Transformer-based cynical expression detection in a corpus of Spanish YouTube reviews

Consumers of services and products actively engage through social networks when they are dissatisfied, exhibiting a wide range of behaviors. Encinas and Cavazos (2021). Encinas presents a classification of dysfunctional consumer behaviors: mild behaviors such as rudeness, complaints, skepticism, or tantrums; moderate behaviors such as manifestations of cynicism, attempts at manipulation, or inappropriate comments and foul language; and intense consumer behaviors such as fraud, theft, verbal aggression, or revenge.

Consumer cynicism can generate feelings of betrayal and deception, leading to anger

Negative Feelings where consumers reflect negatively on a product, usually in a subjective way that is influenced by their personal experiences.

Specific Reasons where consumers identify the specific aspects or components of a product to which their negative feelings are directed, for instance, fuel efficiency or seating comfort.

Attitude of being right where consumers express their rejection of the product and in contrast assert their own correctness.

In (Peled and Reichart, 2017) the identification of sarcasm is based on the ability to generate a non-sarcastic text from an original sarcastic text. e.g., from the sarcastic text "how I love Mondays" is obtained "how I hate Mondays" or "I really hate Mondays". In this work, the sarcasm dataset contains 3000 sarcastic tweets, each with five different non-sarcastic interpretations, and the algorithm based on Machine translation places particular emphasis on feeling words.