8 citations · 11 across the 4 of their papers we have counts for
6 papers · 1 filter
Computational analyses of the topics, sentiments, literariness, creativity and beauty of texts in a large Corpus of English Literature
Arthur M. Jacobs, Annette Kinder
The Gutenberg Literary English Corpus (GLEC, Jacobs, 2018a) provides a rich source of textual data for research in digital humanities, computational linguistics or neurocognitive p…
Electoral Programs of German Parties 2021: A Computational Analysis Of Their Comprehensibility and Likeability Based On SentiArt
Arthur M. Jacobs, Annette Kinder
The electoral programs of six German parties issued before the parliamentary elections of 2021 are analyzed using state-of-the-art computational tools for quantitative narrative, t…
Is Einstein more agreeable and less neurotic than Hitler? A computational exploration of the emotional and personality profiles of historical persons
Arthur M. Jacobs, Annette Kinder
Recent progress in distributed semantic models (DSM) offers new ways to estimate personality traits of both fictive and real people. In this exploratory study we applied an extende…
Quasi Error-free Text Classification and Authorship Recognition in a large Corpus of English Literature based on a Novel Feature Set
Arthur M. Jacobs, Annette Kinder
The Gutenberg Literary English Corpus (GLEC) provides a rich source of textual data for research in digital humanities, computational linguistics or neurocognitive poetics. However…
Features of word similarity
Arthur M. Jacobs, Annette Kinder
In this theoretical note we compare different types of computational models of word similarity and association in their ability to predict a set of about 900 rating data. Using reg…
Explorations in an English Poetry Corpus: A Neurocognitive Poetics Perspective
Arthur M. Jacobs
This paper describes a corpus of about 3000 English literary texts with about 250 million words extracted from the Gutenberg project that span a range of genres from both fiction a…