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Application of Semantic Networks in Communication Management

Łukasz Radliński

Wrocław University of Science and Technology, Faculty of Management, Wrocław, Poland

e-mail: lukaszradlinski@gmail.com

ORCID: 0000-0002-7366-3847

Keywords:
data, communication, management, semantic networks.

Abstract

received:   27.04.2022
corrected:  10.05.2022
accepted: 16.05.2022

In the post-covid world, communication within companies has become even more important than before. The management and communication crisis that emerged during the pandemic created the need for more effective communication strategies. The article focuses on the framework for creating such strategies based on Natural Language Processing techniques with particular emphasis on semantic networks. The COVID-19 pandemic drew attention to communication in the enterprise, as it was indicated as a key activity. It is of great importance for human mental health, but it is also a key factor in overcoming the crisis in the company. At the same time, many studies have been published that focus on applying the achievements of Natural Language Processing to solve problems that have arisen during and after the pandemic. It is reasonable to try to apply these technological achievements in the field of communication in order to improve the quality and effectiveness of communication, with particular emphasis on companies. Important data in the light of such rapid changes has become a key success factor

Aleksandra Mokrzan

Wrocław University of Science and Technology, Faculty of Management, Wrocław, Poland

e-mail: aleksandra@mokrzan.com

ORCID: 0000-0002-8941-7181

Anna Maria Kamińska

Wrocław University of Science and Technology, Faculty of Management, Wrocław, Poland

e-mail: anna.maria.kaminska@pwr.edu.pl

ORCID: 0000-0002-6638-1155

References

  1. Bochkarev, V. V., & Solovyev, V. D. (2019). Properties of the network of semantic relations in the Russian language based on the RuWordNet data. Journal of Physics: Conference Series, 1391, 012052. https:// iopscience.iop.org/article/10.1088/1742-6596/1391/1/012052/meta

  2. Ryza S., Laserson, U., Owen, S., & Wills, J. (2015). Advanced Analytics with Spark. Patterns for Learning from Data at Scale. O’Reilly Media, Inc. https://learning.oreilly.com/library/view/advanced- -analytics-with/9781491912751/ch01.html#:-:text=First%2C% 20the%20vast,and%20writing%20algorithms

  3. Stal, M. (2014). Practices of Software Architects in Business and Strategy. An Industry Experience Report. In I. Mistrik, R. Bahsoon, R. Kazman, & Y. Zhang (Eds.), Economics-Driven Software Architecture (pp. 129-156). https://www.sciencedirect.com/science/article/pii/B9780124104648000076

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