## 5 Discussion  
Participants' donations allowed us to quantify how they depict strangers in terms of reputation. When individuals have to decide how much of their endowment to give to someone else, the reputation of their partner matters. However, when no reputational information was provided by the system, people interacted more generously as Donors. Interestingly, participants donated more on average when their partners had positive reputations (3 out of 5). Without any additional information about their interactors, individuals seem to rely on that automated predisposition towards cooperation individuated by the social heuristics hypothesis' scholars [39] and that is particularly salient from early to mid-adolescence [41]. Since there were no clues about the partners' trustworthiness that could be used to outweigh this heuristic decision-making process, allocations were made more \"indiscriminately\". Instead, when indirect reciprocity mechanisms are in check, cooperation could be preferentially directed towards those individuals who the group identify as \"valuable\" members. Giving to an unknown individual (i.e., a stranger) the same amount of resources as to a well-rated person may not be a \"mismatch\" between humans' evolved psychology and the environment we lived in [42]. Indeed, being generous with unrated individuals could be a successful method for identifying other cooperative individuals and turning them into interaction partners for the future [43]. Overall, our paper contributes to a better understanding of users' behaviors towards online strangers. On the one hand, quantifying users' availability towards strangers may help to prevent the fraudulent exploitation of users [14; 15; 16; 17]. Indeed, since we know that \begin{table}
\begin{tabular}{l c c c} \hline \hline \multicolumn{4}{c}{**GLMM Best Model for Average Donation Dynamics**} \\ \hline  & **Akaike** & **F** & **Df-1(2)** \\ \hline Best Model & 13,745.669 & 154.387 *** & 1 (3357) \\ \hline \multicolumn{4}{c}{**Fixed effects**} \\ \hline
**Factor** & **F** & **Df-1(2)** & **Coefficient (\(\beta\))** & **Student \(t\)** \\ Receiver Reputation & 154.387 *** & 1 (3357) & 0.140 & 14.425 *** \\ \hline \hline \multicolumn{4}{l}{*** = \(p<0.001\).} \\ \end{tabular}
\end{table} 
Table 7: Generalized Linear Mixed Models 5. Average donation. Figure 3: Comparison between the average donation trend with respect to Receivers’ reputation scores (dots) and the amount offered without the reputation system (dashed line). people online tend to trust strangers as if they have a good reputation, new technological solutions and policies are needed to protect users from exploitation. On the other hand, our results could be adopted to ignite patients' self-disclosure in teletherapy settings [44; 45; 46]. Self-disclosure is a fundamental aspect of therapy success. The willingness of people to adopt prosocial behavior towards a stranger could be exploited, by appropriately modulating the participants' anonymity, to activate reciprocity dynamics within a therapeutic setting (e.g., an online group therapy) and thus achieve a higher level of self-disclosure. As for reputation effects, we observed how greatly people rely on reputation for their decision making. Reputation appeared to push individuals to neglect their personal experience (i.e., feedback) and individual preferences (i.e., acceptance) and to adhere to an emerging group standard. This tendency is interpretable within the Social Identity Model of Deindividation Effects [47; 48], which defines the condition needed for conformism to take place online [49]. In our work, we observed that donation, feedback and acceptance behaviors are all preferentially adjusted for well-rated interactors. Moreover, we observed how individuals were susceptible to reputation's influence even when reputation was a \"fake\" cue.