## 5 Implementation and Results
### Emotions Distribution of Controversial and Non-Controversial Artworks  
The structure of the Instagram datasets was further investigated by analyzing their distribution. Both sets of data contained both the final ranking scores and the emotion attribute. The distribution of the three selected emotions (surprise, neutral, and disgust) across both datasets is depicted in Figure 3. The selection of emotions was based on user posts and is limited to three distinct emotions because other lexicon-based methods, such as NLTK, classify emotions into three equally categories, such as positive, negative, and neutral. Therefore, we conformed to this practice. The selection of emotions was based on [PERSON]'s theory of basic emotions and a broader taxonomy of eleven pairs of emotions consisting of three columns, where the kinds of emotion, for instance, are emotions related to object properties, event-related emotions, social emotions, etc. [55]. The other two columns contain positive and negative emotions. For our task, we selected the first category of emotions related to the object properties, and among the positive and negative emotions, we selected surprise and disgust, respectively. We used the neutral emotion for works that did not express any emotion or were partially insensitive. According to the number of samples, the datasets are small because the emotion classification only pertains to the three most popular artworks in each dataset, as determined by ranking. The controversial artworks revealed a normal distribution of emotions, as depicted by the graph, with surprise represented in 430 posts, disgust in 232 posts, and neutral or ambiguous in 232 posts. Figure 3 reveals that in the dataset of non-controversial artworks, 75 posts contain the emotion of surprise, 24 posts contain the emotion of disgust, and 327 posts contain no emotion. According to the data, the emotion distribution in controversial works of art is more typical. However, in the non-controversial works of art, the two most intense emotions, namely surprise and disgust, are significantly less frequent than in the first set of data, and the neutral emotion predominates. This may be due to several factors, but a review of the literature on the effect of art indicates that the inherent qualities of pieces, such as those found in controversial works of art, may be responsible for evoking strong emotions. Regarding the non-controversial works of art, which neither provoke nor possess particularities, this may also explain why attendees exhibited no emotion. In addition to the emotions, the graph below displays the score distribution for the top three works of art. The scores in the table are the result of adding all post-ratings for each piece of artwork. The total number of scores in the first dataset of the three most popular controversial artworks is greater than that in the second dataset of the three most popular non-controversial artworks, as indicated by the mean value in Table 8. This does not occur at all values and has no effect on the result, as it is a result of and dependent on the amount of data. As explained in the experiment, this also proves the premise that controversial artworks may elicit more intense aesthetic emotions, such as disgust or surprise, than non-controversial artworks. The potential for an artwork's qualities and the intense emotions it evokes to increase its popularity through social media engagement is a further argument in favor of the concept. As we observed, viewers were more surprised by the first scenario than the second. Based on extant research and previous experiments, it is highly likely that this is due to the inherent qualities and meaning of the artworks. Even though the qualities of non-controversial artworks were not as distinct as those of controversial artworks, observers did not experience strong emotions when viewing them. The present thesis was  
Figure 3: Emotion distribution of controversial and non-controversial popular artworks.