Abstract
In the present contribution, the use of distributional semantic models (DSMs) is proposed as a novel approach for the analysis of crisis communication strategies. Temporal Random Indexing (TRI), a specific DSM framework, is employed as computational tool to analyse word meaning change over time. Our resource is represented by the CompWHoB (Computational White House press Briefings) Corpus, a political diachronic corpus collecting the transcripts of the White House Press Briefings from 1993 to 2014. Primary objective of this paper is to demonstrate that TRI can be used in conjunction with Critical Discourse Analysis (CDA) theories as an easily adaptable tool applicable to the analysis of the so-called crisis communication management moments where US administration has to cope with risky and serious scenarios.
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Notes
- 1.
Department of Physics, University of Napoli Federico II.
- 2.
The CompWHoB Corpus is planned to be extended to the end of the Obama second term presidency.
- 3.
Global Terrorism Database—http://www.start.umd.edu/gtd/.
- 4.
Temporal Random Indexing—https://github.com/pippokill/tri.
- 5.
FrameNet Project—https://framenet.icsi.berkeley.edu/fndrupal/.
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Esposito, F., Esposito, E., Basile, P. (2017). White House Under Attack. In: Lauro, N., Amaturo, E., Grassia, M., Aragona, B., Marino, M. (eds) Data Science and Social Research. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Cham. https://doi.org/10.1007/978-3-319-55477-8_16
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