Titlebook: Exploring Textual Data; Ludovic Lebart,André Salem,Lisette Berry Book 1998 Springer Science+Business Media Dordrecht 1998 Processing.Time

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Visualization of Textual Data,e information is so complex, and the possible points of view so numerous, that it is impossible to recommend a single path leading from the problem to a definitive solution. In this chapter we shall rather attempt to recognize different ways of delaying somewhat the moment when the user must necessa

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Longitudinal Partitions, Textual Time Series,authors are grouped into a corpus); socio-economic categories, age categories, educational level (in the case of aggregated open responses). This information can be used to establish a series of relationships (same author, similar or consecutive dates, same type, etc.).

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Textual Discriminant Analysis,analysis. However, data . is more dynamic and interactive than simple data description. It uses multivariate statistics to obtain visualizations or groupings of elements that can be either whole texts or items within texts. It looks for associations and structures as well as interesting summaries.

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Introduction,activity with various names (lexical statistics, quantitative linguistics, etc.) that for the past fifty years has linked statistical methods to text analysis, and multivariate statistics, one of the main currents of modern statistics.

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