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Extending Jensen Shannon Divergence to Compare Multiple Corpora
Lu, Jinghui; Henchion, Maeve; MacNamee, Brian
25th Irish Conference on Artificial Intelligence and Cognitive Science, Dublin, Ireland, 7 - 8 December 2017 Investigating public discourse on social media platforms has proven a viable way to reflect the impacts of political issues. In this paper we frame this as a corpus comparison problem in which the online discussion of different groups are treated as different corpora to be compared. We propose an extended version of the Jensen-Shannon divergence measure to compare multiple corpora and use the FP-growth algorithm to mix unigrams and bigrams in this comparison. We also propose a set of visualizations that can illustrate the results of this analysis. To demonstrate these approaches we compare the Twitter discourse surrounding Brexit in Ireland and Great Britain across a 14 week time period. Teagasc
Keyword(s): Machine learning and statistics; Jensen-Shannon divergence measure; Visualisations; Brexit
Publication Date:
2019
Type: Other
Peer-Reviewed: Unknown
Language(s): English
Institution: University College Dublin
Publisher(s): CEUR-WS.org
First Indexed: 2019-05-22 06:15:19 Last Updated: 2019-05-22 06:15:19