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Found 6 papers, 5 papers with code
Sentence-level Media Bias Analysis with Event Relation Graph
Then, we incorporate event relation graph for bias sentences identification in two steps: an event-aware language model is built to inject the events and event relations knowledge into the basic language model via soft labels; further, a relation-aware graph attention network is designed to update sentence embedding with events and event relations information based on hard labels.
EMONA: Event-level Moral Opinions in News Articles
This paper initiates a new task to understand moral opinions towards events in news articles.
Polarity Calibration for Opinion Summarization
To address this issue and make the summarizer express both sides of opinions, we introduce the concept of polarity calibration, which aims to align the polarity of output summary with that of input text.
Identifying Conspiracy Theories News based on Event Relation Graph
Conspiracy theories, as a type of misinformation, are narratives that explains an event or situation in an irrational or malicious manner.
Discourse Structures Guided Fine-grained Propaganda Identification
Hence, we propose to incorporate both local and global discourse structures for propaganda discovery and construct two teacher models for identifying PDTB-style discourse relations between nearby sentences and common discourse roles of sentences in a news article respectively.
Cocktail Edge Caching: Ride Dynamic Trends of Content Popularity with Ensemble Learning
In this paper, we propose Cocktail Edge Caching, that tackles the dynamic popularity and heterogeneity through ensemble learning.
