Projective tests are personality tests that reveal individuals' emotions (e.g., Rorschach inkblot test). Unlike direct question-based tests, projective tests rely on ambiguous stimuli to evoke responses from individuals. In this paper we develop one such test, designed to be delivered automatically, anonymously and to a large community through public displays. Our work makes a number of contributions. First, we develop and validate in controlled conditions a quantitative projective test that can reveal emotions. Second, we demonstrate that this test can be deployed on a large scale longitudinally: we present a fourweek deployment in our university's public spaces where 1431 tests were completed anonymously by passers-by. Third, our results reveal strong diurnal rhythms of emotion consistent with results we obtained independently using the Day Reconstruction Method (DRM), literature on affect, well-being, and our understanding of our university's daily routine.

Given the proliferation of devices like infusion pumps in hospitals, number entry and in particular number entry error is an emerging important concern in HCI. There are clearly design features that could greatly improve accuracy in entering numbers but the context of the task could also play an important role. In particular, the emotional state of a person is known to strongly influence their response to a difficult situation and hence the errors that they make. In this paper, we consider the impact of the emotional state of the user on the accuracy with which people enter numbers. Our experiment shows that participants who are in a more positive emotional state are more accurate. The effect is small but could be very important when considering the potentially highly-charged emotional contexts where many healthcare devices are used.

It is becoming increasingly easy for researchers to develop context-aware applications for smartphones. A perennial challenge, however, is to convince a large number of people to install them and donate contextual data for scientific purposes. Our empirical study seeks to address this challenge by investigating how people's perception and attitude affect their willingness to donate context data to researchers and quantifies the effects of social signals on donation action-taking. Our findings indicate that the perceived need for donation and perceived organization reputation are key determinants in deciding whether to donate: people with altruistic personality do not necessarily donate if they cannot see the need to take an action. Furthermore, we provide evidence that even if people indicate a willingness to donate, they are hesitant to take action towards donating data unless catalysts like social signals (hints about the actions of others) are present. RESEARCH HIGHLIGHTS • Social signal affects people's actual human-computer interaction data donation behavior. • Participants who saw social signal were five times more likely to become donors • Perceived organization reputation and need to donate are key determinants.

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