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1
A network approach to topic models ...
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Using text analysis to quantify the similarity and evolution of scientific disciplines ...
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3
Impact of lexical and sentiment factors on the popularity of scientific papers ...
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4
Statistical laws in linguistics ...
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5
Extracting information from S-curves of language change ...
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6
On the origin of long-range correlations in texts ...
Abstract: The complexity of human interactions with social and natural phenomena is mirrored in the way we describe our experiences through natural language. In order to retain and convey such a high dimensional information, the statistical properties of our linguistic output has to be highly correlated in time. An example are the robust observations, still largely not understood, of correlations on arbitrary long scales in literary texts. In this paper we explain how long-range correlations flow from highly structured linguistic levels down to the building blocks of a text (words, letters, etc..). By combining calculations and data analysis we show that correlations take form of a bursty sequence of events once we approach the semantically relevant topics of the text. The mechanisms we identify are fairly general and can be equally applied to other hierarchical settings. ... : Full paper (8 pages) and Supporting Information (19 pages) ...
Keyword: Computation and Language cs.CL; Data Analysis, Statistics and Probability physics.data-an; FOS Computer and information sciences; FOS Physical sciences; Physics and Society physics.soc-ph
URL: https://dx.doi.org/10.48550/arxiv.1207.0658
https://arxiv.org/abs/1207.0658
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