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Found 58 papers, 6 papers with code
The Emotion Dynamics of Literary Novels
The emotional journeys of the various characters within a story are central to their appeal.
Improving Automatic Quotation Attribution in Literary Novels
Current models for quotation attribution in literary novels assume varying levels of available information in their training and test data, which poses a challenge for in-the-wild inference.
The Project Dialogism Novel Corpus: A Dataset for Quotation Attribution in Literary Texts
We present the Project Dialogism Novel Corpus, or PDNC, an annotated dataset of quotations for English literary texts.
Knowledge Graphs meet Moral Values
Operationalizing morality is crucial for understanding multiple aspects of society that have moral values at their core {--} such as riots, mobilizing movements, public debates, etc.
Contextualized moral inference
Our methodology builds on recent work in contextualized language models and textual inference of moral sentiment.
Text-based inference of moral sentiment change
We present a text-based framework for investigating moral sentiment change of the public via longitudinal corpora.
Understanding Undesirable Word Embedding Associations
Word embeddings are often criticized for capturing undesirable word associations such as gender stereotypes.
Can Character Embeddings Improve Cause-of-Death Classification for Verbal Autopsy Narratives?
We present two models for combining word and character embeddings for cause-of-death classification of verbal autopsy reports using the text of the narratives.
Are Fictional Voices Distinguishable? Classifying Character Voices in Modern Drama
According to the literary theory of Mikhail Bakhtin, a dialogic novel is one in which characters speak in their own distinct voices, rather than serving as mouthpieces for their authors.
Using context to identify the language of face-saving
We created a corpus of utterances that attempt to save face from parliamentary debates and use it to automatically analyze the language of reputation defence.
Automated Fact-Checking of Claims in Argumentative Parliamentary Debates
We present an automated approach to distinguish true, false, stretch, and dodge statements in questions and answers in the Canadian Parliament.
Towards Understanding Linear Word Analogies
A surprising property of word vectors is that word analogies can often be solved with vector arithmetic.
Listwise temporal ordering of events in clinical notes
We present metrics for listwise temporal ordering of events in clinical notes, as well as a baseline listwise temporal ranking model that generates a timeline of events that can be used in downstream medical natural language processing tasks.
Multi-task learning for interpretable cause of death classification using key phrase prediction
We introduce a multi-task learning model for cause-of-death classification of verbal autopsy narratives that jointly learns to output interpretable key phrases.
Classifying Frames at the Sentence Level in News Articles
Previous approaches to generic frame classification analyze frames at the document level.
Recognizing Reputation Defence Strategies in Critical Political Exchanges
We propose a new task of automatically detecting reputation defence strategies in the field of computational argumentation.
Cross-Lingual Sentiment Analysis Without (Good) Translation
Current approaches to cross-lingual sentiment analysis try to leverage the wealth of labeled English data using bilingual lexicons, bilingual vector space embeddings, or machine translation systems.
Argumentation Quality Assessment: Theory vs. Practice
Argumentation quality is viewed differently in argumentation theory and in practical assessment approaches.
Labelled network subgraphs reveal stylistic subtleties in written texts
The vast amount of data and increase of computational capacity have allowed the analysis of texts from several perspectives, including the representation of texts as complex networks.
Computational Argumentation Quality Assessment in Natural Language
Research on computational argumentation faces the problem of how to automatically assess the quality of an argument or argumentation.
Authorship attribution via network motifs identification
The goal of this paper is to apply the concept of motifs, recurrent interconnection patterns, in the authorship attribution task.
Two-pass Discourse Segmentation with Pairing and Global Features
Previous attempts at RST-style discourse segmentation typically adopt features centered on a single token to predict whether to insert a boundary before that token.
Computing Lexical Contrast
We then present an automatic and empirical measure of lexical contrast that relies on the contrast hypothesis, corpus statistics, and the structure of a {\it Roget}-like thesaurus.
Measuring Interlanguage: Native Language Identification with L1-influence Metrics
The task of native language (L1) identification suffers from a relative paucity of useful training corpora, and standard within-corpus evaluation is often problematic due to topic bias.
Distributional Measures of Semantic Distance: A Survey
The ability to mimic human notions of semantic distance has widespread applications.
