‘‘color’’,

For evaluating the predicted sentiment scores we use
the MART dataset which consists of 500 abstract paint-
ings [50] labeled as evoking positive or negative sentiment.
Each artwork received 20 ratings from 20 different subjects
and the average score is considered the ground-truth value.
Besides evaluating the predicted sentiment scores on the
MART dataset which includes positive-negative emotional
judgments, we use the newly introduced WikiArt Emotions
dataset [51] to analyze how the predicted sentiment scores
relate to different emotion categories. The WikiArt Emo-
tions dataset includes emotion annotations for 4105 artworks,
belonging to 22 different style categories, collected from
WikiArt.org. For the purpose of our work we use a subset
of 3379 paintings and analyze the relationship between the
predicted sentiment scores and 8 different emotion categories.
A_Deep_Learning_Perspective_on_Beauty_Sentiment_and_Remembrance_of_Art