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Abstract
In this paper, the perception of COVID-19 situation amongst coaching, mentoring, and supervision practitioners is analyzed based on the survey conducted by European Mentoring Coaching Council (EMCC Global) with the participation of (476) people from various countries. Based on the data obtained, ‘word cluster analysis-emotional text mining’ and ‘correlation analysis’ are performed. The major empirical findings are summarized as follows: firstly, correlations are calculated among the most repetitive words in the statements of participants by using the Euclidian distance approach. In this respect, participants describe COVID-19 related feelings with the most frequent words they use as coaching, work, anxiety, clients, working, fear, time, business, home, and stress respectively. This indicates that COVID-19 epidemic related issues leads participants to think about their clients. They have the most common feelings of anxiety, stress, and fear at work, business and home. They are sensitive about the time as well. Secondly, cluster dendrogram is applied and this indicates that there are five major categories defined with strong correlation between them such that: coaching, work, anxiety, change, issues, crisis, will, managing, new, people, management, client, working, fear, uncertainty, future, time, stress, business, home. In conclusion, policy recommendations are made regarding the pandemic period all over the world in order to contribute relevant literature based on the empirical findings of EMCC Global’s survey.
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EMCC Global supports this academic work and gives permission to use the survey data. In this respect, the authors are grateful for EMCC Global for sharing this valuable multinational survey data to understand the perception of participants against epidemic.
The Euclidean distance is computed based on Euclidean algorithm. The brief explanation of this algorithm is as follows: Euclidean distance can be computed from the center of the source unit to the center of each of the surrounding units. In this way, the True Euclidean distance is achieved at the end. For instance, for each unit, the distance to each source unit is calculated by computing the hypotenuse with x_max and y_max as the other two legs of the triangle. This calculation is necessary to obtain the true Euclidean distance, rather than the unit distance.