Behaviour that occurs online is an important component of many people’s social interactions. It is, therefore, crucial that the detrimental impacts of cyberbullying and similar behaviour (i.e., online aversive behaviour) are addressed. To this end, I present research that progresses from an exploration of online social behaviour in general (Chapter 2) through to quantitative discounting studies that examine an avenue for behaviour change initiatives that improve the online social environment. In the exploratory phase (Chapter 2), I conducted a series of focus groups with young people between 12- and 21-years old on the broad topic of Social Networking Site use (SNS). Participants spoke about how they manage their use of SNS, which coalesced around several key themes. One of these ideas was the importance of showing and receiving support from their online social communities, especially in instances of adversity. An effective way to show support for another person online is to actively intervene when witnessing adverse (or aversive) behaviour directed toward that person. In Chapter 3, I explored a novel application of discounting methods to assess whether social outcomes related to online bystander (i.e., cyberbystander) intervention are discounted similarly to outcomes more common within the discounting literature. I used discounting methods in conjunction with the framework of the Bystander Intervention Model (BIM; Latané & Darley, 1970), reframing the latter to be congruent with the concepts of behaviour analysis. In Chapter 4, I tested the applicability of discounting methods to the decision-making of young adult cyberbystanders. As discounting studies using monetary outcomes have been well-established, I compared the probabilistic discounting of money to that of social outcomes related to cyberbystander behaviour. Having established that probability discounting can be applied to cyberbystander’s decision-making, in Chapter 5, I examined whether scenario severity, audience size, or locus of responsibility (i.e., whether responses related to participant’s own behaviour or their perception of how someone else would respond) impacted the willingness of young adults to intervene in online aversive behaviour. Intervention was marginally more likely when participants considered whether someone else would intervene (rather than themselves) and if the severity were high, but the larger audience size had a negligible effect. Chapter 6 contains a study designed to follow up on the promising findings regarding the impact that perceived scenario severity had on cyberbystander’s decisions to intervene themselves, particularly when compared to what participants considered the social norm to be (i.e., how they thought someone else would respond). The difference between the likelihood of intervention when participants responded for themselves versus what they considered normative was most evident when the scenario was moderate-to-high in severity. In all, my research supports the premise that discounting methods can be applied to cyberbystander decision-making and used to assess aspects of the BIM to identify avenues for cyberbystander behaviour change initiatives. Cyberbystanders’ actions can fundamentally change whether acts of aversive behaviour are reinforced (or punished), as well as mitigate the extent of the harm experienced by a target of online aversive behaviour.