indicate that negative social reactions are associated with more deleterious effects on disclosers (Pinciotti et al., 2019; Ullman & Relyea, 2016), this response pattern may indicate a unique positive outcome of online disclosure, in which the discloser enjoys a “shield” of supportive respondents who actively oppose unsupportive reactions. This hypothesis needs to be considered cautiously due to the small amount of nonsupportive comments in the current sample and should be further investigated. The internal distribution of support messages, in which emotional support was the most prevalent and informational support was the least, also suggests that user comments to self-disclosures are not spontaneous, but are adapted to the disclosure type. Studies of online social support in contexts other than sexual assault (especially mental and physical illness) have found that online communities are frequently robust sources of informational and emotional support, with mixed findings related to the other support types (Hether et al., 2016; Rains et al., 2015). However, the current study found that informational support was the least common of all support types, with esteem support replacing it in frequency.

This finding makes sense in light of the nature of sexual victimization compared with health contexts. While in health contexts social networks are better set up for the task of providing information (e.g., recommending therapists or treatments), in the context of sexual victimization, which involves high feelings of shame and guilt (Andalibi et al., 2016; Moors & Webber, 2013), it is the person’s sense of competence or self-esteem that should be bolstered by others. Hence, our findings indicate that online responses to self-disclosures are not automated, but are usually a calculated attempt to provide support in a way that is perceived as optimal for the context.

In addition to the five known types of support (emotional, informational, esteem, tangible, and network; Cutrona & Suhr, 1992), the current study also recognized a new support type, which we named “Retributive support.” This type of support lies on the seam between emotional support and informative support. On one hand, it expresses anger toward the perpetrators and wishes them harm (“such people should be burned in hell”; “I love you. And also want to burn the man’s house”), thus demonstrating empathy toward the survivors and validation of their suffering. On the other hand, it advises how to act against the perpetrators either legally (“his place is in prison, you have to complain about him”; “you must go to the police with that information!”) or illegally (“tell me where he lives and I’m going to break his legs”), hence including an informational dimension as well.

Interestingly, men’s self-disclosures have significantly raised more retributive responses than women. It is possible that as masculine socialization practices consistently link male sexuality with dominance (Hlavka, 2017), responses calling for action against the perpetrators (i.e., to restore the survivors’ activity) are an attempt to reestablish the “normative” masculine social order. This finding may indicate that the goal of feminist campaigns to provide an alternative platform for doing justice to women survivors of sexual victimization (Lokot, 2018) is paradoxically better fulfilled when it comes to men. However, while feminist hashtag campaigns aim at bringing “attention and justice to women who rarely receive either” by exposing their stories (Williams, 2015, p. 344), the retributive messages found in the current study indicate that the term “justice” may be interpreted in a more private sense and may be even translated into legitimization of violent acts.

Either way, not all sexual victimization survivors perceive social reactions in the same way (Ahrens et al., 2009), and retributive responses may also be interpreted by them as criticism. This is especially reasonable in regard to responses that called the disclosers to complain to the police and expressed surprise that they had not done so before (“This is so infuriating! He should be punished, what are you waiting for? Go to the police now!”). Therefore, it is not at all certain that this type of response (which might also appear on face-to-face interactions) has a positive effect for survivors of sexual victimization and may even increase their sense of guilt and helplessness. Against the background of findings suggesting that nonsupportive responses increase symptoms of post-trauma in survivors of sexual victimization (Andalibi et al., 2016; Orchowski et al., 2013), it is worth continuing to examine the nature of retributive support and its potential effects both online and offline.

Significant differences were also found in emotional support and network support: Women’s self-disclosures evoked more emotional and network support than self-disclosures of men. Similar to the retributive support, these differences can also be explained by mirroring traditional gender roles according to which women are more sensitive and vulnerable than men (Timmers et al., 2003). The high prevalence of network support messages toward women disclosers can also be explained by the context of the disclosures’ publication: Feminist hashtag campaigns, which aim at becoming a way for women to come together, unite their message, and share their unique stories (Maas et al., 2018), may therefore encourage a sense of “sisterhood” in the form of network support messages. And indeed, besides adding the hashtag #MeToo to a response, network support was also expressed in explicit statements about the universal and crossing generations connection between women, such as “Thank you for showing the way and for highlighting the inner struggle all of us sisters have been through one after another” or “You mentioned your mother [. . .] and I find myself thinking about the stories of our mothers, some of whom are only now telling about them, and our grandmothers [. . .].” This finding also indicates that online self-disclosure of sexual victimization might profit from unique affordances of the internet, such as connectedness.

Conclusion, Research Limitations, and Diversity Implications

The main conclusion derived from these findings is that online disclosure provides sexual victimization survivors with relatively safe and supportive environment, which even enjoys some affordances that lack from offline settings, and hence holds advantageous potential effects for their psychological and physical health outcomes. The low prevalence of informational support found in this study, which contradicts findings on self-disclosures in contexts other than sexual victimization, indicates that users’ support messages are adapted to the disclosure context. However, the differences found between reactions toward male and female survivors indicate that users’ reactions are also affected by gender stereotypes.

Do survivors of sexual victimization need different kinds of support on a gender basis? Do online support messages simply represent a vehicle for the same supportive communications that are conveyed in-person? Are they more or less effective than face-to-face interactions? The present study has mapped the surface on which these questions should be examined, to better understand the role of social networks in the processes of self-disclosure and social support. However, it suffers from a number of limitations that may affect its generalizability.

First, the research had focused on the Israeli arena only. Although Israel resembles other Western societies in regard to social construction processes of gender and masculinities (Kamir, 2019), it is also characterized by unique cultural characteristics, such as a direct style of speech (Zaidman, 2001), which may be expressed in unique response patterns to online self-disclosures. In addition, the use of social networks in Israel is among the highest in the world (Silver, 2019). Future studies should also look at other societies (e.g., countries that use social networks less profitably) and examine whether similar findings are obtained.

Another limitation concerns the nature of the database. Due to ethical considerations, the study was based on responses to self-disclosures published in public accounts only. This reliance limits the ability to examine additional variables that may influence patterns of online social support. For example, age, religiosity, gender of the respondent, the nature of his or her relationship with the discloser (an old friend? Coworker? Neighbor?) may mediate the relationship between the disclosers’ gender and the type of social support she or he received. This is a disadvantage in regard to social media research in general, and the present study is no exception. Although there are automated tools for extracting certain demographic information about internet users (especially age and gender), these tools raise ethical questions on issues such as privacy and accessibility of information, which the scientific community should also be aware of.

Third, the present study conducted a quantitative content analysis of online responses, which allowed to analyze the significance level of differences in types of support toward male versus female survivors of sexual victimization. This is an accepted method in studies that examine differences between groups (Riffe et al., 2014). However, this kind of analysis may miss in-depth characteristics that cannot be quantitatively coded, for example, ideological assumptions implicit in responders’ comments or their interaction patterns. The choice to refer to threads in the “Results” and “Discussion” section of the current study, despite the fact that they didn’t meet the quantitative coding scheme, designed to overcome this weakness to some extent. However, it is reasonable that systematic qualitative analysis of the responses (e.g., through discourse or thematic analysis) would place the quantitative findings in a broader context. We recommend future studies to include such methods as well to obtain triangulation.

Research into the role of social networks in social support is in its early stages. Given the increasing use of online networks for exposing sensitive data (Bogen et al., 2019), and the increasing number of sociopolitical campaigns that encourage the sharing of personal experiences online (Lokot, 2018), it is needed to examine the extent to which online responses translate into actions and feelings in the real world as well.

Footnotes

Declaration of Conflicting Interests

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

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Hila Lowenstein-Barkai

Note

Author Biography

Hila Lowenstein-Barkai is a faculty member in the School of Communication in Ariel University, Israel. Her research focuses on political communication, political online behavior, and social psychology.

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