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Found 7 papers, 3 papers with code
Key Point Analysis via Contrastive Learning and Extractive Argument Summarization
Key point analysis is the task of extracting a set of concise and high-level statements from a given collection of arguments, representing the gist of these arguments.
How Will Your Tweet Be Received? Predicting the Sentiment Polarity of Tweet Replies
As a strong baseline, we propose a two-stage DL-based method: first, we create automatically labeled training data by applying a standard sentiment classifier to tweet replies and aggregating its predictions for each original tweet; our rationale is that individual errors made by the classifier are likely to cancel out in the aggregation step.
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Tweet-Reply Sentiment Analysis
on RETWEET
Corpus Query Lingua Franca part II: Ontology
The present paper outlines the projected second part of the Corpus Query Lingua Franca (CQLF) family of standards: CQLF Ontology, which is currently in the process of standardization at the International Standards Organization (ISO), in its Technical Committee 37, Subcommittee 4 (TC37SC4) and its national mirrors.
EmpiriST Corpus 2.0: Adding Manual Normalization, Lemmatization and Semantic Tagging to a German Web and CMC Corpus
The EmpiriST corpus (Bei{\ss}wenger et al., 2016) is a manually tokenized and part-of-speech tagged corpus of approximately 23, 000 tokens of German Web and CMC (computer-mediated communication) data.
A Corpus of German Reddit Exchanges (GeRedE)
GeRedE is a 270 million token German CMC corpus containing approximately 380, 000 submissions and 6, 800, 000 comments posted on Reddit between 2010 and 2018.
EmotiKLUE at IEST 2018: Topic-Informed Classification of Implicit Emotions
EmotiKLUE is a submission to the Implicit Emotion Shared Task.
