Empathy and Resonance in Interactive Digital Climate Fiction
Notice bibliographique
Résumé
Readers of fiction often relate their own experiences to a story’s character or events. Resonance in Fiction is fostered through the power of the narrative to evoke emotions and a sense of reflection in the audience. The extent to which a fictional tale resonates with a reader depends on a number of complex interrelated factors, including, in the case of a story, the structural and stylistic elements of the narrative, and in the case of a reader the subjective experience and the psychological predispositions of a reader, within a larger cultural frame, that encompasses the story and the reader. The core of resonance lies in the emotional impact of fiction. Fictional narratives do not merely convey passive information. They involve the readers at an emotional level leading to the experience of a wide range of feelings. Reading a fiction, therefore, is not a process of simple passive reception; rather the reader actively involves in the process by actively engaging, interpreting and connecting with the narrative. Empathy, the ability to understand and share another's feelings, is essential for building emotional connections in fiction. The readers, therefore, engage in mental simulation, resonating themselves with the character and feeling their emotions and motivations. Theory of Mind in literature refers to the ability of readers to attribute and understand mental states like thoughts, beliefs, intentions, emotions, and desires to characters within a narrative. Readers often involve and connect with characters in stories by interpreting textual cues about the character's thoughts and emotions and the ability to employ Theory of Mind. This process often increases the empathy of the readers. This paper explores the role Theory of Mind plays in establishing resonance in Interactive digital climate fiction, by studying how linguistic cues and images in an Interactive Fiction evoke readers to infer the mental states of characters enhancing emotional engagement and empathy. The study employs a mixed-method approach, using Theory of Narrative Empathy as the theoretical framework. The study includes a pre-test and post-test assessment adapted from the Interpersonal Reactivity Index to measure changes in empathy levels and open-ended questionnaires elicit participants' reflections on resonant moments, before and after engaging with the interactive fiction “The Bitter Sea”. This study will combine both quantitative and qualitative methods, using paired statistical tests to assess changes in empathy scores and thematic analysis to identify moments of emotional resonance linked to Theory of Mind inferences about characters' thoughts and emotions. The results are then cross-referenced with Interpersonal Reactivity Index scores to determine whether engaging Theory of Mind strengthens emotional connections with characters and their stories. The hypothesis of the study is that readers will show a significant increase in empathy levels after engaging with the story, as measured by the Interpersonal Reactivity Index. This research examines how interactive digital fiction can enhance empathy and emotional engagement, offering contributions to narrative studies and digital humanities.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».