![Sections in the Persona Profile, Adapted from Jung et al. [9]](https://www.researchgate.net/profile/Joni-Salminen-2/publication/333741039/figure/tbl1/AS:769180001390592@1560398211118/Sections-in-the-Persona-Profile-Adapted-from-Jung-et-al-9_Q320.jpg)
Content uploaded by Joni Salminen
Author content
All content in this area was uploaded by Joni Salminen on Jun 13, 2019
Content may be subject to copyright.
The Eect of Smiling Pictures on Perceptions of Personas
Joni Salminen
Qatar Computing Research
Institute, HBKU; and Turku
School of Economics
Doha, Qatar
jsalminen@hbku.edu.qa
Soon-gyo Jung
Qatar Computing Research
Institute, Hamad Bin
Khalifa University
Doha, Qatar
sjung@hbku.edu.qa
João M. Santos
Instituto Universitário de
Lisboa (ISCTE-IUL)
Lisbon, Portugal
jmcsm@iscte.pt
Bernard J. Jansen
Qatar Computing Research
Institute, Hamad Bin
Khalifa University
Doha, Qatar
jjansen@acm.org
ABSTRACT
We analyze the eect of a smile in personas pictures on persona
perceptions, including credibility, likability, similarity, and
willingness to use. We conduct an online experiment with 2,400
participants using a 16-item survey and multiple persona prole
treatments of which half have a smiling photo and half do not.
We nd that persona proles with a smiling photo result in an
increase in perceived similarity with, likability of, and
willingness to use the personas. In contrast, a smile does not
increase the credibility of the personas. Our research has
implications for the design of persona proles and adds to
previous ndings of persona research that the picture choice
inuences individuals’ persona perceptions in profound ways.
CCS CONCEPTS
• CCS → Social and professional topics → User characteristics
KEYWORDS
Smile, Personas, Persona design, User study
ACM Reference format:
Joni Salminen, Soon-gyo Jung, João M. Santos and Bernard J. Jansen.
2019. e Eect of Smiling Pictures on Perceptions of Personas. In 27th
Conference on User Modeling, Adaptation and Personalization Adjunct
(UMAP’19 Adjunct), June 9–12, 2019, Larnaca, Cyprus, ACM, New York,
NY, USA, 5 pages. hps://doi.org/10.1145/3314183.3324973
1 Introduction
Persona creators are known to have design power when craing
persona proles, resulting in varied sense-making and possible
biases by the users of personas [7, 12, 23]. Personas provide a
shared mental model of the users’ needs and wants and
summarize data about users in an empathetic format that is more
memorable than numbers [5, 15]. One of the most prominent
sections of the persona prole is the picture, typically a portrait
photo. e picture choice has been shown to inuence the end
users’ perception of the persona, directing the end users’
thinking concerning the persona [16, 21]. For example, Salminen
et al. [23] found that using an African-American picture evokes
racially associated sense-making. In addition, there is a variety of
prior work showing the impact and information aspects of
pictures in system interfaces [10].
However, there is lile to no research on how to choose the
types of images used in persona proles. Even though there are
many possible areas to investigate in this regard, in this research
we are interested in the use of smiling people in pictures.
Specically, in this regard, we could locate no existing research
about the impact of smile on the user perceptions of personas. In
this regard, it is worthwhile to pursue a beer understanding of
individuals’ perceptions toward personas and what kind of
design choices drive these perceptions if personas are to be used
by decision makers. Such research can yield actionable insights
to aid persona designers in developing beer persona proles.
In the following section, we review the related literature.
After this, we explain the experimental setting, including the
creation of the treatments and data collection. This is followed
by an analysis of the results. We conclude by presenting
practical advice for persona creators along with interesting
questions for future research.
2 Related Work
Personas are a vehicle of communication about users within a
team, across departments, and with external stakeholders [15].
Thus, personas provide a shared mental model of the end users
and summarize data about users in an empathetic format that is
more memorable than numbers [20]. Often, personas are
communicated in the form of a story, e.g., “Mary is a 35-year-old
woman who likes…” A persona can be understood as a story that
conveys user experiences that the decision makers would not
necessarily know otherwise. Consider the difference between
creating a software product for the nameless and faceless target
group of 24-35-year-old women, or for “Anna, a stressed single
mum wanting to better manage her time”.
Social scientists have shown that a smile has a profound
eect on perceptions by others. Overall, a smile has been found
to reinforce perceived similarity and identication [6, 8, 26].
Wang et al. [26] observed that the intensity of smile aects
interpersonal perceptions, specically the perceptions of warmth
Permission to make digital or hard copies of all or part of this work for personal
or classroom use is granted without fee provided that copies are not made or
distributed for profit or commercial advantage and that copies bear this notice
and the full citation on the first page. Copyrights for components of this work
owned by others than the author(s) must be honored. Abstracting with credit is
permitted. To copy otherwise, or republish, to post on servers or to redistribute
to lists, requires prior specific permission and/or a fee. Request permissions from
Permissions@acm.org.
UMAP ’19 Adjunct, June 9–12, 2019, Larnaca, Cyprus.
© 2019 Copyright is held by the owner/author(s). Publication rights licensed to
ACM. ACM ISBN 978-1-4503-6711-0/19/06…$15.00
htt
p
s://doi.or
g
/10.1145/3314183.3324973
and competence. Hinsz and Tomhave [8] found that smiling has
a contagious eect, resulting in subjects echoing the positive
feeling, while Deutsch [6] found gender dierences in
perceptions of smiling and non-smiling individuals, so that
females are expected to smile more oen. Oa et al. [17] found
that smiling young people were considered as more extroverted
and ambitious than middle-aged and elderly smiling individuals.
In a similar vein, various studies in human-computer
interaction have explored the interaction of smiles and
technology. For example, Turner and Hunt [25] investigated
social network users’ assessment of other users’ personality
traits based on prole pictures and found that smiling had a
signicant impact on the personality assessments.
Despite the considerable interest in a smile in the context of
person perception, we could nd no existing work in the persona
domain on the impact of smiling pictures in personas, even
though the basis of personas is to present the persona as a real
person. Since personas are human-like user representations, they
are judged like individuals by other individuals, thus making
perceptual studies important in the persona domain.
Given that the persona’s facial picture impacts the way
personas are perceived by end users [21–23], understanding the
eect of a smile or absence of a smile has a direct impact on the
design and implementation of personas, along with their
potential use and eectiveness within organizations.
3 Research estions
Building on the ndings from previous research, we are
interested in the eect of using smiling images in persona
proles on persona perceptions. If the perception of a persona
can be inuenced by the choice of a smiling image, this has
direct implications for persona creation.
Our research question is: How does a smiling persona picture
aect persona perceptions?
Based on our research question, our hypotheses are:
H01: A smiling photo in a persona profile increases
perceived credibility
H02: A smiling photo in a persona profile increases
perceived likability
H03: A smiling photo in a persona profile increases
perceived similarity.
H04: A smiling photo in a persona profile increases the
perceived willingness to use.
We evaluate the impact of a smile in the persona prole on
four constructs: likability, credibility, similarity, and willingness
to use. ese constructs and their measurement items have been
validated in earlier work [24], and are dened as follows.
Credibility – Persona information is clearly presented to
the respondent; the persona seems authentic. Credibility is a
key concern of personas [4, 13].
Likability – The persona is liked by the respondent.
Likability is conceptually similar to attractiveness but a
more comprehensive construct [18].
Similarity – The respondent feels like the persona is like
him or her. Similarity to the personas is akin to the
identification of a common bond [11].
Willingness to use – The respondent would make use of
this persona in his or her work. Willingness to use is a
crucial perception, as it influences the adoption process of a
persona in practice [19].
Table 1 displays the measurement items for each construct.
Table 1: Variables and Items from Survey, Adapted from
Salminen et al. [24]
Construct
Measurement Items
Credibility
This persona seems like a real person.
The persona seems natural.
The persona seems to have a personality.
The picture of the persona looks
authentic.
Likability
I find this persona likable.
I could be friends with this persona.
This persona is interesting.
This persona feels like someone I could
spend time with.
Similarity
I like the same things as this persona.
This persona feels like me.
The persona and I have similar opinions.
I can relate to this persona.
Willingness to
use
I would like to know more about this
persona.
I could see myself making use of the
information about this persona in my work.
This persona would improve my ability to
make decisions about the customers it
describes.
I found this persona helpful for
understanding the people it describes
4 Methodology
In a between-subjects experimental design, we present crowd
workers with persona proles containing the person either
smiling or not smiling.
4.1 Smiling and Non-smiling Pictures for
Persona Profiles
We obtain 24 picture pairs (48 total photos) of a person smiling
and not smiling by using online stock photo banks and
supplementing by employing a professional photographer.
Figure 2 shows examples of the obtained photos pairs.
Aer collecting the photos, we created the pairs of persona
proles (see Figure 1) using the automatic persona generation
method by An et al. [2, 3]. e key aributes of the created
persona proles include age, gender, location, and topics of
interests [2].
Figure 1: Example Treatment (Mature Woman Smiling) and (Mature Woman Not Smiling)
Although there are dierent layouts for persona proles [14],
in this research, we adopt a typical layout and information
content as presented in [9], as this represents a common layout
for personas. Altogether, we created 48 dierent persona prole
pairs by varying age, gender, and race. Previous research on
smile and person perceptions has found that gender has a
mediating inuence on perceived aributes of males and females
[6]. Similarly, ethnicity of the persona has been found inuential
in previous persona research for end user perceptions [23]. us,
by variating these variables we can investigate if the observed
eects are consistent across genders, age groups, and ethnicities.
Figure 2: Example Smiling and Not Smiling Pictures: (a)
Asian Mature Male, (b) Black Young Male, and (c) White
Young Female
Apart from changing the picture, all other information (e.g.,
topics of interest, most viewed content, quotes) was kept
unchanged in the persona proles. Apart from changing the
picture according to the experimental variables, all other
information (e.g., topics of interest, most viewed content, quotes)
was kept unchanged. Table 2 denes the information elements of
the persona prole.
4.2 Survey Creation
We utilize the constructs and items from the Persona Perception
Scale [24]. From this instrument, we chose the four constructs as
outlined above with their associated measurement items (Table
1). We created a questionnaire using the items outlined in [24] as
statements shown to respondents. For each statement, we
utilized a seven-point Likert scale with the options ranging from
(1) Strongly disagree to (7) Strongly agree.
Table 2: Sections in the Persona Profile, Adapted from
Jung et al. [9]
Section
Definition
Name Persona’s name.
Picture Persona’s picture is one of the
treatments
Demographic information Persona’s age, gender, country
Industry Persona’s job
Education Level Persona’s education level
Marital Status Persona’s marital status
Interest Persona’s topics of interest.
Most Viewed Contents Persona’s content interacted with.
Quotes Persona’s quotes
Audience Size Size of the user segment
4.3 Data Collection
We recruited 50 respondents for each persona prole for 2,400
respondents in total. We used FigureEight, the crowdsourcing
platform. To control the answer quality, we undertook measures
outlined in [1]. First, we manually selected the participant
channels, specically FigureEight Elite, Clickworker, and
ClixSense in order to focus on high-quality networks. Second,
we set the participant quality level to Level 3 (Highest quality).
ird, we set a minimum time of 120 seconds for the experiment;
any answer taking less time than this would be disqualied.
Fourth, we ran the experiments in parallel to mitigate the
possibility of the same participants enrolling in many surveys.
e sampling was narrowed to four English-speaking countries:
United States (US), United Kingdom, Canada, and Australia. e
reward for lling in the survey was 0.30 US dollars.
e respondents were asked to reveal their thoughts about
the persona they were shown. We dened the persona as
follows: A persona is a ctitious person describing a bigger
customer segment. It can be understood as a typical or average
customer. We instructed the respondents to review the persona
information carefully. en, we asked the participants to answer
the statements about the persona. At any time while responding
to the survey, they could review the persona prole.
5 Results
We now return to our research question is (How does a smiling
persona picture aect the user’s perception of the persona?) and
the associated research hypotheses that a smiling photo in a
persona prole increases perceived credibility (H01), likability
(H02), similarity (H03), and willingness to use (H04).
A multivariate analysis of variance (AMNOVA was
conducted to determine the effects of smiling on perceived
credibility (H01), likability (H02), similarity (H03), and
willingness to use (H04) at the p<0.05 level of significance in
response to whether the person in the picture of the persona
profile was smiling or not smiling.
No significant differences were found regarding perceived
credibility (F(1, 2398) = 0.560, p = 0.454) on pictures with a
smiling persona (M = 4.763, SD = 1.168) and without a smiling
persona (M = 4.727, SD = 1.149).
Significant dierences were found regarding perceived
likability at the p < 0.001 level (F(1, 2398) = 7.091, p = 0.008), with
pictures with a smiling persona showing higher scores for likability
(M = 4.692, SD = 1.198) than pictures without a smiling persona
(M = 4.563, SD = 1.178).
Signicant differences were found regarding perceived
similarity at the p < 0.001 level (F(1, 2398) = 8.307, p = 0.004),
with pictures with a smiling persona showing higher scores for
similarity (M = 4.493, SD = 1.215) than pictures without a smiling
persona (M = 4.353, SD = 1.171).
Finally, signicant differences were also found regarding
willingness to use at the p < 0.05 level (F(1, 2398) = 5.179, p =
0.023), with pictures with a smiling persona exhibiting higher
scores for willingness to use (M = 4.620, SD = 1.125) than pictures
without a smiling persona (M = 4.518, SD = 1.067). Means and
standard deviations are presented in Table 3.
We also conducted correlation analyses, as shown in Table 4.
Factor analyses for the scale validation have been conducted in
previous work [24].
A significant and positive association was found between
Liking and Similarity (r(2398) = 0.647, p < 0.001), between Liking
and Willingness to Use (r(2398) = 0.644, p < 0.001), and also
between Liking and Credibility (r(2398) = 0.647, p < 0.001).
Furthermore, significant and positive associations were also
found between Similarity and Willingness to Use (r(2398) =
0.599, p < 0.001) and between Similarity and Credibility (r(2398)
= 0.505, p < 0.001). Finally, Willingness to Use was found to have
a significant and positive association with Credibility (r(2398) =
0.612, p < 0.001).
Table 3: Mean and Standard Deviations for Tested
Constructs. Gender, Age, or Ethnicity Did Not Have
Significant Interaction Effects.
Constructs Average Rating (Smiling
& Non-smiling)
Standard Deviation
(Smiling & Non-smiling)
Credibility 4.763
4.727
1.168
1.149
Likability 4.692
4.563
1.198
1.178
Similarity 4.493
4.353
1.215
1.171
Willingness
to use
4.620
4.518
1.125
1.067
(Bold denotes significant difference at p value presented in text.)
Table 4: Correlations Table for Liking, Similarity, and
Credibility.
Credibility Liking Similarity Willingness
to Use
Credibility 1 0.647 *** 0.505 *** 0.612 ***
Liking 1 0.647 *** 0.644 ***
Similarity 1 0.599 ***
Willingness
to Use
1
Note: *** p < 0.001; ** p < 0.01; * p < 0.05
6 Discussion and Implications
A summary of hypotheses testing is presented in Table 5. From
these results, findings are that a smile in the persona picture
increases likability of and the similarity with the persona, as
perceived by the individual exposed to the persona. Moreover,
the willingness to use a persona is increased by showing smiling
pictures. is encourages persona creators to use pictures with
smiling people, as smile results in several positive perceptions
from individuals exposed to personas. is in line with ndings
of the smile perception literature [8, 26] suggesting personas are
seen as people-like to those viewing them.
e lack of support for H01 can be explained by the ndings
of Wang et al. [26] that suggest a tradeo between likability and
credibility. In their context, a smile increased the likability of a
marketer, however, reducing the perception of competence.
us, a smile can contribute to the impression of “fakeness”, at
least among some participants. is eect should be explored
further in subsequent studies by varying the intensity of smile in
the tested persona pictures. Future studies should also explore
the interaction eects between constructs investigated here, e.g.,
the relationship between positive perceptions (likability,
similarity) on willingness to use.
Concerning the limitations, our sample was restricted to four
English-speaking countries. It remains a question for future
research to validate the findings in other cultural contexts and
regions of the world, where perceptions toward others, in
general, may differ. Moreover, experimental conditions, such as
the quality of photos, lighting, and backgrounds could be tested
in future research, as these might have confounding effects.
Future research may also examine how images interact with
other informational elements of the persona profile (i.e., text,
numbers) to form the overall persona perception.
Table 5: Results for Hypothesis Testing – (✓) Indicates
Confirmed, (✕) Not Confirmed
Hypothesis
Result
Conclusion
H01: A smiling photo in
a persona profile
increases perceived
credibility
✕ There can be a tradeoff
between positive affections
and credibility (i.e., sense of
“fakeness”).
H02: A smiling photo in
a persona profile
increases perceived
likability
✓ Individuals are more likely
to feel positive affections
toward a smiling persona.
H03: A smiling photo in
a persona profile
increases perceived
similarity.
✓ Individuals identify more
easily with smiling
personas.
H04: A smiling photo in
a persona profile
increases the perceived
willingness to use
✓ Individuals are keener to
learn more about the
persona they like.
As practical advice for persona creators, smiles in persona
pictures seem to play a signicant role in perceptions by
individuals, so it is probably best to use pictures of people
smiling, as smiling pictures increase perceived likeability,
similarity, and willingness to use. Naturally, this would be
moderated by the case, as there may be contexts and persona use
cases (i.e., funerals, extremely professional profiles, etc.) where a
smile is not appropriate. In general, though, including a smile in
a persona profile picture can be recommended.
7 Conclusion
In general, a smile elicits a positive emotional response to
personas, especially with likeability, similarity, and willingness
to use. erefore, as a general guideline, it is recommended to
use photos of smiling people when designing persona proles.
REFERENCES
[1] Alonso, O. 2015. Practical Lessons for Gathering Quality Labels at Scale.
Proceedings of the 38th International ACM SIGIR Conference on Research and
Development in Information Retrieval (New York, NY, USA, 2015), 1089–
1092.
[2] An, J. et al. 2018. Customer segmentation using online platforms: isolating
behavioral and demographic segments for persona creation via aggregated
user data. Social Network Analysis and Mining. 8, 1 (2018).
DOI:https://doi.org/10.1007/s13278-018-0531-0.
[3] An, J. et al. 2018. Imaginary People Representing Real Numbers:
Generating Personas from Online Social Media Data. ACM Transactions on
the Web (TWEB). 12, 3 (2018).
[4] Chapman, C.N. and Milham, R.P. 2006. The Personas’ New Clothes:
Methodological and Practical Arguments against a Popular Method.
Proceedings of the Human Factors and Ergonomics Society Annual Meeting.
50, 5 (Oct. 2006), 634–636.
DOI:https://doi.org/10.1177/154193120605000503.
[5] Cooper, A. 1999. The Inmates Are Running the Asylum: Why High Tech
Products Drive Us Crazy and How to Restore the Sanity. Sams - Pearson
Education.
[6] Deutsch, F.M. 1990. Status, sex, and smiling: The effect of role on smiling
in men and women. Personality and Social Psychology Bulletin. 16, 3 (1990),
531–540.
[7] Hill, C.G. et al. 2017. Gender-Inclusiveness Personas vs. Stereotyping: Can
We Have it Both Ways? Proceedings of the 2017 CHI Conference (2017),
6658–6671.
[8] Hinsz, V.B. and Tomhave, J.A. 1991. Smile and (Half) the World Smiles
with You, Frown and You Frown Alone. Personality and Social Psychology
Bulletin. 17, 5 (Oct. 1991), 586–592.
DOI:https://doi.org/10.1177/0146167291175014.
[9] Jung, S. et al. 2018. Automatic Persona Generation (APG): A Rationale and
Demonstration. Proceedings of the 2018 Conference on Human Information
Interaction&Retrieval (2018), 321–324.
[10] Kim, Y. and Kim, J.H. 2018. Using computer vision techniques on
Instagram to link users’ personalities and genders to the features of their
photos: An exploratory study. Information Processing & Management. 54, 6
(Nov. 2018), 1101–1114. DOI:https://doi.org/10.1016/j.ipm.2018.07.005.
[11] Liviatan, I. et al. 2008. Interpersonal similarity as a social distance
dimension: Implications for perception of others’ actions. Journal of
experimental social psychology. 44, 5 (2008), 1256–1269.
[12] Marsden, N. and Haag, M. 2016. Stereotypes and Politics: Reflections on
Personas. Proceedings of the 2016 CHI Conference on Human Factors in
Computing Systems (New York, NY, USA, 2016), 4017–4031.
[13] Matthews, T. et al. 2012. How Do Designers and User Experience
Professionals Actually Perceive and Use Personas? Proceedings of the
SIGCHI Conference on Human Factors in Computing Systems (New York,
NY, USA, 2012), 1219–1228.
[14] Nielsen, L. et al. 2015. A Template for Design Personas: Analysis of 47
Persona Descriptions from Danish Industries and Organizations. Int. J.
Sociotechnology Knowl. Dev. 7, 1 (Jan. 2015), 45–61.
DOI:https://doi.org/10.4018/ijskd.2015010104.
[15] Nielsen, L. 2019. Personas - User Focused Design. Springer.
[16] Nielsen, L. et al. 2017. Who Are Your Users?: Comparing Media
Professionals’ Preconception of Users to Data-driven Personas. Proceedings
of the 29th Australian Conference on Computer-Human Interaction (New
York, NY, USA, 2017), 602–606.
[17] Otta, E. et al. 1996. Reading a Smiling Face: Messages Conveyed by Various
Forms of Smiling. Perceptual and Motor Skills. 82, 3_suppl (Jun. 1996),
1111–1121. DOI:https://doi.org/10.2466/pms.1996.82.3c.1111.
[18] Reysen, S. 2005. Construction of a new scale: The Reysen Likability Scale.
Social Behavior and Personality. 33, 2 (Jan. 2005), 201–208.
DOI:https://doi.org/10.2224/sbp.2005.33.2.201.
[19] Rönkkö, K. et al. 2004. Personas is Not Applicable: Local Remedies
Interpreted in a Wider Context. Proceedings of the Eighth Conference on
Participatory Design: Artful Integration: Interweaving Media, Materials and
Practices - Volume 1 (New York, NY, USA, 2004), 112–120.
[20] Salminen, J. et al. 2018. Are personas done? Evaluating their usefulness in
the age of digital analytics. Persona Studies. 4, 2 (Nov. 2018), 47–65.
DOI:https://doi.org/10.21153/psj2018vol4no2art737.
[21] Salminen, J. et al. 2019. Confusion and information triggered by photos in
persona profiles. International Journal of Human-Computer Studies. 129,
(Sep. 2019), 1–14. DOI:https://doi.org/10.1016/j.ijhcs.2019.03.005.
[22] Salminen, J. et al. 2019. Design Issues in Automatically Generated Persona
Profiles: A Qualitative Analysis from 38 Think-Aloud Transcripts.
Proceedings of the ACM SIGIR Conference on Human Information Interaction
and Retrieval (CHIIR) (Glasgow, UK, Mar. 2019).
[23] Salminen, J. et al. 2018. “Is More Better?”: Impact of Multiple Photos on
Perception of Persona Profiles. Proceedings of ACM CHI Conference on
Human Factors in Computing Systems (CHI2018) (Montréal, Canada, Apr.
2018).
[24] Salminen, J. et al. 2018. Persona Perception Scale: Developing and
Validating an Instrument for Human-Like Representations of Data. CHI’18
Extended Abstracts: CHI Conference on Human Factors in Computing
Systems Extended Abstracts Proceedings (Montréal, Canada, 2018).
[25] Turner, M. and Hunt, N. 2014. What Does Your Profile Picture Say About
You? The Accuracy of Thin-Slice Personality Judgments from Social
Networking Sites Made at Zero-Acquaintance. Social Computing and Social
Media (2014), 506–516.
[26] Wang, Z. et al. 2017. Smile Big or Not? Effects of Smile Intensity on
Perceptions of Warmth and Competence. Journal of Consumer Research. 43,
5 (Feb. 2017), 787–805. DOI:https://doi.org/10.1093/jcr/ucw062.
