Users’ emotional and behavioral responses to deepfake videos of K-pop idols
用户对 K-pop 偶像深度伪造视频的情感与行为反应

Deepfakes are widely produced by autoencoders (Kingma & Welling, 2013) and generative adversarial networks (GAN) (Goodfellow et al., 2014). In particular, deepfakes can be created by a series of deep learning processes in which pairs of two artificial networks, the generator and the discriminator, pit against each other in generative adversarial networks (GANs; Creswell et al., 2018). With several facial images from different angles, the generator can produce authentic-looking digital manipulations while the discriminator attempts to tease the authentic and fake images apart (Creswell et al., 2018; Westerlund, 2019). In this simultaneous and competitive environment of two networks, the authenticity gradually improves (Öhman, 2019, pp. 1–8), ultimately creating fake, but hyper-realistic media content (Fletcher, 2018; Maras & Alexandrou, 2019).

Deepfake algorithms have become democratized with open Internet-based platforms or applications such as FaceSwap, FakeApp, DeepFaceLab, and DeepNude, contributing to the widespread production of deepfakes by making the quality deepfakes production process surprisingly easy (Gosse & Burkell, 2020; Kolagati et al., 2022). This development of digital technology under the rapidly changing media environment exacerbates the difficulty of distinguishing between real and fake, potentially misleading audiences (Maras & Alexandrou, 2019). Particularly, videos represent the largest proportion of the content manipulated by deepfakes worsens the problem, as it completely reverses the conventional notion that videos depict the absolute truth (Bates, 2018; Gosse & Burkell, 2020; Köbis et al., 2021; Wagner & Blewer, 2019). Bates (2018) explains that deepfake technology threatens individuals' traditional beliefs about the trustworthiness of live scenes that they have observed. Wagner and Blewer (2019) also indicate that the emergence of deepfakes has disrupted the public's trust in moving images as pure, unalterable truth. Similarly, Gosse and Burkell (2020) point out deepfakes' potential to interfere with any aspect of a shared framework to understand reality. In particular, one study conducted an online experiment to test whether people can detect one of the most difficult deepfake videos, proving that people cannot reliably detect deepfakes but overestimate their abilities to identify them (Köbis et al., 2021). The findings of the experiment confirmed that a lot of online users may fall victim to digital disinformation in the current “post-truth era.”

One of the notorious consequences of deepfake technology is the creation of nonconsensual, hardcore deepfake pornographic videos (DPVs) that superimpose the faces of celebrities onto the bodies of different pornographic actors. Unfortunately, the characteristics of the K-pop industry and idols tend to increase demand for DPVs. To illustrate, K-pop is a world-renowned South Korean pop music style that has become part of the dominant music culture in recent years (Kang, 2016). Idols refer to the K-pop singers raised from an early age under the systematic training provided by entertainment agencies (Cha & Choi, 2011; Shim, 2013). Thus, K-pop idols must work on a strict schedule according to the investments they receive from their agencies, and therefore they are commercially molded and exploited. Specifically, celebrity sex scandals hurt not only the image of the idols themselves but also that of the agency and eventually can affect the company's stock prices, providing a plausible excuse for agencies to control idols' dating lives. Therefore, considering the vulnerability of perfectly imaged idols in the K-pop industry to sex scandals, DPV, which disparages female celebrities, gives the malevolent actors the pleasure of fulfilling undesirable desires (van der Nagel, 2020). For example, Kim (2018) reveals that the sexual objectification of K-pop idols could satisfy men's hidden urges by perpetuating women's subordinate image. Dickson (2019) also claims that anti-fans are likely to feel pleasure or reward from tarnishing innocent female celebrities' reputations. As such, the attributes of the K-pop industry amplify the demand for DPVs.

However, the DPVs cause long-lasting harm to the victims, including emotional distress, physical illness, job loss, and reputational degradation (Bae, 2019; Chesney & Citron, 2019; Melville, 2019). This damage is exacerbated by the nature of cyberspace and deepfake methods. First, it is difficult to control the speed and scope of content production and distribution online. Additionally, the anonymity of online platforms allows DPV creators to produce content without moral accountability. Finally, rudimentary and restrictive regulations on online sex crimes enable creators to commit digital forgery without any legal liability. For example, a partial amendment to the Special Act on punishing sexual violence crimes was approved at a Cabinet meeting, and a law strengthening discipline for deepfake videos began to take effect on June 25, 2020, in South Korea. Still, the law is ineffective for overseas creators (Lee, 2020). In addition to the online environment's problems, the uniqueness of deepfake technology complicates the problem. DPVs are created by deep learning algorithms that are freely accessible anywhere online, thus hindering the political process, allowing anyone to attack cybersecurity systems that are not yet prepared, and creating false beliefs or objectionable sexual content (Gosse & Burkell, 2020; Kolagati et al., 2022). As such, the online environment's characteristics and unique deepfake techniques increase the threat of DPV victimization.

As DPVs are inherently abusive contents and deceptively alter videos without consent, they may elicit negative emotions among general online users. Prior studies have investigated negative feelings about perpetrators’ moral violations, referred to as negative moral emotions (Carver & Harmon-Jones, 2009; Haidt, 2003; Tangney et al., 2007). Negative moral emotions can be categorized into several clusters, including two principal clusters of other-condemning emotions cluster (e.g., anger, contempt, disgust) and self-conscious emotions cluster (e.g., guilt, shame, embarrassment). The first cluster reflects moral emotions toward others with disapproval, while the second cluster includes an ongoing self-evaluation process of the moral worth (Rozin et al., 1999; Tangney et al., 2007). To be specific, contempt often arises from hierarchical relationships, which is felt by one group of members to another group who are slightly inferior, thus linked to racism or prejudice (Rozin et al., 1999). Rozin et al. (1999) found that emotion of disgust is related to violations of divine ethics, such as problems with hygiene or assaults on human dignity; in addition, it involves a tendency to avoid or expel (Haidt, 2003). Moreover, Haidt (2003) contends that shame and embarrassment are triggered by any painful revelation of the self to be flawed or defective, especially that he or she has violated moral standards of action, thus corresponding with motivation to deny, escape, or hide. The difference between the two emotions of shame and embarrassment often relies on the fact that embarrassment occurs more in hierarchical interactions. DPV may not be related to negative emotions elicited upon the hierarchical interactions (e.g., contempt, embarrassment) as well as negative emotions associated with avoidance or hiding tendencies (e.g., disgust, shame, embarrassment) because those emotions may not mediate active behavioral responses in the DPV context.

In the meantime, individuals may experience anger in various situations, such as when affronted, frustrated, or injured by offending others (Carver & Harmon-Jones, 2009; Tangney et al., 2007). Particularly, Tangney et al. (2007) describe anger as an emotion that arises when a perpetrator who has violated basic moral standards is viewed as acting in a morally repulsive manner toward a third party. Likewise, Rozin et al. (1999) illustrate that anger motivates bystanders to rectify injustices that they have observed, similar to other studies’ results suggesting that anger is associated with confrontational coping behaviors that can change stressful situations (Lazarus, 1991). Because DPV is morally reprehensible, fake content generated by an ill-intentioned creator, online users may experience anger if they encounter it. As predicted in previous research, anger can stimulate users to take several coping actions.

On the other hand, guilt results from evaluation of one's own behavior, usually when the individual has violated moral rules (Tangney et al., 2007). Individuals who experience guilt focuses on their bad behavior rather than evaluating themselves as people (Haidt, 2003). Baumeister et al. (1994) explain that guilt is more commonly induced when users believe that their behavior may pose a severe threat to the victim. Moreover, research has shown guilt to foster empathy and motivate individuals to modify or improve situations using constructive strategies (Sheikh & Janoff-Bulman, 2010; Tangney et al., 2007). Further, empirical results indicate that guilt is most effective in stimulating individuals to follow a moral direction in their lives by taking reparative actions such as apologies, confessions, and prosocial behavior (Haidt, 2003; Sheikh & Janoff-Bulman, 2010; Tangney et al., 2007). As such, internet users may feel guilty about their actions after watching DPVs. They are likely to be motivated to correct such actions and situations by evaluating them negatively, feeling empathy for DPV victims, and taking moral countermeasures.

Coping behavior is the process of taking action to address stressful situations (Carver et al., 1989). Previous research has identified problem-focused coping and emotion-focused coping as the two major types of coping behavior (Lazarus & Folkman, 1984). According to Carver et al. (1989), there are variations in problem-focused and emotion-focused coping. While problem-focused coping seeks to actively resolve or change the subject to overcome the stress, emotion-focused coping aims to reduce or control individuals’ stressful emotions. More specifically, problem-focused responses include activities like taking actions directed toward other people to blame, increasing stepwise efforts, or seeking social support through advice, information, and help from higher institutions (Carver et al., 1989). Exercised caution as holding back actions until an opportunity comes is also the problem-focused strategy (Aldwin & Revenson, 1987). Emotion-focused coping involves responses such as seeking social support emotionally, especially for moral approval or understanding (Carver et al., 1989).

In this regard, general online users who watch DPVs may perform two types of coping behaviors after experiencing negative emotions (Carver et al., 1989). In fact, given the anonymity of DPVs creators, a direct confrontation with any DPVs creator is not feasible. In terms of problem-focused coping, users may report DPVs to the police or relevant investigation agencies to seek social help from higher institutions. Moreover, they can ask celebrity management agencies to take corrective measures or ask platform providers to delete DPVs. In terms of emotion-focused coping, users can engage in social advocacy for celebrities with online petitions or emotional support. Therefore, this study considers two types of coping responses in the context of DPV: immediate problem solving and indirect emotional support.

Emotions have an adaptive function related to behavioral tendencies (Plutchik, 1980). Notably, prior literature has revealed that negative moral emotions play an important role in determining individuals' moral decision making and coping processes in the real world (Haidt, 2001, 2003; Monin et al., 2007; Shweder & Haidt, 1993). Accordingly, negative emotions are considered as important predictors of individuals’ moral judgments (Haidt et al., 1993; Shweder & Haidt, 1993). For example, Haidt (2001) highlights that people engage in moral behaviors based on moral emotions. Along the same lines, we also argue that anger and guilt are associated with specific coping responses to malicious deepfake content.

According to prior studies, anger is related to witnessing morally offensive behavior aimed at third parties, inducing bystanders to take action to redress the injustice (Rozin et al., 1999; Tangney et al., 2007). Thus, users who feel anger are likely to enact direct, immediate, and overt punishment for immoral behaviors (Carver & Harmon-Jones, 2009; Fischer & Roseman, 2007). Correspondingly, individuals who may encounter DPVs are likely to engage in active coping behaviors to alter the situation. Furthermore, anger will positively affect the emotion-focused coping behavior of seeking emotional support, as most negative emotions elicit both types of coping (Carver et al., 1989). For this reason, we propose the following hypotheses:

H1a

Online users' anger over DPVs positively affects direct problem-solving behavior.

H1b

Online users' anger over DPVs positively affects indirect emotional supporting behavior.

Research has proven that guilt tends to function as a moral barometer and provide immediate and critical feedback on everyday behavior (Haidt, 2003). Guilt thus strongly influences moral behavior (Tangney et al., 2007). Extant research about guilt has illustrated its association with constructive and proactive pursuits that can change or compensate for guilt-inducing behavior (Haidt, 2003; Sheikh & Janoff-Bulman, 2010; Tangney et al., 2007). More specifically, guilt may inhibit pornography use or hypersexual behavior (Gilliland et al., 2011). Consequently, guilt is likely to be associated with DPV observers’ direct problem-solving responses online. Additionally, as guilt appears to be linked to empathy, it may encourage emotion-focused coping behaviors in DPV contexts (Tangney et al., 2007).

H2a

Online users' guilt over DPVs positively affects direct problem-solving behavior.

H2b

Online users' guilt over DPVs positively affects indirect emotional supporting behavior.

The extant studies have illustrated how individual differences may influence moral sentiments (Shweder & Haidt, 1993; Wang & Kim, 2022) and subsequent behaviors (Carver et al., 1989; Haidt, 2001, 2003; Monin et al., 2007). Moreover, perceptions and acceptance of new information technology may vary depending on individual experiences and characteristics (Gal & Berente, 2008; Xu, 2007). We hypothesized that personal attributes would influence emotions in response to witnessing DPVs online. DPVs are content incorporating new information technologies, but they are inauthentic, illegal, and target individuals sexually without their consent. Thus, DPVs can evoke negative moral emotions and subsequent reactions, the degree of which depends on individual characteristics. Consequently, this study analyzes relevant experiences and features, such as previous tolerance for sexual harassment, prior fondness of celebrities, media exposures, and demographics, to prove the relationship of these variables with anger and guilt, the most representative emotions that we would expect users to feel.

Prior to the actual survey, two pilot surveys were conducted to identify internet users' emotions toward DPVs. The first survey included open-ended questions about feelings after watching DPVs, and the second survey had a quantitative questionnaire. Throughout two pilot surveys, step-by-step, we have tried to identify some negative emotions which are more likely to related to users' coping behavior. In line with literature review on negative emotions, we found that negative emotions related to users’ coping behavior might be anger and guilt. Accordingly, we selected and used anger and guilt as emotional variables in the actual survey.

The survey contained four parts, measuring individuals' preexisting perceptions, negative emotions, coping behaviors, and demographic characteristics. We derived all measures from prior literature, with some modifications to fit our specific research context. All items utilized 5-point Likert response scales ranging from 1 (“strongly disagree”) to 5 (“strongly agree”). We adopted measures of tolerance for sexual harassment from Beauvais (1986) and Mazer and Percival (1989), modifying the Sexual Harassment Attitude Scale (SHAS) to fit the DPV context. We derived items related to celebrity involvement from Wen and Cui (2014) that measured the level of affinity with media figures. To measure the negative emotions of anger and guilt, we used a modified version of Izard et al.’s (1993) Differential Emotions Scale, which has been widely used for understanding individuals' multivariate mood states. We developed behavioral measures from studies by Bowes-Sperry and Powell (1999) and Benavides-Espinoza and Cunningham (2010), which assessed the extent to which participants would take action when observing SH. After eliminating similar items, we modified the questionnaires to fit the DPV and online contexts. We also included demographic information, including gender, age, and average daily video consumption, in the analysis.

We employed partial least squares structural equation modeling (PLS-SEM), using SmartPLS 3.0 as the analytic tool, to test the hypotheses. PLS-SEM is particularly appropriate when dealing with a relatively small sample size (Hair et al., 2011). Further, this approach can simultaneously estimate the structural model with high predictive accuracy, although typically in situations where applications have little available theoretical background (Wong, 2013). We adopted PLS-SEM given our small sample size and the relative insufficiency of existing theory, as discussions on deepfake technology are in their early stages and factors that may influence the individuals’ responses to DPVs have yet to be examined. We also used SPSS 25.0 to enter and code the survey data.

This study sheds light on the recent phenomenon of creating surrealistically crafted media content using AI algorithms. By placing media figures' faces on others' nude bodies, this sophisticated deepfake fabrication technology is causing great harm. However, most previous work has concentrated only on the technological and legal ramifications of deepfakes, with little to no research on online users' responses. To address this gap, this study explored general online users' responses to deepfake pornographic content by analyzing the relationship between individual characteristics, negative emotions, and coping strategies. The results demonstrate that anger is a strong predictor of users' coping behavior in response to DPVs. The PLS-SEM analysis shows that anger has a profound impact on direct reporting of DPVs' existence to related stakeholders, including the police, idols' management agencies, broadcasting deliberation committees, or platform providers. Anger is also associated with users' emotional support of the victims of DPVs. Users tend to socially encourage DPV victims or raise awareness of the issue via online petitions. For example, more than 390,000 South Koreans signed a nationwide online petition to punish DPV creators for sexual crimes. This could have directed public attention to sexually demeaning deepfake videos because the online petition was directly operated by the Blue House, the executive office in South Korea. Consequently, as suggested by prior research results, anger appears to elicit both types of coping responses, direct problem-focused coping behavior and indirect emotion-focused coping behavior, in the DPV context (Carver et al., 1989). However, the findings reveal that guilt is not significantly related to either type of coping behavior. These results indicate that guilt may correct an individual's bad behavior (Haidt, 2003) but may not be sufficiently powerful to induce coping behavior among online users who have encountered DPVs. According to previous literature, guilt exerts a strong influence on individual compensatory, prosocial, and moral actions (Sheikh & Janoff-Bulman, 2010). However, users feeling guilt may not cope directly because the moral behavior of such individuals involves apologizing or confessing, which tends to occur in one-on-one, personal relationships (Haidt, 2003; Sheikh & Janoff-Bulman, 2010; Tangney et al., 2007). Moreover, other empirical results support that guilt alone may not be sufficient to motivate individuals to change, although guilt is related to a desire to rectify socially undesirable behavior (Gilliland et al., 2011). Thus, nonsignificant relationships between guilt and the two coping behaviors are plausible.

Regarding the relationship between individual traits and negative emotions, anger and guilt are negatively related to SH tolerance, while celebrity involvement is positively related to anger only. Specifically, the results imply that individuals' previous opinions of SH are the salient factor generating anger and guilt in the DPV context. This finding suggests that users with more sensitivity to SH are more likely to be angry about deepfake content and even feel guilty when they encounter DPVs. One possible explanation is that this group presumably perceives DPVs as a cruel digital sex crime. Another explanation is that these individuals likely consider the female celebrities in the DPVs as victims of sexual crimes. These perceptions of DPVs and DPV victims may have influenced users' emotional responses. Personal preference for celebrities is also an important predictor of negative emotional reactions to DPVs. Particularly, individuals exhibiting more robust emotional responses tend to be enthusiastic and supportive fans interested in celebrities' happiness and welfare. Therefore, if these individuals witness their favorite entertainer becoming a victim of DPVs and learn that the celebrity is suffering from not only the initial humiliating comments but also from rapid dissemination of content and false information, they are likely to feel angry over the DPV that provoked this situation. Thus, greater affection for K-pop idols tends to yield angrier responses among users to DPVs (Wirth & Schramm, 2005). However, CI does not have a significant relationship with guilt. Guilt over watching DPVs can be expressed regardless of whether individuals like the idols or not. Intuitively speaking, someone with strong affection for idols may feel more guilty about not being able to protect their beloved idols from DPVs, but others may feel less guilty because they believe that DPVs’ production is beyond their control.

While differences in video watching experience do not influence anger or guilt over DPVs, pornography exposure is most strongly, and negatively related to anger and guilt among online users. These results indicate that individuals with more experience with pornographic content tend to respond less emotionally in the DPV context. Consistent with prior research, frequent exposure to hypersexual content can desensitize individuals to similar content (Linz et al., 1984), regardless of who was victimized or what was used to fabricate the video. In contrast, neither anger nor guilt is related to prior video consumption. Given the widespread consumption of videos among the participants—over 80% watched videos for more than 4 h a week (Table 2)—exposure to typical videos may not have been a suitable variable to predict negative emotions. Moreover, in past studies, as repeated exposure to similar content genres (Fanti et al., 2009; Krahé et al., 2011) or violent media (Anderson & Dill, 2000) predicted desensitization, overall media consumption may not be reliably related to emotion.

Gender turns out to be one of the strongest predictors of anger and guilt in the context of DPVs. The findings show that women are more likely to exhibit powerful negative feelings toward the DPVs compared to men. One explanation is that female celebrities are the most frequent targets of DPVs. Furthermore, the memories of women who have experienced SH in real life may increase their empathy for victims and reduce their tolerance for similar online SH content. On the contrary, age does not seem to be related to emotional responses to DPVs. We expected younger individuals to be less sensitive to sexual content because they are frequently exposed to such videos on various online platforms and SNSs, and they can have relatively open conversations about sexual issues. However, in the South Korean context, it is not just the younger generation who have access to the Internet or provocative content. Advances in technology have enabled older individuals to access manipulated online content with SH characteristics. In sum, individuals’ feelings toward DPVs may be similar regardless of age; hence, meaningful relationships may not appear.

This study makes important contributions to both theory and practice. Theoretically, this study sheds new light on the potential coping behaviors exhibited by online users in response to DPVs. The results show that anger is an essential antecedent to both immediately reporting of DPVs and providing emotional support to DPV victims. This aligns with past studies showing that the moral emotion of anger is associated with virtuous coping responses that can change the situation (Carver et al., 1989; Carver & Harmon-Jones, 2009; Fischer & Roseman, 2007). Moreover, this study is one of the timely attempts to examine general online user behavior in the context of deepfake technology. Although several previous studies have addressed deepfake technology's non-technical aspects, there has been little research interest in users who may have encountered DPVs on the Internet. The study of Wang and Kim (2022) is one of the earliest works to identify meaningful relationships between internet users' characteristics and their negative emotions to DPVs. In addition to this, this study expands the discussion of user responses to behaviors. Thus, it may fill the research gap by proposing a research model (Fig. 1) to validate users' different emotional and behavioral responses, which stem from distinct traits and experiences. Moreover, this study classifies personal traits, negative moral emotions, and potential coping behaviors into more specific variables.

This study's results also provide practical implications for platform operators, government, and academia. First, this study highlights the need for stronger governmental efforts to penalize DPV creation. No matter how often users report DPVs to related government organizations, it becomes meaningless if there are no applicable rules to punish DPV creators. Thus, establishing legal foundations for digital sex crimes and fake manipulation videos is an urgent task. Although the South Korean government recently established new DPV-related regulations, they apply only to those who produce or distribute DPVs and not to those who consume or watch them (Kang, 2021). However, it seems necessary to punish consumers because female celebrities are suffering from excessive distribution and production of DPVs, and this supply often stems from the corresponding demand. Besides, the fact that deepfake perpetrators can remain anonymous and that most of them are agitators from abroad suggests that the current regulations are ineffective. Therefore, the government should continuously supplement and revise DPV-related legislation.

Second, this study suggests that platform operators should assume social responsibility for controlling malicious deepfake content. Although netizens must cope with the DPVs, the issue can be resolved only with platforms' effective policies or technological developments that prevent the creation, dissemination, and distribution of illegal content. Even showing a willingness to block DPVs, platform operators can discourage content production and prevent serious consequences. For example, Facebook is one of the leading companies taking preemptive actions to prohibit malicious deepfake content. Facebook first announced that it would ban the posting of deepfakes and immediately delete related content ahead of the 2020 US Presidential Election (Room et al., 2020). Technically, Facebook held a Deepfake Detection Challenge (DFDC) with Microsoft, AWS, and Partnership on AI to facilitate the development of new AI technologies that can identify media manipulations. However, there also are limits to the platforms’ endeavors because certain conditions must be met for the content to be blocked. Thus, attempts at platform-level solutions are meaningful but not sufficient to address the DPV problem. That is why media literacy, which allows users to accurately understand the context of the content and to view media critically, seems ever more important.

Such a need for media literacy is associated with the necessity of strategic digital literacy education. Digital literacy education may help online users understand the opportunities and threats in the online environment and practice digital technology ethics. Such education may include programs that enhance individuals' abilities to discern fake content or predict the possible intentions behind it. This process appears to be vital in the so-called post-truth era, where the line between truth and falsehood largely has become blurred. In addition, the current study's findings reveal that less tolerance for SH and less exposure to pornographic content are likely to elicit more anger, the emotion associated with individuals' prosocial behaviors in the DPV context. These results support the argument that we must improve sex education programs for media users. Curricula on gender sensitivity could help students fully understand gender differences and pursue gender equality. Better explanations about sex crimes in the digital environment and various coping strategies related to online SH, whether users are victims or bystanders, are also required. Furthermore, there should be educational efforts to make people feel uncomfortable with, realize the seriousness of, and understand the appropriate measures to handle digital sex crimes from an early age. By understanding online sex crimes and the potential victims of DPVs, this study anticipates the growth of active grassroots participation in reporting, detecting, and banning DPVs featuring K-pop idols. These potential programs we have listed may be conducted not only by schools but also by IT companies or celebrity management agencies. In sum, through collaborative efforts among schools, online platforms, and the government, we expect that the harm resulted from DPV proliferation can be alleviated.

Despite its meaningful implications, there are several limitations to this study. As an exploratory study that attempted to identify the antecedents of emotional and behavioral responses to DPVs among general online users, this study investigated significant impacts of individuals' perceptions, media experiences, and demographic characteristics on emotions and behaviors. However, the predictors suggested here may not completely explain users' experiences with DPVs. Other predictors could be included or excluded to analyze users' behaviors more comprehensively. Specifically, it would be necessary to examine how individual's personality or other psychological factors influence negative emotions and coping behavior. Future research is required to verify and improve this exploratory model by narrowing the possible influential factors and focusing on specific ones. In addition, this study provided a text scenario and related screenshots of DPVs to measure online users' responses via an online survey. Although the estimations may be limited, this method was the next-best option that still met the institutional review board's research ethical guidelines. Thus, future experimental studies may provide a fuller picture of users' responses to DPVs. Experiments may expose respondents to real deepfake pornographic videos, not images or text. Furthermore, the present study took place in South Korea, a country with one of highest internet penetration rate as of January 2022 (Johnson, 2022), as well as where the K-pop idol industry originated; it is also still a conservative and patriarchal society. Thus, this study's participants may not only be technologically more aware of DPVs but also more hostile to them. Comparative studies conducted with viewers in other countries could validate and generalize this study's proposed model.