Sofia Vlachou and Michail Panagopoulos
Art is ubiquitous nowadays. Thus, the individual's engagement goes beyond observation. Arts transmission relies on technology. Mobile devices allow access to a lot of art. This study's primary objective is to examine the aesthetic experience and the viewer's opinion with pieces of public art that are permanently (in squares, monuments, and bridges, etc.) or periodically displayed in Paris. The selection of this metropolis was based on its cultural, artistic, and historical wealth. On Instagram, a collection of public artworks was identified by title or location. It is therefore intriguing to investigate how viewers of artworks expressed their emotions or opinions in a broader sense. To ensure the editability of textual data, we adhered to the complete procedure for data cleansing. Several lexicon-based approaches for emotion recognition and opinion mining of Python programming language packages for natural language processing (NLP) or other methods like Term Frequency -Inverse Document Frequency (TF-IDF) will be used to examine the experience of art viewers. Specifically, linguistic packages will identify a text's positive, negative, or neutral emotions as well as the frequency of words to determine their association to a particular content. In addition, a comprehensive literature search did not reveal any relevant studies regarding the emotional recognition and opinion mining of art viewers via social media platforms like Instagram. Contrary to other museum-based or lab-based studies, we anticipate that this work will serve as a springboard for future research into aesthetic experience and opinion mining in the domain of social media arts.
