The literature shows that researchers used a wide variety of types of guilt manipulation. A common feature of these studies was that the subjects were not able to doubt their guilt. Additionally, these methods did not take into account the psychometric measurement of this emotion, as well as the possibility of simultaneously inducing other feelings, such as sadness or anger. In a carefully designed experiments, we found a method that is approachable to arrange, which additionally seems to be free from these methodological flaws. In our study participants were shown an arranged message suggesting that the experimenter’s work has been destroyed. In experiment 1 (N = 44), we showed that the method proposed by us significantly affects guilt. In experiment 2 (N = 89), we replicated our result, additionally demonstrating that our procedure significantly affected only the emotion of guilt (compared to other emotions) - which is a novelty. It also has been shown that complying with the request of the victim (conditional forgiveness) makes us feel less guilty, but it does not restore liking to this person - which was established by previous research. The discussion section summarizes the results, indicates their limitations, and proposes directions for future research.

Diffusion of responsibility is a well-known effect widely studied in a real-life setting. It can occur in a situation in which the more people observe a crisis event, the less likely it is that someone will react and provide real assistance. These days of a galloping digital revolution a question is to be raised as to whether the same effect can be observed in the online space of communication. In order to investigate this phenomenon we designed a study aimed at testing whether people exposed to a situation of cyberbullying will decide to take action against it depending on how many other Internet users are also aware of that crisis. Results obtained by us confirmed the existence of the diffusion of responsibility in the Internet similar to that observed in our daily lives. We also confirmed that a well-known influence technique “Even a penny will help” (in our study “every reaction will help”) can be effectively used to model behaviour online. In our times of digital revolution, those outcomes can be a step both toward understanding human behaviour in the online setting, showing us that it is not that different from the one presented in real live face-to-face communication and toward helping deal with antisocial behaviour people face online on a daily basis.