Extending Jensen Shannon Divergence to Compare Multiple Corpora
|Title:||Extending Jensen Shannon Divergence to Compare Multiple Corpora||Authors:||Lu, Jinghui; Henchion, Maeve; MacNamee, Brian||Permanent link:||http://hdl.handle.net/10197/10517||Date:||1-Jan-2017||Online since:||2019-05-20T08:53:52Z||Abstract:||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.||Funding Details:||Teagasc||Type of material:||Conference Publication||Publisher:||CEUR-WS.org||Series/Report no.:||CEUR Workshop Proceedings, Volume 2086, 2018||Keywords:||Machine learning and statistics; Jensen-Shannon divergence measure; Visualisations; Brexit||Language:||en||Status of Item:||Peer reviewed||Is part of:||McAuley, J., McKeever, S. (eds.). Proceedings of the 25th Irish Conference on Artificial Intelligence and Cognitive Science||Conference Details:||25th Irish Conference on Artificial Intelligence and Cognitive Science, Dublin, Ireland, 7 - 8 December 2017|
|Appears in Collections:||Insight Research Collection|
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