Affect as a proxy for literary mood

We propose to use affect as a proxy for mood in literary texts. In this study, we explore the differences in computationally detecting tone versus detecting mood. Methodologically we utilize affective word embeddings to look at the affective distribution in different text segments. We also present a...

Celý popis

Uloženo v:

Podrobná bibliografie
Vydáno v:	Journal of data mining and digital humanities Ročník NLP4DH
Hlavní autoři:	Emily Öhman, Riikka Rossi
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Nicolas Turenne 01.08.2023
Témata:	computer science - computation and language
ISSN:	2416-5999
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Popis
Shrnutí:	We propose to use affect as a proxy for mood in literary texts. In this study, we explore the differences in computationally detecting tone versus detecting mood. Methodologically we utilize affective word embeddings to look at the affective distribution in different text segments. We also present a simple yet efficient and effective method of enhancing emotion lexicons to take both semantic shift and the domain of the text into account producing real-world congruent results closely matching both contemporary and modern qualitative analyses.
ISSN:	2416-5999
DOI:	10.46298/jdmdh.11164