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The digital bystander effect

The digital bystander effect, an extension of the traditional bystander effect, describes the tendency for individuals to avoid intervention in online harassment or cyberbullying. This phenomenon is amplified by factors such as online anonymity, diffusion of responsibility, and dispositional factors. As harmful content spreads rapidly across online platforms, bystanders are often passive, or contribute to the negativity (negative bystander).

Originally identified in 1968 by psychologists Bibb Latané and John Darley after the infamous Kitty Genovese case, the bystander effect has since been applied to digital environments, playing a significant role in incidents like cyberbullying, harassment, and the sharing of distressing content. Studies indicate that approximately 20-40% of youths report being victims of cyberbullying, with the highest rates of victimisation among 12- to 13-year-olds . Given the frequency and scale of these incidents, there is a growing need for targeted interventions in the digital space, including regulatory measures on the age at which teenagers can begin using social media, similar to Australia raising the minimum age to 16 years.

This article explores the digital bystander effect by examining its psychological and social background, real-life case studies, and interventions that aim to mitigate passive bystander behaviour. It also considers the role of technology companies in addressing the issue, through features like content moderation and educational campaigns, and highlights the importance of fostering empathy and responsibility in digital spaces.

Psychological Mechanisms

Diffusion of responsibility

The concept of diffusion of responsibility suggests that individuals are less likely to intervene when others are present, as the responsibility to act is perceived as being shared among the group. This effect is amplified online, where limited information and the absence of clear social roles further reduce a person’s sense of responsibility.

Brody and Vangelisti (2016) supported this idea, finding as individuals perceived more bystanders, they were less likely to intervene. The study also found that when bystanders were anonymous online, they were even less likely to provide help. While these results were correlational, they support the concept of diffusion of responsibility online.

Anonymity

Online platforms provide users with a degree of anonymity, which can contribute to a lack of intervention in instances of cyberbullying or online harassment, mainly due to the lack of physical presence, as users interact behind screens. The presence of other bystanders can increase the sense of anonymity, making individuals feel less accountable for intervening. Additionally, the vast amount of information shared online, coupled with the speed at which it spreads, can overwhelm individuals, contributing to a feeling of helplessness and discouraging intervention in anonymous digital environments.

Evaluation apprehension

Evaluation apprehension refers to the fear of being negatively judged by others, particularly in social settings. This concern about damage to one’s online reputation can deter individuals from intervening. A systematic review of digital bystander behaviour supported this finding fear of confrontation and fear of becoming a victim themselves were two major factors eliciting cyber bystander behaviour. The nature of online communication, which creates psychological distance between the perpetrator, victim, and bystander, further complicates this. This distance can make it more difficult for bystanders to empathise with the victim or recognise the severity of the situation.

Normative social influence

Normative social influence refers to conformity in order to be liked or accepted by others . This applies to cyberbullying as research indicates that cyber bystanders are significantly more likely to become primary aggressors, unlike bystanders in physical bullying situations . Additionally, Hinduja and Patchin (2013) found that 62% of students who reported that all or most of their friends had engaged in cyberbullying in the past six months also admitted to participating in cyberbullying in the previous 30 days . In contrast, only 4% of students whose friends had not engaged in cyberbullying reported similar behavior. The desire to fit in with a social group explains these results, particularly as long-term exposure to cyber aggression has been shown to lower empathic responses toward distressed individuals over time .

Dispositional factors

Empathy, extraversion, and self-efficacy are significant predictors of whether a bystander will actively intervene during cyberbullying. Further research has identified that higher levels of empathy and secure attachment are the major predictors in intervention for cyberbullying cases. However, these studies have conflicting findings for age and gender, as Freis et al., (2013) found no significant effects of age, gender or self esteem on supportive behaviour, whereas Herry et al., (2021) found female students and those in sixth grade were more likely to report intentions of intervention than their male or ninth grade counterparts. It is important to note that in both cases research is only correlational and based on self-reported data, limiting its internal validity.

Although there might be conflict over certain dispositional variables Jeyagobi et al., (2022) provides support with previous research, identifying empathy as a significant factor determining digital bystander behaviour, alongside lack of self-reliance and social self-efficacy, similar to Freis et al., (2013). This review also identified passive bystanders as motivated by concerns over potential negative consequences, such as threats to their safety, loss of friendships, or becoming a victim themselves.

Contextual factors

Bystanders are more likely to intervene if they feel a close connection to the victim, those with weaker relationships may lack the opportunity to seek clarification or understand the context of a situation. The common motivations for inaction include the desire to avoid drama, fear of confrontation, and a perception that intervening would be a waste of time. A systematic review of 27 studies found that fewer than half of individuals intervened in cases of cyberbullying, although this is still higher than the involvement rate for physical bullying, which stands at approximately 19%. Other factors contributing to bystander inaction include moral disengagement, victim-blaming, low empathy, and fear of becoming a victim themselves.

Theoretical Background

Latane and Darley (1968) diffusion of responsibility

Latane and Darley (1968) identified several key factors that influence whether individuals intervene in emergency situations:

1. Noticing the event
2. Interpreting it as an emergency
3. Assuming responsibility
4. Deciding how to help
5. Taking action

A related concept, pluralistic ignorance, occurs when individuals look to others for cues on how to respond, particularly in ambiguous situations. If others seem unconcerned, individuals may conclude that no action is needed. This dynamic is particularly prevalent in online environments, where the absence of visible emotional cues (such as facial expressions or tone of voice) can reinforce inaction, making it less likely for bystanders to intervene.

Piliavin et al (1969) Cost-reward model

The cost-reward model suggests that bystanders decision to intervene depends on the emotional arousal caused by the emergency and the cost reward analysis of taking action. People are more likely to help if:

• Arousal is strong (empathy or distress from witnessing an incident)
• Perceived cost of helping is low (minimal risk or effort)
• The perceived cost of not helping (guilt) outweighs the cost of the help

This model emphasises the role of individual calculations and decision-making, highlighting that intervention is not solely driven by group dynamics as proposed by Latane and Darley.

Tajfel and Turner (1979) social identity theory

Tajfel and Turners Social Identity Theory (1979) suggests that individuals derive a sense of belonging from their memberships in social groups, influencing their behaviours and attitudes toward others. For example, a bystander is more likely to ignore cyberbullying if the victim is seen as belonging to an out-group, as supported by Sjogren et al., (2021) who found friendship with a victim motivates the bystander to intervene, whereas friendship with a bully demotivates intervention. Similarly, Jeyagobi et al., (2022) found individuals only felt responsibility to intervene when they felt close to the victims, those with weaker relationships were less likely to intervene.

Zimbardo (1969) deindividuation theory

Zimbardos deindividuation theory (1970), derived following the famous Stanford prison experiment, stated that individuals in groups or anonymous settings may experience a reduction in self-awareness and personal accountability, leading to behaviours that are more impulsive than in individualised settings.

Online anonymity allows individuals to feel detached from the consequences of their actions, and in digital environments, users feel less accountable for their behaviour because they are physically removed from the situation, with an obscured identity. This sense of anonymity and the lack of immediate consequences can reduce the perceived responsibility to intervene in cyberbullying.

These dynamics are closely linked to moral disengagement strategies, where individuals rationalise or justify harmful actions to maintain their moral self-image. Common strategies include blaming others, displacing responsibility, or reinterpreting harmful actions as harmless banter. These mechanisms allow bystanders to participate in or ignore online abuse without feeling guilt, making it easier for them to disengage from the responsibility of intervention.

Key incidents

2017 sexual assault of 15 year old girl

In 2017, a 15 year old girl was sexually assaulted by a group of men, it was broadcasted on Facebook live with over 40 viewers, none of whom made a phone call to the police . A professor at Northwestern University's law school remarked that it isn't illegal to watch such a video, or not report it to the police, only downloading it would result in charges.

Suicide of Amanda Todd

Amanda Todd, a 15-year-old Canadian girl, died by suicide on October 10, 2012, after years of cyberbullying and harassment. At age 12, she was coerced into sharing an explicit image online, which was later circulated, leading to relentless bullying both online and offline. Weeks before her death, she posted a YouTube video using flashcards to share her struggles with mental health, bullying, and self-harm. Her story drew international attention to cyberbullying, online exploitation, and youth mental health. A Dutch man was later convicted for his role in her harassment. Todd's case inspired online anti-bullying advocacy worldwide.

Interventions

Younger people have expressed that they do not receive the necessary support from their environment and are unequipped to aid their peers to resolve cyber bullying experiences. However, research has also demonstrated that 76% of bystanders self-reported offering some form of support in a prior cyber bullying situation, with many participants offering more than just one form of support. Therefore, bystanders are willing to help, albeit without the proper resources.

Digital bystander intervention may include:

• Reporting abuse allowing administrators to initiate action
• Offering support via empathy, resources or encouragement
• Redirecting conversations in threads so misinformation can be prevented
• Promoting positive behaviour by encouraging and modelling respectful communication

M1: Instagram sensitive content warning

The role of technology companies

Technology companies, including Meta, Twitter, Snapchat, and Instagram, utilise algorithms designed to detect and flag harmful content, allowing platforms to remove it or issue warnings to users. Additionally, features such as reporting and blocking make it easier to limit the spread of harmful content.

Raising awareness and providing educational initiatives, such as online campaigns, can increase intervention rates by fostering discussions about the digital bystander effect. Programs which actively incorporate teachers and students are found to be the most effective . In-app notifications, such as sensitive content warnings (see image: M1), can also help minimise exposure to harmful or distressing material.

Summary

A recent meta analysis on cyber bystander behaviour found an interaction of multiple factors in digital bystander behaviour, however the Bystander Intervention Model by Latin and Darley was the most simple and useful. The main reasons identified in this review of 27 articles for not intervening included not thinking the event was severe enough, not thinking its their responsibility to intervene and not having the necessary skills, knowledge or self-efficacy to intervene.

This ties neatly into the importance for collaboration between researchers, educators, technology companies, and policymakers to create safer, more supportive online environments and encourage active digital bystander behaviour. This may involve strengthening regulations on content moderation and ensuring platforms have better algorithms to detect and combat abuse. Digital literacy programs in school during peak times of cyber bullying should be utilised to promote empathy and active intervention.