KOSMOS: Knowledge-graph Oriented Social media and Mainstream media Overview System
Chua Hao Yang, Yong Shan Jie, Boon Kok Chin, Lander Chin, Lynnette Hui, Xian Ng

TL;DR
KOSMOS is a knowledge retrieval system that constructs and visualizes a knowledge graph from social and mainstream media documents to analyze media coverage and public opinion, demonstrated through COVID-19 event analysis.
Contribution
The paper introduces a novel system that integrates event detection, relation extraction, and visualization to analyze media content and public opinion.
Findings
Effective event clustering and representation from media documents
Enhanced knowledge graph with relation triplets and disambiguation
Useful web interface for media analysis and understanding media slant
Abstract
We introduce KOSMOS, a knowledge retrieval system based on the constructed knowledge graph of social media and mainstream media documents. The system first identifies key events from the documents at each time frame through clustering, extracting a document to represent each cluster, then describing the document in terms of 5W1H (Who, What, When, Where, Why, How). The event centric knowledge graph is enhanced by relation triplets and entity disambiguation from the representative document. This knowledge retrieval is supported by a web interface that presents a graph visualisation of related nodes and relevant articles based on a user query. The interface facilitates understanding relationships between events reported in mainstream and social media journalism through the KOSMOS information extraction pipeline, which is valuable to understand media slant and public opinions. Finally, we…
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Taxonomy
TopicsSemantic Web and Ontologies · Complex Network Analysis Techniques · Advanced Graph Neural Networks
