## 5 Discussions  
The four research questions in this paper can be discussed by combining the above results of the surveys and experiments. Overall, for RQ1, RQ2, and RQ3, the type of feedback and the type of previous emotions affect the type of user emotions when users encounter interaction errors in HRI, but the type of contexts, CPIR and CAIR, do not. Specifically, whether users actively interact with robots or not does not affect their emotions when encountering interaction errors, and users rarely feel fear. When previous emotions show one type of emotion, this emotion also has the largest proportion in user emotions after encountering interaction errors. For example, when the previous emotion was happiness, the user's emotion tends to be happiness. Hence, it is better to design robot expressions that can make users feel happier to reduce the possibility of negative emotions and help them cope when encountering interaction errors. Since the emotional intensity perceived by users does not show an impact on user emotions, the designed robot's expressions of happiness should be recognized by users; however, the corresponding intensity is unimportant in handling interaction errors. Furthermore, regarding the feedback mentioned in RQ2, compared with CF, IF tends to evoke happiness and surprise according to the results of [PERSON]'s exact test. As shown in Tables 4 and 7, in the case of IF, the corresponding magnitude of the effect size decreases with the frequency of interaction errors, while it increases in the case of CF. Considering the uncontrollability of previous emotions, it is better to reduce the corresponding magnitude of the effect on user emotions in real HRI. Hence, if we hope user emotions will be in a more positive state when users encounter interaction errors, an irrelevant answer to the user is a better choice when handling interaction errors. Further, the overall magnitude of the effect size of feedback on user emotions reduces with the times of interaction errors, as shown in Table 5. This trend is also evident in the CAIR and the CPIR, respectively, and the decreasing amplitude of effect size in the CAIR is faster than that in the CPIR, as shown in Table 6. This indicates that, although the CAIR and the CPIR do not affect user emotions, different feedback from robots shows different effects on users in the cases of the CAIR and the CPIR. Significant differences were only found in the first interaction error in the CAIR. This means that the impact of the different feedback, IF and CF, is manifested in the CAIR. Combined with Figure 6, IF is better than CF in making users express fewer negative emotions in the CAIR. As mentioned above, if interaction errors occur when users operate robots actively, an irrelevant answer given to users may be better for their emotions, even though the irrelevant answer is a social norm violation of interaction. The type of previous emotions and the type of feedback are influencing factors on user emotions in this case. But when the interaction begins with the robot, expressions, including social norm violationsand technical failure from the robot, given to users do not affect their emotions, and the type of previous emotions is the influencing factor. For RQ4, there are no interaction effects between the three factors. This means that the selection of contexts, the expression of feedback, and the regulation of previous emotions can be considered, respectively. Through the appropriate design of the factors, users' negative emotions toward interaction errors can be reduced. The intensity of user emotions is not affected by contexts or feedback. With increasing frequency of repeated interaction errors, the general intensity of anger increases. Hence, it is necessary to deal with interaction errors as soon as they are found to reduce the accumulation of anger. In addition, the effects of gender were also considered. In the experiments, a total of 34 males (M = 22.56, SD = 3.34) and 28 females (M = 22.44, SD = 2.26) were recruited.