Does a Smile Matter if the Person Is Not Real?: The Effect of a Smile and Stock Photos on Persona Perceptions

Abstract

We analyze the effect of using smiling/non-smiling and stock photo/non-stock photo pictures in persona profiles on four key persona perceptions, including credibility, likability, similarity, and willingness to use. For this, we collect data from an experiment with 2,400 participants using a 16-item survey instrument and multiple persona profile treatments of which half have a smiling photo/stock photo and half do not. The results from structural equation modeling, supplemented by a qualitative analysis, show that a smile enhances the perceived similarity with the persona, similar personas are more liked, and that likability increases the willingness to use a persona. In contrast, the use of stock photos decreases the perceived similarity with the persona as well as persona credibility, both of which are significant predictors to a willingness to use a persona. These professionally crafted stock-photos seem to diminish the sense of identification with the persona. The above effects are consistent across the tested ages, genders, and races of the persona picture, although the effect sizes tend to be small. The results suggest that persona creators should use smiling pictures of real people to evoke positive perceptions toward the personas. In addition to presenting quantitative evidence on the predictors of willingness to use a persona, our research has implications for the design of persona profiles, showing that the picture choice influences individuals' persona perceptions even when the other persona information is identical.

Using artificially generated pictures in customer-facing systems: an evaluation study with data-driven personas

“…Regarding the female persona with an artificial picture being perceived as more authentic, we surmise that there might be a 'stock photo' effect involved, rather than a gender effect. This proposition is backed up by previous findings of stock photos being perceived differently by individuals than non-stock photos (Salminen et al 2019f). Visually, to the respondents, the real photo chosen for the female persona appears different from the one chosen for the male persona (see Figure 4).…”

“…This approach seems intuitively compatible with personas, as researchers have reported several attitudinal perceptions concerning personas (Salminen et al 2019c). These are captured in the PPS survey instrument (Salminen et al 2018c;Salminen et al 2019f;Salminen et al 2019g) that includes eight constructs and twenty-eight items to measure user perceptions of personas. We deploy this instrument in this research, as it covers essential user perceptions in the persona context.…”

“…The perceptions are measured using the PPS (Salminen et al 2018c), a survey instrument measuring what individuals think about specific personas (see Table 3). The PPS has previously deployed in several persona experiments (see [Salminen et al 2019f;Salminen et al 2019g]). Note that the authenticity construct is similar to constructs in earlier artificial image evaluationspecifically to realism (Zhou et al 2019b) and naturalness (Iizuka, Simo-Serra, and Ishikawa 2017).…”

Data-Assisted Persona Construction Using Social Media Data

“…Studies show that, similar to designer bias, users and designers are affected by visual properties. To keep this effect from happening, pictures (stock, generated or otherwise, e.g., sketched) may be refrained from being used so that the acceptance of the persona by the users will not be affected by the likeability of the persona picture [36].…”

Does Your Smile Mean That You’re Happy? – a Multi-Channel Analysis of Emotional Reactions

“…In the latter, the major focus lays on the impact of emotional drivers on individual adoption decisions, whereby emotions are predominantly measured by means of self-reports of survey participants (e.g., [18]). In contrast, in the discipline of Human-Computer Interaction, facial expressions in order to assess emotional responses to computer-induced stimuli, have been analyzed by using observational (e.g., FACS),physiological methods (e.g., electromyography (EMG) [15], as well as using questionnaires [19]). The combination of both focuses (the HCI and the IS adoptionrelated), results in the following objective: The impacts' comparison of facial emotional reactions to computerinduced stimuli on self-reported perceptive evaluations towards the respective stimulus and system.…”