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Found 10 papers, 10 papers with code
GisPy: A Tool for Measuring Gist Inference Score in Text
Decision making theories such as Fuzzy-Trace Theory (FTT) suggest that individuals tend to rely on gist, or bottom-line meaning, in the text when making decisions.
Knowledge-Augmented Language Models for Cause-Effect Relation Classification
Previous studies have shown the efficacy of knowledge augmentation methods in pretrained language models.
Predicting Directionality in Causal Relations in Text
In this work, we test the performance of two bidirectional transformer-based language models, BERT and SpanBERT, on predicting directionality in causal pairs in the textual content.
ParsiNLU: A Suite of Language Understanding Challenges for Persian
Despite the progress made in recent years in addressing natural language understanding (NLU) challenges, the majority of this progress remains to be concentrated on resource-rich languages like English.
A Multi-Modal Method for Satire Detection using Textual and Visual Cues
Satire is a form of humorous critique, but it is sometimes misinterpreted by readers as legitimate news, which can lead to harmful consequences.
Content analysis of Persian/Farsi Tweets during COVID-19 pandemic in Iran using NLP
Iran, along with China, South Korea, and Italy was among the countries that were hit hard in the first wave of the COVID-19 spread.
LexiPers: An ontology based sentiment lexicon for Persian
The results show an acceptable performance in terms of accuracy and F-measure in the generated sentiment lexicon.
Identifying Nuances in Fake News vs. Satire: Using Semantic and Linguistic Cues
As avenues for future work, we consider studying additional linguistic features related to the humor aspect, and enriching the data with current news events, to help identify a political or social message.
Does Causal Coherence Predict Online Spread of Social Media?
In this paper, we test the hypothesis that causal and semantic coherence are associated with online sharing of misinformative social media content using Coh-Metrix – a widely-used set of psycholinguistic measures.
SentiPers: A Sentiment Analysis Corpus for Persian
To the best of our knowledge, SentiPers is a unique sentiment corpus with such a rich annotation in three different levels including document-level, sentence-level, and entity/aspect-level for Persian.
