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Found 38 papers, 15 papers with code
GGPONC 2.0 - The German Clinical Guideline Corpus for Oncology: Curation Workflow, Annotation Policy, Baseline NER Taggers
Despite remarkable advances in the development of language resources over the recent years, there is still a shortage of annotated, publicly available corpora covering (German) medical language.
“Beste Grüße, Maria Meyer” — Pseudonymization of Privacy-Sensitive Information in Emails
The exploding amount of user-generated content has spurred NLP research to deal with documents from various digital communication formats (tweets, chats, emails, etc.).
Emotion Embeddings $\unicode{x2014}$ Learning Stable and Homogeneous Abstractions from Heterogeneous Affective Datasets
Human emotion is expressed in many communication modalities and media formats and so their computational study is equally diversified into natural language processing, audio signal analysis, computer vision, etc.
EmoBank: Studying the Impact of Annotation Perspective and Representation Format on Dimensional Emotion Analysis
We describe EmoBank, a corpus of 10k English sentences balancing multiple genres, which we annotated with dimensional emotion metadata in the Valence-Arousal-Dominance (VAD) representation format.
Acquiring a Formality-Informed Lexical Resource for Style Analysis
To track different levels of formality in written discourse, we introduce a novel type of lexicon for the German language, with entries ordered by their degree of (in)formality.
Towards Label-Agnostic Emotion Embeddings
Research in emotion analysis is scattered across different label formats (e. g., polarity types, basic emotion categories, and affective dimensions), linguistic levels (word vs. sentence vs. discourse), and, of course, (few well-resourced but much more under-resourced) natural languages and text genres (e. g., product reviews, tweets, news).
GGPONC: A Corpus of German Medical Text with Rich Metadata Based on Clinical Practice Guidelines
The lack of publicly accessible text corpora is a major obstacle for progress in natural language processing.
What Makes a Top-Performing Precision Medicine Search Engine? Tracing Main System Features in a Systematic Way
From 2017 to 2019 the Text REtrieval Conference (TREC) held a challenge task on precision medicine using documents from medical publications (PubMed) and clinical trials.
Learning and Evaluating Emotion Lexicons for 91 Languages
Emotion lexicons describe the affective meaning of words and thus constitute a centerpiece for advanced sentiment and emotion analysis.
Allgemeine Musikalische Zeitung as a Searchable Online Corpus
The massive digitization efforts related to historical newspapers over the past decades have focused on mass media sources and ordinary people as their primary recipients.
CodE Alltag 2.0 --- A Pseudonymized German-Language Email Corpus
The vast amount of social communication distributed over various electronic media channels (tweets, blogs, emails, etc.
ProGene - A Large-scale, High-Quality Protein-Gene Annotated Benchmark Corpus
Genes and proteins constitute the fundamental entities of molecular genetics.
A Time Series Analysis of Emotional Loading in Central Bank Statements
We examine the affective content of central bank press statements using emotion analysis.
De-Identification of Emails: Pseudonymizing Privacy-Sensitive Data in a German Email Corpus
We deal with the pseudonymization of those stretches of text in emails that might allow to identify real individual persons.
Continuous Quality Control and Advanced Text Segment Annotation with WAT-SL 2.0
Today{'}s widely used annotation tools were designed for annotating typically short textual mentions of entities or relations, making their interface cumbersome to use for long(er) stretches of text, e. g, sentences running over several lines in a document.
At the Lower End of Language---Exploring the Vulgar and Obscene Side of German
In this paper, we describe a workflow for the data-driven acquisition and semantic scaling of a lexicon that covers lexical items from the lower end of the German language register{---}terms typically considered as rough, vulgar or obscene.
The Influence of Down-Sampling Strategies on SVD Word Embedding Stability
The stability of word embedding algorithms, i. e., the consistency of the word representations they reveal when trained repeatedly on the same data set, has recently raised concerns.
JeSemE: Interleaving Semantics and Emotions in a Web Service for the Exploration of Language Change Phenomena
We here introduce a substantially extended version of JeSemE, an interactive website for visually exploring computationally derived time-variant information on word meanings and lexical emotions assembled from five large diachronic text corpora.
JeSemE: A Website for Exploring Diachronic Changes in Word Meaning and Emotion
We here introduce a substantially extended version of JeSemE, an interactive website for visually exploring computationally derived time-variant information on word meanings and lexical emotions assembled from five large diachronic text corpora.
Representation Mapping: A Novel Approach to Generate High-Quality Multi-Lingual Emotion Lexicons
In the past years, sentiment analysis has increasingly shifted attention to representational frameworks more expressive than semantic polarity (being positive, negative or neutral).
A Corpus of Corporate Annual and Social Responsibility Reports: 280 Million Tokens of Balanced Organizational Writing
We introduce JOCo, a novel text corpus for NLP analytics in the field of economics, business and management.
Emotion Representation Mapping for Automatic Lexicon Construction (Mostly) Performs on Human Level
Emotion Representation Mapping (ERM) has the goal to convert existing emotion ratings from one representation format into another one, e. g., mapping Valence-Arousal-Dominance annotations for words or sentences into Ekman's Basic Emotions and vice versa.
Modeling Word Emotion in Historical Language: Quantity Beats Supposed Stability in Seed Word Selection
To understand historical texts, we must be aware that language -- including the emotional connotation attached to words -- changes over time.
Word Emotion Induction for Multiple Languages as a Deep Multi-Task Learning Problem
Predicting the emotional value of lexical items is a well-known problem in sentiment analysis.
Readers vs. Writers vs. Texts: Coping with Different Perspectives of Text Understanding in Emotion Annotation
We here examine how different perspectives of understanding written discourse, like the reader{'}s, the writer{'}s or the text{'}s point of view, affect the quality of emotion annotations.
Bad Company---Neighborhoods in Neural Embedding Spaces Considered Harmful
We assess the reliability and accuracy of (neural) word embeddings for both modern and historical English and German.
Feelings from the Past---Adapting Affective Lexicons for Historical Emotion Analysis
We here describe a novel methodology for measuring affective language in historical text by expanding an affective lexicon and jointly adapting it to prior language stages.
UIMA-Based JCoRe 2.0 Goes GitHub and Maven Central ― State-of-the-Art Software Resource Engineering and Distribution of NLP Pipelines
We introduce JCoRe 2. 0, the relaunch of a UIMA-based open software repository for full-scale natural language processing originating from the Jena University Language {\&} Information Engineering (JULIE) Lab.
CodE Alltag: A German-Language E-Mail Corpus
We introduce CODE ALLTAG, a text corpus composed of German-language e-mails.
Collaboratively Annotating Multilingual Parallel Corpora in the Biomedical Domain---some MANTRAs
The coverage of multilingual biomedical resources is high for the English language, yet sparse for non-English languages―an observation which holds for seemingly well-resourced, yet still dramatically low-resourced ones such as Spanish, French or German but even more so for really under-resourced ones such as Dutch.
Disclose Models, Hide the Data - How to Make Use of Confidential Corpora without Seeing Sensitive Raw Data
Confidential corpora from the medical, enterprise, security or intelligence domains often contain sensitive raw data which lead to severe restrictions as far as the public accessibility and distribution of such language resources are concerned.
CALBC: Releasing the Final Corpora
These usually lead to implementation of trained solutions (1) for a limited number of semantic entity types and (2) lacking in generalization capability.
Iterative Refinement and Quality Checking of Annotation Guidelines --- How to Deal Effectively with Semantically Sloppy Named Entity Types, such as Pathological Phenomena
We here discuss a methodology for dealing with the annotation of semantically hard to delineate, i. e., sloppy, named entity types.
