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Asian Communication Research
[ Original Research ]
Asian Communication Research - Vol. 22, No. 2, pp.30-30
ISSN: 1738-2084 (Print) 2765-3390 (Online)
Print publication date 31 Mar 2025
Received 25 Jul 2025 Revised 02 May 2025 Accepted 20 May 2025
DOI: https://doi.org/10.20879/acr.2025.22.009

Weaponizing Visibility: Online Shaming and Vigilantism During COVID-19

Edson C. Tandoc Jr. ; Guan Peng Loy ; Seth Seet ; Langcheng Zhang
Wee Kim Wee School of Communication and Information, Nanyang Technological University, Singapore

Correspondence to: Edson C. Tandoc Jr.Wee Kim Wee School of Communication and Information, Nanyang Technological University, Singapore, 31 Nanyang Link, Singapore. Email: edson@ntu.edu.sg

Copyright ⓒ 2025 by the Korean Society for Journalism and Communication Studies

Abstract

During the COVID-19 pandemic, as countries implemented regulations to curb the spread of COVID-19, social media users called on others to follow the measures while capturing and uploading images of those violating the rules. Guided by the frameworks, theory of planned behavior (TPB) and belief in a just world (BJW), the current study focuses on the context of Singapore to identify factors behind engaging in such acts of online shaming, and whether these constitute online vigilantism. Based on an online survey in Singapore (n = 1000), and using a binary logistic regression, this study found that those who perceive online shaming as a commonplace behavior, and who think it is expected of them to do so, were more likely to engage in online shaming. Conversely, attitude and perceived behavioral outcome did not predict online shaming. Additionally, those who have strong BJW for others were more likely to engage in online shaming, providing evidence that for some, online shaming is a form of online vigilantism. However, those with a strong BJW for self are less likely to engage in online shaming. These suggest that for some, online shaming is a form of online vigilantism, motivated by a sense of justice.

Keywords:

COVID-19, online vigilantism, shaming, social media, SingaporeCOVID-Singapore

In May 2021, the Singapore police arrested a woman after a video of her refusing to wear mask and berating a safe-distancing ambassador who had asked her to do so had gone viral (Tang, 2021). Soon after, many social media users uploaded more videos of her not wearing a mask in various locations. In August 2021, a British national was sentenced to six weeks in jail in Singapore a few months after a video of him not wearing a mask inside the train had also gone viral (Alkhatib, 2021). Singapore, a small Asian nation that was among the first few countries to be severely hit by the COVID-19 pandemic, strictly enforced mask-wearing starting in April 2020, along with other safety measures, such as safe distancing and restrictions to group activities, to curb the spread of the virus (Mahmud, 2020). Thereafter, social media teemed with posts, images, and videos showing and shaming those seen breaching the rules. For example, Facebook groups dedicated to reporting and shaming such transgressors in Singapore were created, attracting substantial followers and audiences, a phenomenon many considered as a form of online vigilantism (Mahmud, 2020).

Vigilantism refers to when citizens take it upon themselves to punish, outside the legal framework, others who have done wrong (Kosseff, 2016). Vigilantism has become easier online, as vigilantes can stay anonymous and easily punish others in several ways. Online vigilantism usually takes the form of online shaming (Skoric et al., 2010), an act widely documented in Singapore during the COVID-19 pandemic (Alkhatib, 2021; Mahmud, 2020; Tang, 2021). While online shaming refers to the acts of uploading and sharing images, videos, and information about target individuals—in this case, those believed to be violating rules—online vigilantism involves acts that are motivated by seeking punishment for the targets as a form of social justice. Thus, online vigilantes upload photos of those accused of wrongdoing but may also leak some personal data of the targets, such as home or workplace addresses, to either inconvenience these targets or even expose them to harm (Loveluck, 2019). This current paper examines online shaming and vigilantism during the COVID-19 pandemic in Singapore, a city-state known for its high levels of internet and social media penetration. National surveys estimate that about 88% of Singapore residents regularly use messaging platform WhatsApp while 70% use social media platform Facebook (Tandoc, 2021). Thus, Singapore provides an appropriate context for this study.

Some scholars have also referred to “everyday authoritarianism” in the city-state, where authoritarianism is not only top-down or state-driven but also entails grassroots practices, where the people act as the state’s partners to implement policies and punishments (Ibrahim, 2018). The existing political structures, prevailing social norms, and the collectivist culture in the region have also shaped citizenship in Singapore as being more supportive of state policies (Noh & Tumin, 2008). Thus, scholars have also suggested these contexts to explain public support for online vigilantism in the Singapore context (Tan & Khader, 2022). Mindful of these social contexts, this current study focuses on the individual level to understand what leads some individuals to engage in the online shaming of those who flout COVID-19 rules in Singapore and examines the extent to which this may be construed as online vigilantism—that is, whether these acts are motivated by a sense of justice. Drawing on the frameworks of the theory of planned behavior (TPB) and the belief in a just world (BJW), the current study uses a national online survey to examine factors that lead social media users in Singapore to engage in online shaming and vigilantism, particularly in relation to control measures amid the COVID-19 pandemic.

LITERATURE REVIEW

Online Shaming and Online Vigilantism

Social media have become deeply embedded in people’s everyday lives, providing opportunities for users to engage in civic discourse and opinion expression, among other types of political engagement (Shah et al., 2005). But these platforms have also provided channels for hateful speech, bullying, and shaming. Among various forms of negative online behaviors, one area that has attracted increasing scholarly attention is online vigilantism. Online vigilantism has been defined and operationalized in various ways. For example, scholars have examined cybersecurity counter-hacking, hacktivism, online scambaiting, and online shaming as vigilante acts (Loveluck, 2019; Smallridge & Wagner, 2020). Studies have also used alternative terms to refer to online vigilantism. For example, Loveluck (2019, p. 3) used “digital vigilantism” to broadly refer to “online direct actions in response to perceived civil or moral transgressions, crimes or injustices.” This broad definition also describes digital vigilantism as “direct online actions of targeted surveillance, dissuasion or punishment which tend to rely on public denunciation or an excess of unsolicited attention, and are carried out in the name of justice, order or safety” (Loveluck, 2019, p. 5).

In conceptualizing online vigilantism, Smallridge et al. (2016) relied on Johnston’s (1996) definition of vigilantism. Johnston (1996) had identified six elements of vigilantism: it involves planning prior to action; the perpetrator is a private agent, not acting on behalf of the state; the vigilante does not receive any support from the state; it involves the use of force; it is motivated by the desire to preserve social order or punish someone who committed a crime; and involves the intention of ensuring community safety. Smallridge et al. (2016) argued most of these elements also characterize vigilantism in online spaces, as cyber-vigilantes also act autonomously and are not sanctioned by the state. The only element not necessarily applicable to the online context is the use of force. Thus, they recommended understanding cyber-vigilantism in “a broader spectrum of harm” (Smallridge et al., 2016, p. 66). In this broader spectrum, online vigilantism does not necessarily cause physical harm, but it usually causes psychological harm (Smallridge et al., 2016) through verbal threats, abuse (Trottier, 2017), or “symbolic violence” (Loveluck, 2019, p. 3). Psychological harm online is often achieved through shaming, when people upload and share unflattering images, videos, and information about target individuals without the target’s consent. Thus, some studies examine online vigilantism by focusing on acts of online shaming. For example, while Skoric et al. (2010, p. 181) referred to “civic vigilantism,” the study exclusively focused on “online shaming” that targets “socially undesirable behaviors, such as unsafe driving and bad parking and signalling a revival of shame as a form of social control.”

What differentiates online vigilantism from online shaming and other negative online behaviors is the motive behind the vigilante’s acts. Johnston (1996) argued that a defining feature of vigilantism is the actors’ desire to preserve social order and ensure community safety. In other words, vigilantes tend to believe that what they do is congruent with social norms and restoring social justice. Thus, while cyberbullying is also intended to hurt or humiliate someone online, the motivation of cyberbullies does not necessarily include social justice or public safety concerns (Keith & Martin, 2005). Unlike vigilantes, some cyberbullies are aware of the criminal nature of their acts and that their acts are not endorsed by social norms or policies. In a country like Singapore, where the government enjoys a high level of public trust, which further strengthened during the pandemic, with the public supporting state-led safety measures (Yuen et al., 2021), online shaming of those who violated government instituted safety measures can be construed as a form of support for state policies rather than cyberbullying.

The nature of the transgression being targeted also distinguishes online vigilantism from other acts. In online vigilantism, which can involve online shaming with the intention to punish a target person, the social transgression that merits punishment is usually criminal in nature, a violation of the law (Smallridge & Wagner, 2020). Indeed, vigilantes are those who take the law into their own hands (Johnston, 1996). While the violations targeted by online vigilantes may involve serious offenses such as large-scale corruption, they may also refer to day-to-day transgressions. For example, during the COVID-19 pandemic, online vigilantes in Singapore used their mobile phones to snap images of individuals violating the mask mandate and safe distancing measures and uploaded these photos online (Mahmud, 2020). Thus, online shaming of COVID-19 policy violators can be conceptualized as a commonly observed form of online vigilantism, which weaponizes online visibility, putting the online spotlight on a target person and behavior (Hou et al., 2017; Oravec, 2020). Such behavior is carried out by individuals against those who had committed social transgressions or unlawful acts (Skoric et al., 2010).

Based on these studies and their conceptualizations, this current study conceptualizes the acts of sharing and uploading images and videos of individuals perceived to have violated COVID-19 safety rules in Singapore as constituting online shaming and, when they are motivated by a sense of justice, or the desire to punish a social wrong, these acts may also constitute online vigilantism. In this case, online visibility is weaponized against perceived transgressors to mete out a symbolic form of punishment, where the goal is either to humiliate a particular person to enforce behavioral change across society, or to attract the attention of authorities to restore social order and justice (Loveluck, 2019). Hence, to examine people’s intention to engage in online shaming, this study utilizes the theory of planned behavior. However, to explore whether online shaming constitutes online vigilantism, this study applies the concept of belief in a just world to examine the motivational aspects of intention to engage in online shaming behavior.

Theory of Planned Behavior

The first goal of this current study is to examine antecedents to engaging in the online shaming of those who violate COVID-19 safety rules. This study turns to the theory of planned behavior (TPB) for conceptual guidance. TPB argues that one’s engagement in a specific behavior is a function of one’s attitude toward the behavior, perceptions of norms around the behavior, and one’s perceived behavioral control (Beck & Ajzen, 1991). TPB examines the influence of each factor; for example, an individual may have positive attitudes toward a behavior but may still not engage in the behavior if it is perceived as too difficult or complex or is beyond one’s behavioral control (Bresnahan et al., 2007). Numerous studies have drawn on the framework to examine a range of behaviors, such as smoking cessation (Lee et al., 2006), exercise (Cho et al., 2020), and recycling (Strydom, 2018). It has also been used to examine online behaviors, such as cyberbullying (Auemaneekul et al., 2020) and online shopping (Wu & Song, 2021).

TPB argues that intention is an important precursor to actual behavior (Ajzen, 1991). One’s intention to engage in a behavior can be shaped by three factors: attitude, perceived norms, and perceived behavioral control. Attitude refers to whether an individual holds “favorable or unfavorable evaluation or appraisal of the behavior” and the probability that the behavior will effectuate the outcome they associate with it (Ajzen, 1991, p. 188, 2020). A positive evaluation of both the behavior itself and the outcome of the behavior leads to intention to engage in that behavior. For example, positive attitudes toward healthy eating were found to correlate with the behavior of consuming healthy food (Conner et al., 2002). Attitude also encompasses the perceived probability of the outcome. Thus, other studies utilizing TPB have also operationalized attitude as outcome expectancy (Rocheleau, 2013). For example, qualitative and quantitative studies have found that the positive benefits of online shaming—preventing further harm—motivates people to participate in online shaming, with negative consequences prompting the reverse (De Vries, 2015; Pundak et al., 2021). This expected outcome is a salient factor for understanding online shaming and especially so for online vigilantism, where the outcome expectancy—punishing criminals and enforcing social justice—is integral to the behavior (Loveluck, 2019; Smallridge et al., 2016). However, examinations into online shaming and vigilantism have not examined the outcome expectancy component of attitude toward the behavior.

Perceived subjective norms refer to perceptions of social pressure to engage in a specific behavior. Under the original TPB, subjective norms referred to “the perceived social pressure to perform or not to perform the behavior,” which is understood as whether “important others” approve of the behavior (Ajzen, 1991, pp. 188, 195). This measure of subjective norms have thus since been further delineated into two types of norms: descriptive and injunctive (Ajzen, 2020; Cialdini et al., 1991). While descriptive norms “refer to beliefs about what is actually done by most others in one’s social group,” injunctive norms include a sense of obligation motivated by “a desire to avoid social sanctions” (Lapinski & Rimal, 2005, p. 130). Through a meta-analysis, Rivis and Sheeran (2003) found that this delineation between injunctive and descriptive increases the predictive power of TPB. Injunctive and descriptive norms have been shown to predict intention in numerous TPB studies and contexts, such as healthy lifestyle behaviors (Smith-McLallen & Fishbein, 2008), plagiarism (Curtis et al., 2018), and contraception (Fekadu & Kraft, 2002). Regarding online shaming, it is possible that descriptive and injunctive norms are also at play. When online shaming is considered a collective action endorsed by current social norms, such as the notion of everyday authoritarianism (Ibrahim, 2018), one’s perception of how widespread it is may also affect intention to partake in it.

Finally, perceived behavioral control (PBC) refers to an individual’s perception of the level of difficulty in carrying out the behavior. Individuals will weigh the various factors, both within and beyond their control, that will impact their level of success if they are to engage in a behavior before engaging in it (Rotter, 1966). For example, those who believe they are adept at online shopping are more likely to continue shopping online (Wu & Song, 2021). Participants of online shaming have indicated that the ease afforded by mobile phones to capture offenders makes recording events commonplace and simple (De Vries, 2015).

Thus, based on the TPB, this current study hypothesizes that:

  • H1: Online shaming is positively related to a) the valence of one’s attitude toward such behavior; b) the expected outcomes of such behavior; c) subjective norms regarding such behavior; and d) perceived control over such behavior.

While TPB has been used extensively to predict various behaviors, it has also been subjected to several limitations and criticisms, such as TPB not accounting for emotional influences or past habits (Sniehotta et al., 2014). Moreover, while TPB accounts for people’s evaluation of a behavior and its outcomes (Ajzen, 2020), it does not account for specific motives for engaging in a behavior. For example, Corbett (2002) found that water conservation efforts are also impacted by financial motivations, apart from the existing TPB variables. Likewise, McLachlan and Hagger (2011) found that intention to exercise is also affected by one’s intrinsic motivation, namely, enjoyment. In the case of online shaming, one potential motivation is vigilantism, where shaming is done to address unpunished wrong behavior (Skoric et al., 2010). This is akin the concept of a belief in a just world, which may act as an intrinsic motivation. Hence, this study also turns to the framework of belief in a just world (Lerner & Miller, 1978).

Belief in a Just World (BJW)

What may turn online shaming into a form of online vigilantism is the underlying motivation of carrying out social justice by exposing and punishing a social wrong. Indeed, taking matters into one’s own hands also derives from a sense of prevailing injustice in society (White & Rastogi, 2009). During a pandemic, flouting health regulations is regarded as transgressions against public safety and ignoring one’s social responsibility (Koh, 2020). Hence, shaming people who violate safety rules may be a form of online vigilantism motivated by ideals of fairness, justice, and concern for public health. Therefore, the second goal of this study is to examine the extent to which sense of justice drives engagement in online shaming of those who violate safety rules. For this, we turn to the concept of belief in a just world (BJW).

The BJW framework argues that “individuals have a need to believe that they live in a world where people generally get what they deserve” (Lerner & Miller, 1978, pp. 1030-1031). Thus, the BJW can be seen as a cognitive attempt to identify an image of a stable world, as opposed to a frightening and hopeless world, which enables individuals to make and execute long term plans (Lerner, 1980). Such a belief helps people to deal with their experiences with injustice and people are motivated to preserve this belief when it is threatened, by either taking actions to restore justice or changing their perceptions of the situation if they think justice cannot be restored (Lerner, 1980). Indeed, this condition of taking action speaks to certain elements of the TPB framework, such as behavioral control and outcome expectancy. But since TPB does not specifically incorporate this cognitive need for a sense of justice, this current study brings TPB together with the BJW framework.

After its conception, BJW was explicated to BJW for self (BJW-self) and BJW for others (BJW-others) (Lipkus et al., 1996). BJW-others refers to the belief that the world is generally fair and that others get what they deserve, while BJW-self refers to one’s belief that the world is fair to them and that they get what they deserve (Lipkus et al., 1996). Based on the original scales, Dalbert (1999) developed a new shorter scale focusing on personal and general BJW, measuring the extent people believe that they are treated justly, and that the world is generally a just place; both scales produce similar results (Dalbert, 1999). Hence, this study will use the term and scale for BJW-self and BJW-others as created by Lipkus et al. (1996). BJW-self and BJW-others influence people differently. BJW-self leads to better mental health and wellbeing, unlike BJW-others (Bègue & Bastounis, 2003; Dalbert, 1999; Sutton & Douglas, 2005). Stronger BJW-others has also been found to be linked to victim-blaming: If something bad happens to someone, those with stronger BJW-others tend to think that the victim deserves it or is the one to blame (Bègue & Bastounis, 2003; Correia et al., 2012). In contrast, BJW-self was found to be unrelated to the derogation of victims or minorities (Bègue & Bastounis, 2003). Instead, it was positively linked to greater acceptance of vulnerable groups (Bègue & Bastounis, 2003). However, online shaming is an ambiguous behavior. On one hand, it can be understood as punitive behavior, ensuring that a target person is socially punished through the unwanted visibility. In this way, it may be driven by BJW-others, which is associated with stronger support for punitive actions against offenders (Bègue & Bastounis, 2003), including online shaming (Hou et al., 2017). On the other hand, online shaming can also be construed as pro-social behavior, especially if the act is motivated by a desire to preserve social justice and prevent future harm. In this way, it might be driven by one’s BJW-self, which is found to be associated with defending victims of bullying (Correia et al., 2009) and taking action to aid vulnerable individuals (Silver et al., 2015). This overlaps with online shaming and vigilantism which includes preventing future harm (De Vries, 2015). Hence, when online shaming is driven by one’s belief in a just world, it becomes a form of online vigilantism. Given these considerations, this current study also explores how BJW contributes to intention to engage in online shaming, answering the following question:

  • RQ1. To what extent are belief in a just world for a) others and b) self, related to engagement in online shaming?

METHOD

Following approval from the Nanyang Technological University, Singapore University’s Institutional Review Board (IRB), a local-based polling company recruited 1,000 adult residents to participate in a national online survey. The survey was conducted in July 2020, when the total number of COVID-19 cases in Singapore breached 45,000 following outbreaks in crowded migrant worker dormitories and a slew of government regulations to curb the spread of the virus. Participants received incentives from the polling company in the form of points redeemable for shopping vouchers. The sample sought to match the adult population distribution in Singapore. The average age is 38.75 (SD = 12.04) and 48.1% were female. In terms of ethnicity, 75% identified as Chinese, 15% were Malay, 8% were Indian, and 2% selected “others.” Some 58.9% had at least a university degree or higher. In terms of monthly household income, 24.7% reported having below $4,500 while 32.9% reported having more than $9,000.

A confirmatory factor analysis (CFA) was conducted using maximum likelihood estimation in lavaan in R to test the latent factors in this study. The model demonstrated adequate fit to the data: χ² (467) = 1866.21, p < .001, CFI = .94, TLI = .93, RMSEA = .055 (90% CI [.052, .058], p = .001 for RMSEA ≤ .05), and SRMR = .04. These values suggest an acceptable to good fit.

Measurement

Online shaming. This variable is based on four items based on the actual context of Singapore during the pandemic. Following the government requirement to wear masks and practice safe distancing outdoors, social media groups were created to post about those who violate these regulations, such as the Facebook group sgcovidiots (Mahmud, 2020). In the survey questionnaire, participants were asked to indicate using a 5-point scale, from never (1) to six or more times (5), how often in the past few weeks they did the following: Post on social media a photo/video of someone not wearing a face mask; share someone else’s post about people not wearing face mask; post on social media a photo or video of people violating safe distancing; share someone else’s post about people violating safe distancing. This scale was self-created for the context of this study, informed by both the qualitative interviews and survey measures of online shaming developed by Skoric et al. (2010) and Tandoc et al. (2024), adapted to the context of online shaming during COVID-19. The scale is reliable, Cronbach’s α = .94. Some 49% of the participants reported having never engaged in online shaming, M = 1.84, SD = 1.12.

Attitude: valence. This variable is measured by two items adapted from previous TPB studies (Tandoc et al., 2024), using a 5-point Likert scale from strongly disagree (1) to strongly agree (5). The participants were asked how much they agree that posting or sharing photos/videos of people who do not wear face masks or violate safe distancing is: a good thing to do; and a responsible action to make. The scale is reliable, Cronbach’s α = .85. The data showed an overall neutral attitude toward online vigilantism, M = 3.01, SD = 1.03.

Attitude: outcome expectancy. This variable is also based on three items adapted from previous studies that incorporated outcome expectancy into the attitude construct of the TPB framework (Tandoc et al., 2024). The participants were asked to rate using a 5-point Likert scale, from strongly disagree (1) to strongly agree (5), how much they agree that posting or sharing photos/ videos of people who do not wear face masks or violate safe distancing: helps discourage violators; helps encourage others to follow the rules; and helps the government in catching the violators. The scale is reliable, Cronbach’s α = .88; M = 3.49, SD = 0.92.

Descriptive norms. This variable is measured using two items adapted from previous TPB studies into the COVID-19 safety measures context (Tandoc et al., 2024). Participants were asked how often they come across a social media post showing a photo/video of someone not wearing a face mask, and of people violating safe distancing. The participants rated frequency on a 5-point scale, from never (1) to six or more times (5). The scale is reliable, Cronbach’s α = .81; M = 2.48, SD = 1.18.

Injunctive norms. This variable concerns people’s normative expectations of themselves and is measured by four items adapted from previous TPB studies (Tandoc et al., 2024). The participants were asked to rate using a 5-point Likert scale, from strongly disagree (1) to strongly agree (5), how much they agree that posting or sharing photos/videos of people who do not wear face masks or violate safe distancing is: something that is expected of me; something that the government recommends; something that responsible citizens should do; and something that I should do as a citizen. The scale is reliable, Cronbach’s α = .92; M = 2.97, SD = 1.04.

Perceived behavioral control. This variable is based on two items and phrased consistently with previous TPB studies (Tandoc et al., 2024). The participants were asked to rate using a 5-point Likert scale, from strongly disagree (1) to strongly agree (5), how much they agree that if they see some people not wearing masks or not practicing social distancing outside: it is easy for me to upload and share a photo or video of them, and I know how to capture a photo or video for evidence. The scale is reliable, Cronbach’s α = .85; M = 3.04, SD = 1.06.

Belief in a just world for self and others. These two variables are each measured by eight items used in previous BJW studies (Lipkus et al., 1996). For BJW-others, participants rated on a 5-point Likert scale their agreement with eight statements such as “I feel that people get what they deserve,” and “I feel that the world treats people fairly.” The scale is reliable, Cronbach’s α = .92; M = 3.23, SD = 0.78. For BJW-self, the participants also rated eight items on a 5-point Likert scale, including statements such as “I feel that the world treats me fairly,” and “I feel that I get what I deserve”. The scale is also reliable, Cronbach’s α = .90; M = 3.38, SD = 0.69.

RESULT

This study conducted a binary logistic regression analysis to test the hypotheses. The model was statistically significant in explaining the variance in engaging in online shaming of those who flout COVID-19 regulations (χ2 (11) = 422.94, p < .001). The model explained between 36.6% (Cox and Snell R Square) and 48.9% (Nagelkerke R Square) of the variance, accurately classifying 77.6% of cases. Based on the Hosmer and Lemeshow test, the model was a good fit to the data (χ2 (8) = 5.24, p = .731). Controlling for demographics—age, gender, education, and income—only age (B = -.017, Wald = 5.48, p = .019, Exp (B) = .984, 95% CI [.970, .997]) and gender (B = -.365, Wald = 4.25, p = .039, Exp (B) = .694, 95% CI [.491, .982]) were significant predictors. This means that younger and male respondents were more likely to engage in the online shaming of violators during COVID-19.

H1a-d predicted that a) attitude-valence, b) attitude-outcome expectancy, c) subjective norms, d) perceived behavioral control would be positively related to engagement in online shaming. The analysis found that attitude-valence (B = -.045, Wald = .102, p = .750, Exp (B) = .956, 95% CI [.723, 1.262]), attitude-outcome expectancy (B = -.20, Wald = 2.40, p = .122, Exp (B) = .818, 95% CI [.635, 1.055]), and perceived behavioral control (B = .183, Wald = .916, p = .339, Exp (B) = 1.20, 95% CI [.826, 1.746]) were not significant predictors. Thus, H1a, H1b, and H1d are not supported.

H1c focused on the effect of subjective norms. Following previous studies, we tested both descriptive and injunctive norms. Descriptive (B = .968, Wald = 119.43, p < .001, Exp (B) = 2.63, 95% CI [2.213, 3.131]) and injunctive (B = 1.01, Wald = 46.05, p < .001, Exp (B) = 2.74, 95% CI [2.049, 3.670]) norms were both significant predictors. Thus, H1c is fully supported. Those who perceive online shaming as commonplace as well as a behavior that is expected of them tend to engage in these acts more often.

Finally, RQ1 explored the impact of beliefs in a just world (BJW) for self and others on frequency of engaging in online shaming. The result shows that BJW-others was a significant and positive predictor of engaging in online shaming (B = 1.05, Wald = 30.63, p < .001, Exp (B) = 2.85, 95% CI [1.968, 4.135]), while BJW-self was a significant and negative predictor (B = -.63, Wald = 9.41, p = .002, Exp (B) = .53, 95% CI [.356, .797]). This means that those with a strong belief that the world is generally fair to people are more likely to engage in online shaming, while those who believe the world is fair to them are less likely to do so (see Table 1).

Predicting Online Vigilantism

DISCUSSION AND CONCLUSION

Guided by the frameworks of TPB and BJW, the current paper sought to examine factors affecting whether people engage in online shaming of people who violated mask-wearing and safe distancing policies in Singapore during COVID-19 and whether this is motivated by a sense of justice, using online shaming as a form of online vigilantism. The analysis found that of all the TPB variables, only subjective norms—injunctive and descriptive norms—predicted online shaming behavior. Those who perceived online shaming as a behavior that is common as well as one that is expected of them to do as responsible citizens were more likely to engage in these acts. However, the other TPB variables did not predict online shaming behavior. This is consistent with discussions of the collective nature of online shaming and vigilantism, which may be rooted in ensuring community order and safety (Banaji et al., 2019; Loveluck, 2019; Smallridge et al., 2016). In contrast, the analysis found that attitude toward the behavior and ease of engaging in it exerted no impact on engagement in online shaming. It is plausible that one’s personal attitudes toward a behavior may no longer matter when engagement in the behavior is perceived as required or endorsed by social norms, especially in Singapore, which displays high conformity to social norms and pressures (Gelfand, 2012). For some people, online shaming may also be a matter of joining the bandwagon, hence the impact of descriptive norms. Another potential explanation for this result is that people are simply highly ambivalent toward online shaming, evident by the mean and standard deviation of the attitude construct. People, having no strong opinion about online shaming, may rely on other factors other than their personal attitude toward online shaming when deciding to participate or not participate in online shaming.

The non-significance of the outcome expectancy component of attitude may also imply that for some participants, shaming those who violated COVID-19 safety rules is a form of punishment—it is something that violators deserve—but whether that punishment leads to other socially desired outcomes, or whether they think online shaming is a positive action is not so much a concern. For them, the important thing is for justice to be immediately preserved, even if done with an unproductive and disliked act. Taken together, these suggest that online shaming is primarily driven by normative beliefs. One such belief is a belief in a just world. This is supported by results from the belief in a just world (BJW) framework.

While TPB is a general framework that can help to explain various behaviors, the original model does not specifically focus on an individual’s sense of justice. While this study’s measurement of outcome expectancy focused on socially desirable outcomes, such as ensuring public safety and discouraging perceived negative behaviors, the BJW framework argues that individuals have a cognitive need to believe that the world is fair, or what we may refer to as a sense of justice (Lerner, 1980). We have argued that when it drives engagement in online shaming, such a belief may turn online shaming into a form of online vigilantism, an act that is conceptualized to be motivated by the desire to preserve or restore social justice by ensuring that those who challenge social order are punished in one way or another (Johnston, 1996; Smallridge & Wagner, 2020). The analysis found that BJW-others—that is, believing that people in general are treated fairly in this world—was positively related to engagement in online shaming, while BJW-self—that they themselves get what they deserve—was negatively related to engaging in online shaming.

This shows that those who believe the world is generally fair are also more likely to take part in handing out punishment to violators, such as by shaming them online or publicly flagging their problematic behavior. Doing so preserves their belief that the world is fair. They are more likely to believe that violators deserve to be punished and therefore partake in giving the punishment, instead of letting these social violations go unpunished. In this sense, we see how online shaming becomes a form of online vigilantism—the online visibility forced upon a target person is weaponized as a form of punishment for violating social rules. In contrast, we found a negative effect from BJW-self. This supports previous studies that found that only BJW-others, and not BJW-self, is associated with stronger support for punitive actions against offenders (Bègue & Bastounis, 2003), including online shaming (Hou et al., 2017). As BJW-self is oft found to be related to defending vulnerable groups (Bègue & Bastounis, 2003), it is possible that people do understand the moral ambiguity of online shaming (Laidlaw, 2017), that it can sometimes be excessive, till the point of unnecessarily harming the target. Similarly, BJW-self is also tied to willingness to forgive (Strelan & Sutton, 2011). Hence, those with higher BJW-self may shy away from such excessive action against violaters. The inclusion of BJW again demonstrates that intrinsic motivations can impact intention to engage in certain behaviors, apart from the original TPB variables.

In summary, this study found that perception of social norms around online shaming may be driving individuals to engage in online shaming in Singapore, especially during the pandemic. For some individuals, engaging in online shaming is a form of online vigilantism, as it is motivated by their sense of justice, seeing online shaming as a form of punishment for a social wrong. However, it must be noted that online shaming also has its dark side. In 2018, after footage of a cyclist breaking the side mirror of a vehicle attempting to overtake him was posted online, netizens soon published the name and family of the man they thought was the cyclist, leading to extensive online harassments (How, 2018). The internet users, however, got it wrong. They tagged the wrong person. While online shaming as a form of online vigilantism may be rooted in a sense of justice, such as what this current study found, it is also prone to mistakes that may cause more harm than good. Indeed, scholars have warned that online vigilantism has many problems: it is often fuelled by anger and involves aggression; it substantially threatens privacy and may incur offline harassment; and it may eventually disrupt social control, making the world more anarchic (Hou et al., 2017; Laidlaw, 2017; Solove, 2007). Thus, while online vigilantism may be motivated by a sense of justice, it may not always lead to a just outcome.

Of course, the findings of this study must be examined through a set of limitations. First, to keep the questionnaire length manageable for participants, some of the scales used to measure the variables consisted of only two items. This may have introduced some limitations to these measures as well as restricted the variance in the responses. Second, as this paper is exploratory in examining the role of BJW in online shaming, this study only examined direct relationships; however, there may be more complex interplays between BJW and TPB, such as moderated and mediated relationships among the variables of interest, which this study did not examine. Future studies can expand on this further by theorizing potential mediation and moderation between BJW and TPB. Moreover, it is likely that other factors, such as personal ethics, or legal repercussions, would impact people’s intention to engage in online shaming and vigilantism, factors that this study did not account for; future studies can build on this study to examine how these other pressures impact people’s online shaming intentions.

Third, we focused on specific acts of online shaming—posting and sharing images of those not wearing masks or violating safe distancing measures. Future studies should build on the results we presented to examine other types of online vigilantism, such as launching an investigation that may also result in doxing. Fourth, guided by TPB and BJW, we focused on individual-level factors, when online vigilantism is rooted in notions of social justice. Thus, future studies should also explore the effects of contextual factors, such as culture. For example, Singapore is an Asian nation considered to be a collectivistic society. How does online vigilantism pan out in individualistic communities? While we acknowledged what others have referred to as “everyday authoritarianism” in Singapore, where residents may be seeing themselves as part of enforcing rules in the city-state (Ibrahim, 2018), as part of the context where we conducted this study, future examinations may seek to understand the extent to which this may be explaining why some residents engage in acts of online vigilantism, such as engaging in the online shaming of COVID-19 policy violators. Finally, this exploratory study proposed and tested the combined framework of TPB and BJW in examining predictors of online vigilantism. While the analysis showed the utility of such theoretical fusion, more studies are needed to test the validity of framework we have proposed, as well as compare it with other theoretical frameworks and models that may help explain why individuals engage in online vigilantism. Specific acts of vigilantism online may also differ across situations—for example, online shaming through photos and videos are different from other actions, such as doxxing. Thus, our findings here may be limited to only a particular type of online vigilantism acts. Despite these limitations, we hope that our findings can contribute to a more nuanced and inclusive scholarship on online shaming and vigilantism, especially in the specific context of an unprecedented pandemic.

Acknowledgments

This work was supported by Ministry of Education – Singapore (RG150/18).

Disclosure Statement

No potential conflict of interest was reported by the author.

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Table 1.

Predicting Online Vigilantism

Variables B Wald p Exp (B) 95% C.I. for Exp (B)
Lower Upper
χ2 (11) = 422.94, p < .001
Age -.017 5.483 .019 .984 .970 .997
Education .131 2.558 .110 1.140 .971 1.339
Income -.040 .692 .405 .960 .873 1.056
Gender -.365 4.248 .039 .694 .491 .982
Attitude-Valence -.045 .102 .750 .956 .723 1.262
Attitude-Outcome Expectancy -.200 2.391 .122 .818 .635 1.055
Descriptive Norms .968 119.433 <.001 2.632 2.213 3.131
Injunctive Norms 1.009 46.050 <.001 2.742 2.049 3.670
Perceived Behavioral Control .183 .916 .339 1.201 .826 1.746
BJW-self -.629 9.412 .002 .533 .356 .797
BJW-others 1.048 30.630 <.001 2.853 1.968 4.135