Related papers: Using the profile of publishers to predict barriers across news articles

Using the profile of publishers to predict barriers across news articles

URL: http://arxiv.org/abs/2301.05535v1
Date: Fri, 13 Jan 2023 13:32:42 GMT
Title: Using the profile of publishers to predict barriers across news articles
Authors: Abdul Sittar, Dunja Mladenic
Abstract summary: We present an approach to barrier detection in news spreading by utilizing Wikipedia-concepts and metadata associated with each barrier. We believe that our approach can serve to provide useful insights which pave the way for the future development of a system for predicting information spreading barriers over the news.
Score: 0.685316573653194
License: http://creativecommons.org/licenses/by/4.0/
Abstract: Detection of news propagation barriers, being economical, cultural, political, time zonal, or geographical, is still an open research issue. We present an approach to barrier detection in news spreading by utilizing Wikipedia-concepts and metadata associated with each barrier. Solving this problem can not only convey the information about the coverage of an event but it can also show whether an event has been able to cross a specific barrier or not. Experimental results on IPoNews dataset (dataset for information spreading over the news) reveals that simple classification models are able to detect barriers with high accuracy. We believe that our approach can serve to provide useful insights which pave the way for the future development of a system for predicting information spreading barriers over the news.

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