In this paper, we highlight the importance of contextualizing social information, capturing how this information is disseminated in social networks.
These indicators can effectively capture bias in ideologically-charged texts, such as policy documents or political de- bates, which do not try to hide their ...
In this paper, we highlight the importance of contextualizing social information, capturing how this information is disseminated in social networks. We use ...
A graph convolutional network was used to encode social information for the political perspective detection of news media [95] , and a graph convolutional ...
This repository provides a reference implementation of news bias prediction model as described in the paper: Encoding Social Information with Graph ...
Encoding Social Information with Graph Convolutional Networks for Political Perspective Detection in News Media. ACL 2019. paper. Chang Li, Dan Goldwasser ...
Encoding social information with graph convolutional networks forpolitical perspective detection in news media. C Li, D Goldwasser. Proceedings of the 57th ...
In this paper, we explore the use of graph convolutional network techniques for inferring a user's personality traits from their Facebook status updates or ...
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What are graph convolutional networks used for?
A novel approach for detecting fake news campaigns using graph convolutional networks. A method for constructing diffusion trees from tweets and their retweets.
Encoding Social Information with Graph Convolutional Networks forPolitical Perspective Detection in News Media · Conference Paper. January 2019. ·. 139 Reads.