Poster backgrounds

Study location and respondents' recruitment. We conducted the study at the Korkeasaari Zoo, Helsinki, Finland. The respondents were recruited through direct requests in situ at the zoo. The study was conducted on two consecutive summers, 2021 and 2022, from June to September. The study took place in an auditorium at the zoo. Every session began with a brief explanation of its aims, procedure, informed consent and instructions. After that, the respondents filled in the questionnaire, and the research assistants showed the stimulus video. In the end, we gave the respondents the possibility to remain seated to listen to the study team’s explanation of the events and emotional states in the videos, with some background information about the stimulus animals.  If any respondents had given the English version of the form, everything was also explained in English. The introduction to the videos was identical in content, regardless of the language used in the sessions, and participants were given the same background information and instructions, whether in English or Finnish. 

Questionnaire. The questionnaires included questions about the respondent’s age group (18–30, 31–45, 46–60, 61–75, 76 and over), gender (woman, man, other, prefer not to say), and animal experience (currently having a pet /not), in the year 2021 there were separate question of owning a cat. The questionnaire included three previously published and validated instruments: the Animal Empathy Scale (AES; Paul, 2000), the Social Dominance Orientation scale (SDO; Dhont et al., 2014), and the Speciesism scale  (SPEC; Dhont et al., 2014), all translated into Finnish.

 The 2022 questionnaire was also available in English. 

Animal emotion videos. We collected video clips depicting various emotions of three species, all living and filmed at the Korkeasaari Zoo: the Barbary macaque, the Siberian tiger, and the markhor goat, also known as the screw-horned goat. The species were chosen to represent different mammalian groups and selected so that there would be one that was evolutionary close to humans (the Barbary macaque as another primate), and one that would be somewhat similar to a species that many participants would have personal experience from (the Siberian tiger, belonging to the same family as the domestic cat) and one for which neither of the above would be true for most of the zoo visitors (most people do not have personal experience of goats).

We obtained the video footage by ourselves. We filmed all material from the same viewing areas that the visitors had access to during zoo opening hours. The animals were not disturbed in any way for the purpose of obtaining the footage. 

The length of videos was restricted by our decision to limit the amount of contextual information provided to viewers, such as a carcass hanging in a tree for the Siberian tigers or a physical conflict breaking out among the macaques. We aimed at having an equal number of clips of each species in each emotional state. 

Then, to derive numeric values for each clip, Helena Telkänranta and Sonja Koski, both experienced scientists in the fields of animal behaviour and emotions, scored the emotional states of the target animals on each video clip on a 7-step Likert scale for both valence and arousal separately, based on the behaviour and facial expressions visible in each clip. Then they carried out a consensus scoring for each clip. Finally, for the statistical analyses, the scores were recorded into emotion categories, where valence was scored as ‘positive' and arousal as high for scores 5–7, valence as neutral and arousal as average for reference score 4, and valence as 'negative' and arousal as 'low' for reference scores 1–3. 

The final compilations of the clips included 15 videos, 5 of each species. They were divided into three sets so that each video compilation included clips of all three species and different levels of arousal and valence. Each clip was included in the compilation three times: in real-life speed, as 0.5x slow motion, and as a still image lasting 10 seconds of the target animal. The total duration of the compilations was 3.1, 3.6 and 3.14 minutes. 

• Example video and experts' descriptions: Example video

Emotion recognition by the respondents. We showed the respondents short video clips depicting the target animal exhibiting an emotion in a real-life situation. The respondents were shown one of the three video clip compilations. The video was paused after each clip to allow respondents time to score it. The respondents scored each clip for arousal and valence, respectively, on a 7-point Likert scale. The explanations were given as follows: 1 = negative, 7 = positive for valence, and 1 = low, 7 = high for arousal. 

Analyses. Altogether, we obtained 5410 ratings for valence and arousal, respectively, from 1082 respondents. We excluded from analyses the respondents who had not rated one or more of the clips or had left questions concerning gender, age, or having a pet unanswered (N = 85). Regarding gender, respondents who categorised themselves as 'other' or chose the 'not want to answer' option were excluded from the analysis due to the small number (respectively 9 and 10). Eleven respondents who reported their age as over 75 years were combined into the 61–75 age group.

First, we recalculated the accuracy of the valence and arousal ratings given by the respondents, by assessing whether the answer matched the emotion category ratings done by the animal behaviour experts as explained above ('positive' / 'high' = reference scores 5–7, vs 'negative' / 'low' = reference scores 1–3). Comparing these yielded the accuracy of each video clip from each respondent. The scores for neutral valence and average arousal, indicated by value 4, were omitted from analyses. This resulted in a final dataset of 3889 responses. 

Next, we assessed the factors predicting the accuracy of the respondents’ recognition using linear models. We use separate models to evaluate the effects on valence and arousal. In models the target variable was the accuracy of the evaluation (correct / not correct) and the predictors were the reference categories of valence and arousal, species (markhor, Siberian tiger, Barbary macaque), gender (woman/man), age group (18–30, 31–45, 46–60, 61 and over) and pet ownership (yes or no). The year of data collection (2021/2022) and video clip compilation were included as additional predictors. We also modelled a subset of the 2021 data for recognition accuracy of Siberian tiger emotional states only, adding cat ownership into the model as a predictor (yes, no) and the response variable was the accuracy of valence and arousal recognition as above.

Initially, we attempted to use Generalised linear mixed models (GLMM) with the respondent identity as a random variable to account for pseudoreplication in our sample, as each respondent provided ten scores to the data (five for valence and five for arousal). However, these models failed to converge. The disproportionate ratio between the total number of responses (>5000) and the answers provided by a single respondent (5 per model) is the likely reason for this, as total variation in our data explained by respondent identity is minuscule, in comparison to that explained by the variables included in the models. When running the models with respondent ID number as a random factor despite the warnings, variation explained by the random factor was estimated as 0.0000, both for valence and arousal. 

All analyses were conducted using R statistical software (v4.2.2; R Core Team 2022) with generalised linear regression analysis (GLM) as implemented in package lme4 (v1.1-26 ⁸⁵). Evaluating a model we used McFadden's pseudo-R²⁸⁶ and Akaike Information Criterion, AIC (Sutherland et al. 2023). For factors with multiple levels, estimated marginal means were used to test for significant pairwise differences between factor levels, using the package emmeans (v1.10.4.900003 ⁸⁷). The emmeans package was also used to calculate log-odds and convert them to predicted probabilities.

Altogether, we obtained 5306 valence and arousal rating scores from 1082 respondents. There were 2160 scores from 432 respondents in 2021, collected over 21 days (1–3 times per day), and 3250 scores from 650 respondents in 2022 (1–5 times per day), collected over 48 days (Table 1). 63% of the respondents self-identified as women, 35% as men, and 2% (N = 19) as non-binary or chose not to specify their gender; this last group was excluded from the analyses. The most respondents were in the age group 31–45 years (46%). Compared to the overall demographic of the Helsinki Zoo visitor profile, the study had a bias toward women (in our data women 65%, in the Korkeasaari visitor profile in the year 2021 52%). 

Effects of predictors on recognition accuracy (0/1) of emotional valence (positive vs negative) and arousal (low vs high), as observed in video clips. Model estimates of a generalised linear model (GLM) with a binomial family are given with standard error, and p-values are based on a chi-square likelihood ratio test. 

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