Towards a Conflict Heuristic. Detecting Conflict in Literary Texts By Adapting Word Embedding Based Sentiment Analysis

Name: Towards a Conflict Heuristic. Detecting Conflict in Literary Texts By Adapting Word Embedding Based Sentiment Analysis
Keywords: Paper, and methods, Conflict, annotation structures, Word Embedding Models, cultural analytics, Short Presentation, Literary studies, text mining and analysis, Humanities computing

Häußler, Julian; Gius, Evelyn

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Article . 2023

License: CC BY

Data sources: Datacite

ZENODO

Article . 2023

License: CC BY

Data sources: Datacite

DBLP

Conference object

Data sources: DBLP

Towards a Conflict Heuristic. Detecting Conflict in Literary Texts By Adapting Word Embedding Based Sentiment Analysis

descriptionPublicationkeyboard_double_arrow_right Article , Conference object 30 Jun 2023 English Publisher:Zenodo

Authors: Häußler, Julian; Gius, Evelyn;

doi: 10.5281/zenodo.8108038 , 10.5281/zenodo.8108037

Towards a Conflict Heuristic. Detecting Conflict in Literary Texts By Adapting Word Embedding Based Sentiment Analysis

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Abstract

To detect conflicts in literary texts, this short paper adapts word embedding based sentiment analysis for assigning conflict values to texts. This heuristic approach is able to output relevant verb phrases of a corpus of German novels from the Romantic period and indicate first trends in the corpus.

Related Organizations

Technische Universität Darmstradt
Germany
TU Darmstadt
Germany

Keywords

Paper, and methods, Conflict, annotation structures, Word Embedding Models, cultural analytics, Short Presentation, Literary studies, text mining and analysis, Humanities computing, Sentiment Analysis, systems, Romantic Literature, natural language processing

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