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


  • The authors are grateful for the cooperation and financial support provided for the field study by the Swiss National Science Foundation. Comments by Candace Jones, Magdalena Wojcieszak, Joep Cornelissen, Craig Carroll, Stelios Zyglidopoulos, Johan van Rekom, Nicole Kronberger, Aude Bicquelet and Kevin Corley to earlier drafts were helpful for revising the paper. A final thanks goes also to the reviewers from the Academy of Management Conference, EGOS Colloquium and participants at the research seminars at Brunel Business School and London School of Economics and Political Science whose comments were very constructive and helpful in shaping this paper.


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.