This article examines the reliability of statistical models that use visualization of word distances using computer-assisted text analysis. This study looks at the choice of parameters in the COOA - software for word co-occurrence analysis. The word co-occurrence analysis enables visualization of text structure through the exploration of the number of co-occurrences of words. The data visualization provided by a multi-dimensional scaling (MDS) procedure is susceptible to a particular form of error. The nonlinear relationship between words with significantly different frequencies lies at the root of this problem where words with higher frequencies are placed in the middle of a two-dimensional MDS map visualization. Words with lower frequency, on the other hand, are forced by the MDS estimator to the edge of the two-dimensional map and their estimated spatial positions are unstable. These two processes are potentially a major source of error in making inferences. One solution for reducing this source of error is to (a) reduce the number of words in a model or (b) increase of the number of model dimensions. This article, however, suggests that a detailed investigation of the word structure and a thorough analysis of the error sources and their meaningful interpretation may be a better solution., Václav Čepelák., and Obsahuje bibliografii
This article presents a method for computer-assisted text analysis, which has been employed by the author in a number of studies. The inductive methodology is based on a frequency count analysis of the co-occurrence of words; and a visualization of the results of this text analysis in a two dimensional space. The main advantage of this text analysis technique is its potential for (a) exploring large amounts of textual data without any pre-coded or theoretically laden vocabularies or thesauri; and (b) the extraction of discursive patterns often only detectable in an a posteriori expert analysis. An example is used to demonstrate the use of this computer assisted text analysis method through an analysis of the transcripts of biographical interviews exploring life in Czech socialist society. The analysis presented uncovers both shared and distinctive discursive patterns found in the narratives of the interviewees who come from two distinct social groups., Martin Hájek., and Obsahuje bibliografii a bibliografické odkazy