Visualization Techniques to Enhance Automated Event Extraction

• URL: http://arxiv.org/abs/2106.06588v1
• Date: Fri, 11 Jun 2021 19:24:54 GMT
• Title: Visualization Techniques to Enhance Automated Event Extraction
• Authors: Sophia Henn, Abigail Sticha, Timothy Burley, Ernesto Verdeja, Paul Brenner
• Abstract summary: This case study seeks to identify potential triggers of state-led mass killings from news articles using NLP. We demonstrate how visualizations can aid in each stage, from exploratory analysis of raw data, to machine learning training analysis, and finally post-inference validation.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Robust visualization of complex data is critical for the effective use of NLP for event classification, as the volume of data is large and the high-dimensional structure of text makes data challenging to summarize succinctly. In event extraction tasks in particular, visualization can aid in understanding and illustrating the textual relationships from which machine learning tools produce insights. Through our case study which seeks to identify potential triggers of state-led mass killings from news articles using NLP, we demonstrate how visualizations can aid in each stage, from exploratory analysis of raw data, to machine learning training analysis, and finally post-inference validation.

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