An Analysis of COVID-19 Knowledge Graph Construction and Applications

• URL: http://arxiv.org/abs/2110.04932v1
• Date: Sun, 10 Oct 2021 23:58:57 GMT
• Title: An Analysis of COVID-19 Knowledge Graph Construction and Applications
• Authors: Dominic Flocco, Bryce Palmer-Toy, Ruixiao Wang, Hongyu Zhu, Rishi Sonthalia, Junyuan Lin, Andrea L. Bertozzi and P. Jeffrey Brantingham
• Abstract summary: We present a knowledge graph constructed from COVID-19 related tweets in the Los Angeles area. We use natural language processing and change point analysis to extract tweet-topic, tweet-date, and event-date relations.
• Score: 7.849573720043142
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: The construction and application of knowledge graphs have seen a rapid increase across many disciplines in recent years. Additionally, the problem of uncovering relationships between developments in the COVID-19 pandemic and social media behavior is of great interest to researchers hoping to curb the spread of the disease. In this paper we present a knowledge graph constructed from COVID-19 related tweets in the Los Angeles area, supplemented with federal and state policy announcements and disease spread statistics. By incorporating dates, topics, and events as entities, we construct a knowledge graph that describes the connections between these useful information. We use natural language processing and change point analysis to extract tweet-topic, tweet-date, and event-date relations. Further analysis on the constructed knowledge graph provides insight into how tweets reflect public sentiments towards COVID-19 related topics and how changes in these sentiments correlate with real-world events.

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