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Artificial Intelligence and Decision Making, 2014, Issue 4, Pages 68–72
(Mi iipr378)
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Data analysis
On application of data mining techniques to research of manifestos of political parties
E. D. Kornilina, A. P. Mikhailov, A. P. Petrov Keldysh Institute of Applied Mathematics of Russian Academy of Sciences, Moscow
Abstract:
The paper presents a new method for determining the proximity of political positions contained in manifestos, i.e. the election programs of political parties, as well as other documents published by the parties to attract voters, which is based on latent semantic analysis. The approach is based on the conjecture that the proximity of political positions reveals itself as syntagmatic proximity of texts of the manifestos. A detailed description of the algorithm is presented, which includes the preprocessing of text, breaking it into fragments, “fragment-word” matrix construction, its normalization, the use of singular value decomposition, and construction of proximity diagrams. Some conclusions obtained from this analysis are briefly outlined.
Keywords:
LSA, political parties’ manifestos, political position, mathematical model.
Citation:
E. D. Kornilina, A. P. Mikhailov, A. P. Petrov, “On application of data mining techniques to research of manifestos of political parties”, Artificial Intelligence and Decision Making, 2014, no. 4, 68–72
Linking options:
https://www.mathnet.ru/eng/iipr378 https://www.mathnet.ru/eng/iipr/y2014/i4/p68
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Abstract page: | 11 | Full-text PDF : | 9 | References: | 1 |
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