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Found 10 papers, 7 papers with code
Inductive detection of Influence Operations via Graph Learning
Influence operations are large-scale efforts to manipulate public opinion.
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.
Applying Word Embeddings to Measure Valence in Information Operations Targeting Journalists in Brazil
Among the goals of information operations are to change the overall information environment vis-\'a-vis specific actors.
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.
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.
The Role of Individual User Differences in Interpretable and Explainable Machine Learning Systems
There is increased interest in assisting non-expert audiences to effectively interact with machine learning (ML) tools and understand the complex output such systems produce.
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.
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.
