1 1 Comparing a standardized to a product-specific emoji list for evaluating food products by children 2 Joachim J. Schouteten1*, Jan Verwaeren2, Xavier Gellynck1, Valérie L. Almli3
3 1 Department of Agricultural Economics, Ghent University, Coupure links 653, 9000 Gent, 4 Belgium
5 2 Department of Data analysis and mathematical modeling, Ghent University, Coupure links 6 653, 9000 Gent, Belgium
7 3 Nofima AS, P.O. Box 210, 1431 Ås, Norway
8 * Author to whom correspondence should be addressed; E-Mail:
10 Tel.: +32-92-645-930; Fax: +32-92-646-246.
11
12 Abstract
13 There is a growing interest in the emotional associations of children to food products in order to better 14 understand their preferences. Recently, emoji were suggested as a novel way to assess these 15 emotional associations. In this study, 172 children aged 8-11 years evaluated the emotional profile of 16 five biscuits in a check-all-that-apply task, where half of the subjects (n=87) evaluated the applicability 17 of 38 emoji obtained from a standardized emoji list, while the other half (n=85) worked with 20 emoji 18 from a product-specific emoji list. A similar average number of emoji were used by the participants for 19 the emotional profiling of the samples in both approaches. Results showed that the product-specific 20 emoji list was better able to discriminate between product samples compared to the standardized 21 emoji list. Several emoji were even discriminating between similarly liked samples when using a 22 product-specific emoji list, while only one emoji was able to discriminate between equally-liked 23 samples when using a standardized emoji list. Both approaches produced similar emotional spaces and 24 product configurations, although one needs to consider that the first dimension of the correspondence 25 analysis for the product-specific emoji list explained over 90% of the total variance against 60% for the 26 standardized list. While more research is recommended, this study indicates that a product-specific 27 emoji list could facilitate the emotional product discrimination by children.
28
29 Keywords
30 Child; Biscuit; Emoji; Check-all-that-apply (CATA); Hedonic 31 Acknowledgments
32 J.J. Schouteten wants to acknowledge FWO (Research Foundation – Flanders, grant FWO V416118N) 33 enabling the cooperation with Nofima for this study.
34 3
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35 Introduction
36 Sensory and consumer research has a growing interest in the measurement of emotions in order to 37 have a broader perspective on consumer’s food experience (Cardello, et al., 2012; Meiselman, 2015;
38 Thomson, Crocker, & Marketo, 2010). These measurements might discriminate between food products 39 when the sensory acceptability is similar (King & Meiselman, 2010; Ng, Chaya, & Hort, 2013;
40 Schouteten, et al., 2015b; Spinelli, Masi, Zoboli, Prescott, & Monteleone, 2015). Moreover, research 41 has suggested that the inclusion of emotional conceptualizations helps to better predict actual food 42 choice in blind and informed evaluation conditions (Dalenberg, et al., 2014; Gutjar, et al., 2015).
43 Self-reported measurements have been primarily applied to study food-evoked emotions using Check- 44 All-That-Apply (CATA)-based questionnaires (Lagast, Gellynck, Schouteten, De Herdt, & De Steur, 45 2017). These word-based questionnaires either work with a standardized term list or use a product- 46 specific term list (Schouteten, et al., 2015b). The EsSense Profile™ (King & Meiselman, 2010), 47 containing a list of 39 terms to measure consumers’ emotional responses to food products, is currently 48 the mostly used standardized list (Lagast, et al., 2017). Although it has been originally developed on 49 snack products (e.g. chocolate, crackers, pizza, ice cream), it has been applied to a variety of food 50 products during the last couple of years such as blackcurrant squashes (Ng, et al., 2013), kiwifruit 51 (Jaeger, Cardello, & Schutz, 2013), coffee (Bhumiratana, Adhikari, & Chambers Iv, 2014), breakfast 52 drinks (Gutjar, et al., 2015) and green tea beverages (Pramudya & Seo, 2017). Product-specific lists on 53 the other hand, are consumer-defined lists obtained though first selecting emotional terms during a 54 pretest (Ng, et al., 2013). These product-specific, consumer-defined lists have been applied to a wide 55 range of food products such as chocolate (Thomson, et al., 2010), black-currant squashes (Ng, et al., 56 2013), (Bhumiratana, et al., 2014), orange juice (Thomson & Crocker, 2014), cheese (Schouteten, et 57 al., 2015a) and burgers (Schouteten, et al., 2016).
58 However, several points of concerns have been raised concerning the ecological validity of using word- 59 based questionnaires. First, prior research pointed out that although most participants found it 60 intuitive and easy to associate words with food products, some participants found it rather a strange 61 task to perform(Jaeger, et al., 2013). Moreover, some participants are not aware of certain emotions 62 and do not fully comprehend the meaning of the listed emotional terms (Jaeger, et al., 2013; Köster &
63 Mojet, 2015). Consumers also seldom use words to express their emotions of food products (Köster &
64 Mojet, 2015). Therefore, recently emoji have been introduced as an alternative way to assess food- 65 elicited emotions by consumers (Jaeger, Vidal, Kam, & Ares, 2017). Moreover, Swaney-Stueve, Jepsen, 66 and Deubler (2018) showed that emoji can be applied as an alternative form of a facial scale to assess 67 children’s liking of food products.
68 Given that emoji are widely used nowadays on a wide variety of mobile devices and are even used in 69 popular culture (e.g. The Emoji Movie, Sony Pictures Animation), the use of emoji also provides 70 opportunities for research with children, whom often are accustomed to express their feelings with 71 these icons in real-life communication. Gallo, Swaney‐Stueve, and Chambers (2017b) examined which 72 emoji best expressed how they felt in response to self‐selected favorite, least favorite, and “just okay”
73 foods before, during, and after recalled consumption occasions. Moreover, children evaluated the 74 applicability of several emoji on food product packages and food products. Based upon these data and 75 focus group discussions, Gallo, et al. (2017b) distilled a list of 38 emoji which were considered 76 appropriate for food evaluations by children. In a follow-up study, Gallo, Swaney‐Stueve, and 77 Chambers (2017a) compared the use of emoji by children to evaluate food images versus actual tasting 78 of food products. They found that tasting the foods resulted in increased use of positive emoji and 79 decreased use of negative emoji. Schouteten, Verwaeren, Lagast, Gellynck, and De Steur (2018) 80 showed that emoji could be applied to obtain discriminatory emotional profiles between similar 61
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3 81 samples within a product category (namely, speculoos biscuits) when working with a children 82 population. Moreover, they found that including emoji measurements help to better predict actual 83 food choice of the children compared to the sole inclusion of overall liking.
84 The growing interest in the use of emoji of food products bears the questions whether a standardized 85 list or a product-specific list should be preferred when working with children. A standardized list has 86 the advantage that it is cheaper to use and saves time, but normally contains many items so that no 87 potentially relevant items may be missed. Jaeger, et al. (2013) stipulated that standardized verbal lists 88 could generate a lower quality of data compared to product-specific lists, due to boredom and fatigue 89 of adult respondents. Given the lower attention span of children and need for age-appropriate 90 methods to examine children’s food preferences (Laureati, Pagliarini, Toschi, & Monteleone, 2015), 91 the goal of this study is to compare the performance of a standardized emoji list with a product-specific 92 emoji list using a children population.
93
94 2. Materials and methods 95 2.1. Experimental design
96 This study opted to work with a between-subjects design. The first group of children evaluated their 97 emotional response using a standardized list of 38 emoji based upon research from Gallo, et al.
98 (2017b). A second group of children from the same school used a product-specific emoji lexicon (20 99 emoji) which was established after a pretest with prior research. This pretest was a two-step procedure 100 in which children first indicated the applicability of emoji for a range of biscuits and thereafter 101 researchers made the final selection (see 2.4.). For both groups, the CATA approach was used whereby 102 children were asked to check all the emoji they found applicable to describe how they felt after 103 consuming a particular sample. Children were assigned to one of the two groups based upon their 104 school class, while school classes were randomly assigned to each condition.
105 2.2. Participants
106 Children from the 4th, 5th and 6th year (8-11 years old) of an elementary school located in Belgium 107 were recruited for this test. A signed parental informed consent was necessary to be eligible to 108 participate in this study and the child had the opportunity to withdraw at any time of the study.
109 Moreover, only children who did not have any allergies to the ingredients of speculoos (wheat, soy 110 and gluten) were considered suitable as participants. Testing took place in the refectory of the school, 111 with one class at the time.
112 In total, 87 children fully completed the questionnaire with the standardized emoji lexicon and 85 113 children fully filled in the questionnaire containing the product-specific emoji list. Socio-demographic 114 variables and information about the internet usage, number of mobile devices owned and emoji usage 115 of each population sample are listed in Table 1. Statistical analyses showed no significant differences 116 between the two groups for any socio-demographic or behavioral characteristic.
117 Insert Table 1 around here 118 2.3. Product samples
119 The focal product of this study were speculoos biscuits, a traditional biscuit in Belgium prepared with 120 several spices including cinnamon. Five commercially available samples were selected based upon 121 prior research to represent the range of sensory variability in the Belgian market. While speculoos 122 biscuits are traditionally prepared with wheat flour, the last years speculoos came available made with 121
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123 whole wheat or multigrain wheat as response to the request for more healthy food products. The 124 researchers selected three samples of speculoos biscuits made with wheat (W1, W2 and W3), one 125 sample made with whole wheat (WW) and a multigrain sample (M) containing wheat, rye, spelled, oats 126 and barley. Samples were from the same batch and had a similar shelf-life to limit potential product 127 differences between the participants. All samples were bought in local supermarkets.
128 The samples were served in odor-free transparent plastic containers (coded with 3-digit random 129 numbers) at room temperature (21 °C ± 1 °C) following a design balanced for presentation order and 130 carry-over effects (Williams Latin Square design) (MacFie, Bratchell, Greenhoff, & Vallis, 1989). Serving 131 size was sufficient to allow three bites per sample and water was available for rinsing.
132 2.4. Product-specific emoji lexicon development
133 Prior to the main test, a product-specific emoji lexicon was developed. For the selection of emoji a 134 similar procedure was applied as when selecting emotional verbal terms (De Pelsmaeker, Schouteten, 135 & Gellynck, 2013; Jiang, King, & Prinyawiwatkul, 2014). First, a group of 20 children (10 boys and 10 136 girls aged 7-12 years old) individually indicated which emoji they found applicable (CATA) for describing 137 how they felt for each of five speculoos biscuits. The CATA-list with emoji during the pretest was 138 obtained from previous research containing all emoji from two prior research studies with emoji (Gallo, 139 et al., 2017b; Jaeger, Lee, et al., 2017). Also, children had the opportunity to add any missing emoji and 140 provide written feedback. After the individual assessment of the speculoos samples, the children were 141 grouped in 3 groups to shortly provide feedback on the task. Next, the researchers (J.J. Schouteten and 142 X. Gellynck) made the final selection to obtain the product-specific emoji lexicon. The main criteria 143 were the number of participants selecting an emoji (≥10%) and the ability of the emoji to discriminate 144 between the different products (e.g., not same frequency for each product) which have been applied 145 in previous research with children (De Pelsmaeker, et al., 2013; Schouteten, De Steur, Lagast, De 146 Pelsmaeker, & Gellynck, 2017). Also, when children indicated that emoji had a similar meaning for 147 them (e.g. , and ) the most common emoji (based upon feedback of the children during the 148 focus groups) was used. The researchers included positive, negative and neutral emoji in the final 149 selection in order to have a complete overview of how children experienced the samples (Gallo, et al., 150 2017b). Based upon the selection, a final product-specific lexicon of 20 emoji was obtained (see Figure 151 1b). Permission was obtained from Apple Inc. to use these emoji for scientific research.
152 Insert Figure 1a and 1b around here 153 2.5. Questionnaire
154 Children were first introduced to the task by the researchers and each child completed the 155 questionnaire individually. Before starting, the children were informed of the anonymity of the 156 research and were guided through the questionnaire question by question by the researcher. This was 157 done to ensure that every child had sufficient time to complete and understand the questionnaire.
158 Also, the teacher of each class was present during the task to ensure that children were less distracted 159 and to enable them to feel more at ease during the task.
160 The children were first asked how often they consume speculoos using 6 scale labels ranging from 161 “never” to “daily” (Schouteten, De Steur, Lagast, et al., 2017). Next, participants answered three 162 questions related to internet and emoji usage (Jaeger, Vidal, et al., 2017). They were asked how many 163 devices they owned (desktop computer, laptop computer, tablet/IPad and/or smartphone), how often 164 they used the Internet in general and how frequently they used emoji when sending / posting a 165 message (Table 1).
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5 166 Children were instructed to take a first bite of a sample to indicate their overall liking of a sample on a 167 9-point hedonic scale ranging from 1 –dislike extremely to 9 - like extremely. Previous research 168 indicated that children of a similar age to the present study are able to work with this 9-point overall 169 liking scale (Laureati, et al., 2015). Following the hedonic assessment, children were instructed to take 170 another bite of the speculoos sample before checking all the applicable emoji for that particular 171 product sample (Figure 1a and 1b). The instruction for emotional profiling task with emoji was ‘Please 172 take another bite of sample XXX. Please check the emoji which you find applicable to describe how you 173 feel right now after consuming sample XXX. (Multiple emoji might be checked)’. . The order of the 174 emoji was not randomized in order to facilitate the task for the children and avoid fatigue. Based upon 175 their class group, they assessed either the standardized or the product-specific emoji list for all product 176 samples during this task. Children were instructed to rinse their mouth with water between tasting the 177 different product samples. Finally, the respondents indicated their age and gender.
178 2.6. Data analysis 179 2.6.1. Overall liking data
180 Linear mixed modelling was performed to uncover significant differences in hedonic ratings across 181 experimental treatments (standardized vs. product-specific emoji list). Treatments, samples and their 182 interaction were specified as fixed effects, whereas consumer was specified as a random effect.
183 Furthermore, ANOVA was applied on overall liking data for the two questionnaires separately, 184 considering sample as a fixed source of variation and consumer as a random effect. A significance level 185 of 5% was considered. When differences among samples were found, Tukey’s test was used for post 186 hoc comparison of means.
187 2.6.2. Emotional response
188 The data obtained by the emoji list were analyzed using standard procedures for CATA approach 189 (Meyners, Castura, & Carr, 2013) using SPSS Statistics 25 (IBM, United States of America). Cochran’s Q 190 test was used to examine for significant differences in usage frequency for each emoji between the 191 different product samples. If Cochran’s Q test revealed a significant difference, a McNemar test was 192 performed to pairwise assess between which samples significant differences in emoji usage 193 frequencies occurred.
194 Pearson correlation coefficients were computed to examine the relationship between mean overall 195 liking scores and emoji frequency counts.
196 Correspondence analysis (CA) was carried out to examine the relationship between the samples and 197 the emoji from the CATA questions for the standardized and product-specific list separately (Hair, 198 Black, Babin, & Anderson, 2009). CA was carried out on the frequency table containing the samples 199 and the total frequency of each emoji, considering mean overall liking scores as a supplementary 200 variable. Given that CA only considers overall frequency counts, multiple correspondence analysis 201 (MCA) was carried out in order to also consider individual data from the respondents (Hair, et al., 202 2009). MCA was performed separately for the data obtained from the standardized and product- 203 specific emoji list. For the MCA, a contingency table was constructed whereby rows represented each 204 consumer assessing each of the 11 products across the 36 emotions (columns) (Ng, et al., 2013).
205 The Pearson correlation analysis, CA and MCA were performed with R 3.4.2 (R Core Team, 2014) using 206 the R-package FactoMineR version 1.34 for the CA and MCA (Lê, Josse, & Husson, 2008).
207 2.6.3. Comparison of emotional response between emoji lists 239
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208 Multiple factor analysis (MFA) was applied to compare the data sets obtained from the standardized 209 and product-specific emoji lists and examine for patterns of attribute correlations (Lê, Pagès, & Husson, 210 2008; Morand & Pagès, 2006). XLSTAT (Version 2015.1.03.15473, Addinsoft, USA) was used to examine 211 the multivariate product configurations of both datasets for similarities and differences.
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7 212 3. Results
213 3.1. Standardized emoji lexicon 214 3.1.1. Overall liking
215 Product differences were found in overall liking scores (p<0.001) (Table 2). Product groupings based 216 upon Tukey’s HSD multiple comparison test indicated one group of highly liked samples consisting of 217 W2 and W3. Samples W1 and M were moderately liked by the children. Lastly, the wholegrain sample 218 WW (mean value 5.9) was slightly liked by the children but not significantly less compared to the 219 multigrain sample M (mean value 6.3).
220 Insert Table 2 around here 221 3.1.2. Emotional response
222 On average, children used 2.8 emoji (7.5%) for describing how they felt after consuming a sample. The 223 average emoji usage frequency was lowest for the least liked sample WW with 2.5 emoji, and highest 224 for the most-liked sample with 3.3 emoji. On aggregate level, considering all samples, usage 225 frequencies for a specific emoji varied from 0.23 % ( ) to 31.03 % ( ). Given that was only used 226 once by a single person, this emoji was excluded for further data analysis.
227 Significant differences between the usage frequency of the emoji were found for 6 of 38 emoji (16%).
228 Mainly positive emoji were discriminative between the different speculoos samples ( , , , ), 229 next to one negative emoji ( ) and one neutral emoji ( ). It is interesting to note that the emoji 230 was significantly more used for sample W3 compared to sample W2, which shows that this emoji was 231 able to discriminate between these equally high-liked samples.
232 Insert Table 3 around here
233 High positive correlations were found between overall liking of the samples and positively valenced 234 emoji (Table 4). Negative correlations were found for neutral and negatively valenced emoji. Overall, 235 the correlation of only 9 emoji with overall liking reached significance (p<0.05). Significant correlations 236 were primarily obtained by positive emoji ( , , , , , ) with only 2 negative emoji ( , ) 237 and one neutral emoji ( ) showing significant correlations with overall liking scores.
238 Insert Table 4 around here
239 The first two dimensions of the CA on the frequency table for the emoji explained over 77% of the 240 inertia. Positively associated emoji were mainly situated on the left side of the CA plot, while the right 241 side of the CA plot contained primarily negative emoji (Figure 2). Therefore, the first dimension of the 242 CA is linked to the valence (positive vs. negative) of the emoji. The spread across the second dimension 243 of the CA is more difficult to interpret. The CA plot shows that the three wheat samples are closely 244 linked with one another at the left part of the plot and closely linked with positive emoji such as 245 and . The multigrain sample is more linked to neutral emoji (e.g. and ). The lowly liked whole- 246 wheat speculoos is more associated with several negatively valenced emoji (e.g. , and ).
247 Insert Figure 2 around here
248 Given that CA only includes the total frequencies of the emoji, MCA was used to also consider 249 individual responses to each emoji and the product configuration. Similar to the CA plot, the first 250 dimension distinguishes according to the valence of the emoji (Figure 3). In contrast to the CA plot, it 251 is more clear in the MCA plot that the second dimension is related to the arousal for the negative 357
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252 emoji. Negative emoji which are more activated (e.g. , ) were situated higher compared to lower- 253 activated emoji such as and . Moreover, it should be noted that negative emoji were situated 254 higher than the neutral emoji. Furthermore, only three emoji ( , and ) were located in the lower 255 quadrants.
256 Insert Figure 3 around here 257
258 3.2. Product-specific emoji lexicon 259 3.2.1. Overall liking
260 As with the standardized emoji lexicon group, significant differences were found in consumers’ overall 261 liking for the products (p < 0.001) (Table 2). Product groupings indicated by the Tukey’s HSD multiple 262 comparison tests were similar, albeit that it should be mentioned that the mean overall liking of the 263 wholegrain sample WW (mean overall liking: 5.9) was significantly higher than the multigrain sample 264 M (mean overall liking: 4.9). Moreover, a linear mixed model found no effect of the type of list 265 (standardized or product-specific) on the overall liking scores (p = 0.086).
266 3.2.2. Emotional response
267 On average, children used 3.0 emoji (15.2%) to describe their feelings after eating a speculoos biscuit.
268 The average emoji usage frequency was the lowest for the least liked sample WW with 2.5 emoji and 269 the highest for the most liked sample W3 with an average use of 3.9 emoji. Average usage percentages 270 are similar to those obtained from the standardized list. When considering all samples, children used 271 the least (5.9%) and the most (36.5%).
272 Out of the 20 emoji of the list, only three were not able to discriminate between the samples, showing 273 that more emoji of the product-specific list are discriminating compared to the standardized list (85 % 274 vs. 16%). All 6 emoji which were discriminating in the standardized list were also discriminative in the 275 product-specific list. Furthermore, several emoji ( , , , ) were able to discriminate between 276 samples with similar overall liking scores.
277 Insert Table 5 around here
278 Similar as with a standardized list, positive emoji were positively correlated with overall liking while 279 negative emoji were negatively correlated with overall liking (Table 6). Only one neutral emoji was 280 listed in the product-specific emoji list ( ), which was negatively correlated with the overall liking.
281 The correlation with overall liking was not significant for only 3 emoji ( , , ) and these were all 282 positively valenced.
283 Insert Table 6 around here
284 The CA plot was mainly unidimensional, as the first dimension explained over 90% of the variance 285 (Figure 4). The first dimension divided the emoji according to the valence, with the positive emoji 286 situated on the right and the negative emoji on the left of the CA plot. On the right side, the three 287 biscuits made with wheat were present. These 3 samples were closely associated with positive emoji 288 such as , and . The multigrain sample was placed rather in the middle of the plot, without any 289 close links to any emoji. The less-liked whole-wheat sample was located on the left, mainly associated 290 to the neutral emoji . Also, the negative emoji such as and were situated closest by the whole- 291 wheat sample.
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9 292 Insert Figure 4 around here
293 The MCA explained over 90% of the adjusted inertia (Greenacre & Blasius, 2006), of which 82 % in the 294 first dimension and 9.4 % in the second dimension. Similar as with a standardized list, the first 295 dimension was associated to the valence of the emoji with the neutral emoji located on the left of the 296 MCA plot and the positive emoji grouped on the right of the MCA plot.
297 Insert Figure 5 around here 298
299 3.3. Product configurations
300 Statistical comparison of the two product configurations (one by the standardized and one by product- 301 specific list) was obtained by applying MFA. Figure 6 shows the variable correlation circle obtained by 302 the MFA comparing emotional responses for the speculoos samples of the standardized and product- 303 specific emoji lists. The first two dimensions of the MFA explained over 75% of the total variance, 304 indicating a good agreement between both approaches. The first dimension was related to the valence 305 of the emoji, with more negatively valenced emoji situated on the left side of the MFA plot while the 306 positively valenced emoji were located on the right of the MFA plot. Samples W2 and W3 showed the 307 largest variance between the two methods across both axes, mainly in terms of product positioning 308 along the second dimension (Figure 7).
309 Insert Figure 6 and Figure 7 around here 310
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311 4. Discussion
312 The objective of this paper was to compare the performance of a standardized and a product-specific 313 emoji list. Overall, the results indicate that a product-specific emoji list is able to obtain more 314 discriminating profiles between the samples.
315 The standardized emoji list used in this study is based upon 3 focus groups presented in the study of 316 Gallo, et al. (2017b). This list only included facial emoji, consisting of 17 positive emoji, 17 negative 317 emoji and 4 more neutral emoji ( , , , ). As such, it is a more balanced list for the valence 318 compared to the product-specific list. This product-specific list, obtained using a pretest with 20 319 Belgian children, contained 15 positive emoji, 3 negative and 2 neutral emoji. The criteria for selecting 320 the emoji (selection frequency, discriminatory ability and inclusion of positive, negative and neutral 321 emoji) are similar to those in previous research examining the self-assessed emotional response of 322 food products by children (De Pelsmaeker, et al., 2013; Schouteten, De Steur, Lagast, et al., 2017;
323 Schouteten, et al., 2018). When asking the children about the number of emoji during the pretest, they 324 indicated during the pretest that a list should not contain more than 25 items (some younger children 325 even mentioned around 20). In order to keep the list down to 20 items, only the most common emoji 326 was used when several emoji had a similar meaning according to the children of the pretest (e.g. , 327 and ). A direction for future research is to examine if certain emoji could be grouped in clusters 328 of similar meaning to facilitate the shortlisting of emoji. Given that commercial samples were used in 329 this pretest, it is rather normal that the products are more associated with positive emotions and emoji 330 (Gallo, et al., 2017b; Meiselman, 2015). This product-specific list also contained several non-facial 331 emoji such as and . These non-facial emoji are more intuitive, which is interesting when working 332 with (young) children as the meaning of facial emoji might not always be clear (Schouteten, et al., 333 2018). Moreover, previous research with adults indicated that non-facial emoji ( and ) were the 334 most frequently used emoji to indicate how they perceive food products (Jaeger, Lee, et al., 2017).
335 However, one needs to consider that these non-facial emoji might be more related to the hedonic 336 appraisal of a product than resembling an emotion. Future research is therefore recommended to 337 examine the impact of non-facial emoji on assessing children’s evoked emotions. One non-facial emoji 338 ( ) was also able to discriminate between equally liked samples, but future research is needed to 339 examine the potential influence of non-facial emoji on the overall acceptance and the possibility to 340 discriminate between samples.
341 In the product-specific emoji group, the overall liking score of the multigrain sample significantly 342 differed from all the wheat samples which was not the case in the standardized emoji group. Thus, it 343 appears that children discriminate slightly better for hedonic liking when using a product-specific 344 listHowever, it should be noted that the ranking of the samples does not change and there is no 345 significant effect of the cluster thus this difference is likely due to the difference in composition of the 346 panels. Overall, it can be concluded that there is no effect of type of list on the overall liking. While 347 research with adults found little evidence that asking emotional associations (with words) could 348 influence hedonic liking (King, Meiselman, & Carr, 2013; Schouteten, Gellynck, et al., 2017), it is unclear 349 if this is the case when working with emoji and especially using a children population. In this study, 350 hedonic liking was assessed before the emotional profiling task as recommended by King, et al. (2013) 351 in order to limit the potential influence of the emoji on the hedonic liking. It could be that the 352 proportion of positive and negative emoji played a role in discriminating the samples regarding overall 353 liking as the product-specific list contained mainly positively valenced emoji (15) while the 354 standardized list had a balanced number of positively and negatively valenced emoji. Nevertheless, 355 more research is recommended to examine if (certain types of) emoji questions might influence the 356 hedonic scores of food products when working with children.
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11 357 The standardized list contained 38 emoji (Gallo, et al., 2017b) whereas the product-specific list, 358 established after a pretest with children, contained 20 emoji. While the average usage frequencies of 359 the emoji differed, with 15.2% emoji used of the product-specific emoji list against 7.5% emoji of the 360 standardized list, it appears that the average number of emoji is similar regardless of type of list 361 (product-specific: 3.0 vs. standardized: 2.8). The average number of used emoji is also similar to a 362 previous study with biscuits (Schouteten, et al., 2018). The other two studies using emoji to assess 363 children’s food product evaluations did not report the average usage frequencies, which does not 364 make a comparison possible (Gallo, et al., 2017a, 2017b). The study of Schouteten, De Steur, Lagast, 365 et al. (2017) reported that children used 3.8 emotional words to describe how they felt when 366 consuming speculoos biscuits during a blind evaluation condition. This is higher than the scores 367 reported here when working with emoji, but might be the result of working with a lower number of 368 items (only 16 emotional words) or that only four products were assessed.
369 This study supports earlier findings that emoji can be used to obtain discriminatory sensory profiles 370 when working with samples of the same product category (Schouteten, et al., 2018). Furthermore, the 371 discriminatory ability is in line with those of two other CATA studies for emotional profiling with 372 children, a study which linked emotional terms to flavored milk brands (De Pelsmaeker, et al., 2013) 373 and a paper reporting the associations of emotions with sandwich pictures (Jervis, Jervis, Guthrie, &
374 Drake, 2014). Although children used a similar number of emoji for the samples, this study found that 375 the emoji of the product-specific emoji list are better able to discriminate between the samples than 376 the standardized emoji list. Moreover, only was able to partially discriminate between equally 377 highly-liked samples when using the standardized list. In contrast, 4 out of 20 emoji ( , , , ) 378 were able to discriminate between samples with similar overall liking scores when using the product- 379 specific emoji list. As a standardized list is normally longer because it contains many items in order to 380 not miss out any important items, this might have led to a lower quality of the data due to fatigue or 381 boredom (Jaeger, et al., 2013; Spinelli, et al., 2015), or due to a wider spread of the children’s answers 382 over multiple emoji of similar meanings. Moreover, using more items could also result in a higher use 383 of certain items related to performing the task (e.g. ) instead of selecting emoji related to the food 384 tested (Schouteten, et al., 2015b). However, more research is needed to confirm if the discriminatory 385 ability between equally liked samples is indeed better when working with a product-specific emoji list, 386 across diverse product types.
387 High positive correlations were found between overall liking scores and positive emoji while negative 388 correlations were established between overall liking and negative emoji. Moreover, negative 389 correlations were also found for neutral emoji. This supports previous findings by Schouteten, et al.
390 (2018) that neutral emoji might be experienced as more negative by children compared to adults 391 (Jaeger & Ares, 2017). Furthermore, it is important to mention that more correlations were significant 392 when working with a product-specific list (17 out of 20) compared to a standardized list (8 out of 38) 393 advocating that higher quality of data was obtained when using a product-specific emoji list.
394 The first dimension of the CA plot of both the standardized and product-specific emoji list is clearly 395 based upon the valence of the emoji (Figure 2 and 4). Also, the neutral emoji were often located 396 between the positive and negative emoji in the CA plot, albeit that most of the neutral emoji were 397 closer to the negative emoji. This is in line with previous research with children (Schouteten, et al., 398 2018) and adults (Jaeger, Lee, et al., 2017). Previous studies suggested that the second dimension of 399 the CA plot with emoji is based upon arousal (Jaeger, Lee, et al., 2017; Schouteten, et al., 2018), but 400 this was less pronounced in this study. Moreover, the second dimension of the CA plot of the product- 401 specific emoji only explained 3% of the total variance displaying the limited relevance of that 402 dimension. But one needs to bear in mind that the selection of the samples could have contributed to 593
594 595 596 597 598 599 600 601 602 603 604 605 606 607 608 609 610 611 612 613 614 615 616 617 618 619 620 621 622 623 624 625 626 627 628 629 630 631 632 633 634 635 636 637 638 639 640 641 642 643 644 645 646 647
403 the rather low arousal (Jaeger, Lee, et al., 2017). Furthermore, the fact that over 90% of the variance 404 is explained in the first dimension when working with a product-specific emoji list could be related to 405 the inclusion of the different thumbs emoji (e.g. and ) These emoji are actually an expression of 406 liking and not of emotions. As such, they might contribute to the higher explained variance, but all on 407 the valence dimension. Therefore, more research is needed with other food product categories and 408 experimental product development samples which might also be less liked. In this study, we opted to 409 work with commercial samples but such commercial products are normally associated with more 410 positive or neutral emotions and emoji (Gallo, et al., 2017b; Jiang, et al., 2014; Meiselman, 2015). It 411 should be noted that with the whole-wheat and multigrain biscuits two less-liked samples were 412 included which were associated with more negative emoji. Moreover, the inclusion of little liked 413 samples might lead to children not willing to complete the test.
414 The MCA plot of the product specific list explained over 90% of the total variance while the MCA plot 415 of the standardized list was of a lower quality given that it only explained 62% of the total variance.
416 The first dimension of the MCA plot of both the standardized and product-specific emoji lists divide 417 the emoji according to their valence. Moreover, the MCA plot of the product-specific emoji list is rather 418 similar to the one obtained from a previous study using a list of 33 facial emoji (Schouteten, et al., 419 2018).
420 Although the MFA showed that that emotional responses obtained from the standardized and product- 421 specific emoji list were similar, the product positions differed for the W1 and W2 along the second 422 dimension. This second dimension is traditionally associated with the level of arousal / engagement 423 when using self-report emotional questionnaires (Jiang, et al., 2014), but the meaning of the second 424 dimension was less clear in the current study. Nevertheless, given that main differences were observed 425 in the product positioning along the second dimension, it appears that there might be a difference in 426 the capability of the standardized and product-specific emoji list to measure differences along the 427 second dimension. More research is recommended to see to which extent these differences persist 428 with other products and using a broader consumer sample, or if these results were directly caused by 429 the low usage frequencies of some emoji in the standardized emoji list.
430 This study opted to work with a between-subjects design, a design which has been previously applied 431 in the field of consumer and sensory science when comparing the performance of two approaches to 432 measure consumer’s emotional associations of food products (Ng, et al., 2013; Spinelli, Masi, Dinnella, 433 Zoboli, & Monteleone, 2014). As such, this study eliminates within-subjects factors that may play a role 434 when consumers evaluated the samples under two different conditions (e.g. carry-over effects).
435 Although future research might opt to use a within-subjects design in order to control for potential 436 between-subjects effects, one needs to bear in mind that no significant differences were found in 437 several key parameters (demographics, consumption, and internet and emoji usage) of the two sample 438 groups in this study.
439 The researchers opted to not randomize the order of emoji in order to facilitate the task for the 440 children. Previous research with adults found little impact of the order on the emotional profiling task 441 and concluded that the absence of randomization does not invalidate the outcome (King, et al., 2013).
442 However, more research is needed to examine if order effects occur when using emoji to assess 443 consumer’s emotional associations with food products.
444 The experiment took place at school, which is an asset when conducting research with children and is 445 also a realistic consumption environment (Laureati, et al., 2015). However, previous research with 446 adults indicated that the research setting might influence the results when asking for the emotional 447 associations of food products (Danner, et al., 2016; Schouteten, De Steur, Sas, De Bourdeaudhuij, &
651 652 653 654 655 656 657 658 659 660 661 662 663 664 665 666 667 668 669 670 671 672 673 674 675 676 677 678 679 680 681 682 683 684 685 686 687 688 689 690 691 692 693 694 695 696 697 698 699 700 701 702 703 704 705
13 448 Gellynck, 2017). Interesting future research possibilities lie in comparing context effects at laboratory 449 context, natural eating context (e.g. at school, at home) and even virtual evaluation context.
450 711 712 713 714 715 716 717 718 719 720 721 722 723 724 725 726 727 728 729 730 731 732 733 734 735 736 737 738 739 740 741 742 743 744 745 746 747 748 749 750 751 752 753 754 755 756 757 758 759 760 761 762 763 764 765
451 4. Conclusion
452 Recent research indicated that including emoji measurements might help to better predict children’s 453 actual food preference, yet there is still little research carried out using emoji with children. This study 454 contributes to the current literature by showing that a product-specific list might provide better 455 product discrimination than a standardized emoji list. This study also found that non-facial emoji such 456 as and have rather high usage frequencies, advocating the inclusion of such emoji in future 457 studies with children. However, one needs to consider that this study focused on a familiar food 458 product and only included commercial samples.
459 Future research might compare the performance of an emoji list with a word list, to examine the best 460 method to obtain discriminatory emotional profiles of product samples according to the purpose of 461 the research. Moreover, since children may not be able to verbalize how they experience a food 462 product, the use of emoji may bring new potential in sensory and emotion research with children.
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575 576 947 948 949 950 951 952 953 954 955 956 957 958 959 960 961 962 963 964 965 966 967 968 969 970 971 972 973 974 975 976 977 978 979 980 981 982 983 984 985 986 987 988 989 990 991 992 993 994 995 996 997 998 999 1000 1001
577 Table 1. Socio-demographic characteristics of the sample groups
Standardized lexicon (N=87) Product-specific lexicon (N=85)
Mean age in years (S.D.) 10.1 (0.9) 10.0 (0.9)
Gender (% females) 47.1 51.8
Speculoos consumption frequency (% respondents)
Less than once a month 21.8 21.2
Monthly 26.4 31.8
Weekly 26.4 18.8
Multiple times a week 18.4 22.4
Daily 6.9 5.9
Internet usage (% respondents)
Less than every two weeks 3.4 3.5
Once every two weeks 2.3 3.5
Once a week 13.8 10.6
Multiple times a week 31.0 27.1
Daily 49.4 55.3
Mobile devices owned (% respondents)
0 0 0
1 device 14.9 14.1
2 devices 27.6 24.7
More than 2 devices 57.5 61.2
Emoji usage in messaging communication (%
respondents)
Never 10.3 4.7
Almost never 10.3 5.9
Sometimes 26.4 35.3
(Almost) everytime 52.9 54.1
578 579 1005 1006 1007 1008 1009 1010 1011 1012 1013 1014 1015 1016 1017 1018 1019 1020 1021 1022 1023 1024 1025 1026 1027 1028 1029 1030 1031 1032 1033 1034 1035 1036 1037 1038 1039 1040 1041 1042 1043 1044 1045 1046 1047 1048 1049 1050 1051 1052 1053 1054 1055 1056 1057 1058 1059
19 580 Table 2. Mean overall liking of the samples from the standardized lexicon (n = 87) and product-specific lexicon (n = 85)
581 experiments
Standardized lexicon (n = 87) Product-specific lexicon (n = 85)
W1 6.9b 6.6b
W2 7.7a 7.2a
W3 7.8a 7.7a
WW 5.7c 4.9c
M 6.3bc 5.9b
582 583 1065 1066 1067 1068 1069 1070 1071 1072 1073 1074 1075 1076 1077 1078 1079 1080 1081 1082 1083 1084 1085 1086 1087 1088 1089 1090 1091 1092 1093 1094 1095 1096 1097 1098 1099 1100 1101 1102 1103 1104 1105 1106 1107 1108 1109 1110 1111 1112 1113 1114 1115 1116 1117 1118 1119
584 Table 3. Frequency (%) in which each emoji was used by the children to describe the samples using the standardized emoji
585 list and p-value of the Cochran’s test of each emoji (n = 87).
Emoji Mean usage frequency
W1 W2 W3 WW M p
33.8 32.2ab 43.7a 42.5a 25.3b 25.3b <0.001
31.0 27.6b 42.5a 46.0a 23.0b 16.1b <0.001
29.9 33.3 34.5 31.0 21.8 28.7 0.250
21.1 19.5b 31.0a 24.1ab 12.6b 18.4ab 0.011
17.0 16.1b 19.5b 27.6a 10.3b 11.5b 0.002
16.1 13.8 17.2 24.1 11.5 13.8 0.087
12.6 12.6 14.9 17.2 6.9 11.5 0.137
12.4 9.2 17.2 12.6 11.5 11.5 0.301
8.5 10.3 8.0 9.2 5.7 9.2 0.821
8.3 8.0 9.2 8.0 9.2 6.9 0.966
7.8 8.0 5.7 12.6 6.9 5.7 0.312
6.1 16.1 19.5 20.7 12.6 11.5 0.108
5.1 4.6 4.6 6.9 3.4 5.7 0.785
4.6 4.6 1.1 2.3 9.2 5.7 0.073
4.6 2.3ab 3.4ab 0.0b 8.0a 9.2a 0.012
4.4 8.0 1.1 4.6 2.3 5.7 0.187
4.1 4.6 3.4 6.9 4.6 1.1 0.372
3.7 2.3 1.1 6.9 4.6 3.4 0.241
3.7 1.1ab 0.0b 2.3ab 6.9a 8.0a 0.014
3.4 2.3 2.3 4.6 4.6 3.4 0.753
3.2 2.3 3.4 2.3 4.6 3.4 0.910
3.0 2.3 3.4 2.3 4.6 2.3 0.822
3.0 2.3 4.6 2.3 4.6 1.1 0.513
3.0 3.4 3.4 0.0 2.3 5.7 0.260
3.0 2.3 2.3 0.0 5.7 4.6 0.158
2.5 2.3 1.1 1.1 3.4 4.6 0.519
2.5 0.0 3.4 1.1 2.3 5.7 0.116
2.3 2.3 0.0 0.0 3.4 5.7 0.061
2.1 2.3 0.0 2.3 2.3 3.4 0.588
2.1 1.1 2.3 1.1 3.4 2.3 0.800
1.8 2.3 3.4 1.1 1.1 1.1 0.525
1.8 2.3 0.0 1.1 2.3 3.4 0.446
1.6 2.3 1.1 0.0 3.4 1.1 0.446
1.1 0.0 1.1 0.0 2.3 2.3 0.406
0.9 1.1 0.0 0.0 2.3 1.1 0.478
0.9 1.1 0.0 2.3 1.1 0.0 0.478
0.7 0.0 0.0 1.1 2.3 0.0 0.255
0.2 0.0 0.0 0.0 1.1 0.0 0.406
586 587 1123 1124 1125 1126 1127 1128 1129 1130 1131 1132 1133 1134 1135 1136 1137 1138 1139 1140 1141 1142 1143 1144 1145 1146 1147 1148 1149 1150 1151 1152 1153 1154 1155 1156 1157 1158 1159 1160 1161 1162 1163 1164 1165 1166 1167 1168 1169 1170 1171 1172 1173 1174 1175 1176 1177
21 588 Table 4. Correlation coefficients between emoji of the standardized list and mean overall liking scores (n = 87). Significant
589 correlations are in bold (p <0.05).
Emoji Correlation p
0.891 0.043
-0.839 0.075
0.541 0.346
-0.810 0.097
-0.928 0.023
0.829 0.083
-0.698 0.190
-0.975 0.005
-0.293 0.633
0.853 0.066
-0.857 0.064
0.908 0.033
0.500 0.390
-0.412 0.490
0.970 0.006
0.936 0.019
-0.248 0.688
0.057 0.928
0.077 0.902
-0.485 0.408
0.611 0.273
0.219 0.723
0.501 0.390
-0.448 0.450
0.410 0.493
-0.551 0.336
-0.698 0.190
0.912 0.031
0.488 0.404
0.959 0.010
-0.042 0.947
-0.001 0.999
-0.757 0.139
-0.810 0.097
-0.827 0.084
-0.735 0.157
-0.974 0.004
590 591 1183 1184 1185 1186 1187 1188 1189 1190 1191 1192 1193 1194 1195 1196 1197 1198 1199 1200 1201 1202 1203 1204 1205 1206 1207 1208 1209 1210 1211 1212 1213 1214 1215 1216 1217 1218 1219 1220 1221 1222 1223 1224 1225 1226 1227 1228 1229 1230 1231 1232 1233 1234 1235 1236 1237
592 Table 5. Frequency (%) in which each emoji was used by the children to describe the samples using the product-specific
593 emoji list and p-value of the Cochran’s test of each emoji (n = 85).
Emoji Mean usage frequency
W1 W2 W3 WW M p
36.5 31.8bc 44.7ab 52.9a 17.6d 28.2cd <0.001
29.4 31.8ab 42.4a 35.3a 16.5c 21.2bc <0.001
28.0 22.4b 36.5a 43.5a 16.5b 21.2b <0.001
20.7 20ab 24.7ab 29.4a 14.1b 15.3b 0.021
19.1 22.4a 21.2ab 31.8a 8.2c 11.8bc <0.001
17.6 15.3ab 21.2a 27.1a 9.4b 15.3ab 0.007
16.7 15.3b 4.7c 4.7c 30.6a 28.2a <0.001
15.8 15.3ab 23.5a 23.5a 4.7b 11.8b <0.001
15.1 17.6a 20.0a 22.4a 4.7b 10.6ab 0.003
13.6 10.6b 21.2ab 24.7a 4.7c 7.1b <0.001
13.6 11.8ab 18.8a 21.2a 7.1b 9.4b 0.002
12.0 16.5ab 7.1b 17.6a 11.8ab 7.1b 0.041
11.8 11.8ab 12.9ab 18.8a 5.9b 9.4ab 0.040
10.6 4.7b 1.2b 2.4b 27.1a 17.6a <0.001
9.2 10.6 8.2 14.1 5.9 7.1 0.274
7.8 7.1b 0.0c 0.0c 23.5a 8.2b <0.001
7.3 3.5bc 1.2bc 1.2c 20.0a 10.6ab <0.001
6.6 8.2 10.6 7.1 2.4 4.7 0.112
6.6 9.4 8.2 8.2 1.2 5.9 0.099
5.9 3.5bc 0.0c 1.2bc 16.5a 8.2ab <0.001
594 595 1241 1242 1243 1244 1245 1246 1247 1248 1249 1250 1251 1252 1253 1254 1255 1256 1257 1258 1259 1260 1261 1262 1263 1264 1265 1266 1267 1268 1269 1270 1271 1272 1273 1274 1275 1276 1277 1278 1279 1280 1281 1282 1283 1284 1285 1286 1287 1288 1289 1290 1291 1292 1293 1294 1295
23 596 Table 6. Correlation coefficients between emoji of the product-specific list and mean overall liking scores (n = 85). Significant
597 correlations are in bold (p <0.05).
Emoji Correlation p
0.884 0.046
-0.956 0.011
-0.966 0.007
0.181 0.770
0.931 0.021
0.973 0.005
0.834 0.079
0.999 <0.001
0.963 0.008
0.727 0.164
0.871 0.055
-0.956 0.011
-0.970 0.006
0.902 0.036
0.951 0.013
0.927 0.023
-0.955 0.011
0.953 0.012
0.970 0.006
0.938 0.018
598 599 1301 1302 1303 1304 1305 1306 1307 1308 1309 1310 1311 1312 1313 1314 1315 1316 1317 1318 1319 1320 1321 1322 1323 1324 1325 1326 1327 1328 1329 1330 1331 1332 1333 1334 1335 1336 1337 1338 1339 1340 1341 1342 1343 1344 1345 1346 1347 1348 1349 1350 1351 1352 1353 1354 1355
Figure 1a. Overview of the standardized emoji list (Gallo, et al., 2017b)
Figure 1.b. Overview of the product-specific emoji list 2
3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56
Figure 2. Representation of the samples and the emoji in the first and second dimensions of the correspondence analysis obtained from the standardized emoji CATA total frequency counts (n = 87).
3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57
Figure 3. Representation of the samples and the emoji in the first and second dimensions of the multiple correspondence analysis obtained using the emoji CATA individual consumer responses of the standardized list (n = 87).
2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56
Figure 4. Representation of the samples and the emoji in the first and second dimensions of the correspondence analysis obtained from the product-specific emoji CATA total frequency counts (n = 85).
3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57
Figure 5. Representation of the samples and the emoji in the first and second dimensions of the multiple correspondence analysis obtained using the emoji CATA individual consumer responses of the product-specific list (n = 85).
2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56
-1 -0,75 -0,5 -0,25 0 0,25 0,5 0,75 1
-1 -0,75 -0,5 -0,25 0 0,25 0,5 0,75 1
F2 (15.78 %)
F1 (61.81 %)
Product-specific Standardized
Figure 6. Representation of the emoji in the first and second dimensions of the multiple factor analysis using the data from the standardized (n = 87) and product-specific emoji list (n = 85).
3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57
W3 Product-specific W3 Standardized
WW Product-specific
WW Standardized
W1.Product-specific W1 Standardized
M Product-specific M Standardized
W2 Product-specific
W2 Standardized -2
-1,5 -1 -0,5 0 0,5 1 1,5
-2,5 -2 -1,5 -1 -0,5 0 0,5 1 1,5 2 2,5
F2 (15.78 %)
F1 (61.81 %)
Figure 7. Representation of the samples in the first and second dimensions of the multiple factor analysis using the data from the standardized (n = 87) and product-specific emoji list (n = 85). Each product is represented using two points corresponding to each method (Standardized and product-specific), and its compromise position in the middle.
2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56
