Applying Co‐occurrence Text Analysis with ALCESTE to Studies of Impression Management

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Abstract
This paper reviews the potential role of co‐occurrence text analysis using ALCESTE, a computerized text analysis program. Using an illustrative case study from the biometric industry, we demonstrate that this method offers a number of advantageous features, including the provision of visual outputs which are useful for interpreting results, the ability to study longitudinally the effectiveness of impression management at the inter‐organizational level of analysis and the possibility of studying large textual data sets without using predefined dictionaries. Meanwhile, key limitations of the method include its limited versatility, its tedious data‐cleaning process and its ineffectiveness in identifying the centrality or tonality of the discourse. Our overall conclusion is that the introduction and more widespread use of this method in management is timely, particularly for scholars interested in studying narrative fidelity and frame amplification.

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