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Tools from the machine learning and data mining domain become even more popular in the fields of economics, entrepreneurship, and policy-making. At the same time, the research on small and medium-sized enterprises (SMEs) is getting amplifying importance for governments and policy-makers especially when it comes to support of SME’s digitalization. A good understanding of the current level of digitalization of SMEs by industries is a prerequisite for design and integration of effective national policies. The goal of this paper is to design the architecture of an ML-based AI conceptual framework for assessing SMEs digitalization. We do this from the perspective of customers assuming that their preferences are absorbed in the publicly available (online) data that they generate in social media and community forums. This approach forms a significant contribution of this paper. Furthermore, we define an algorithm for data preparation, and we develop an algorithm based on sentiment analysis, which generates a set of industry-specific digitalization indices, which is another important contribution of this paper.
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