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Analysis of the Impact of Work on the Emotional State of a Person Based on Data from Social Networks

Student: Tefikova Alie

Supervisor: Armen Beklaryan

Faculty: Graduate School of Business

Educational Programme: Business Informatics (Master)

Year of Graduation: 2020

This paper is devoted to the research of whether there is a difference in the influence of different types of professions on the emotional state of a person. At the moment, there are not many scientific studies devoted to this issue. In General, scientific research only confirms the fact that work can actually affect a person's emotional health, but does not consider this relationship in the distribution by profession, which underscores the novelty of this study. The study of the impact of work on the human condition has a lot of practical value. For employers, this is an opportunity to reduce costs caused by the impact of negative impact on employees and build a personalized approach, using data on what level of emotional state is displayed in what position. For applicants, this is an opportunity to make a more informed choice of profession, as well as to enrich their understanding of it and its impact on their personal life. These reasons also confirm the relevance of research on the impact of work on the emotional state of a person. The aim of the study is to determine the emotion of text they post on social network "Twitter" and the presentation of results in distribution in the profession specified in a social network "Vkontakte". To achieve this goal you need to complete the following tasks: 1. Analyze research papers that study the issue 2. To review existing methods and tools 3. Collect, process and analyze data 4. Determine the emotional state of a person and sum up As further research prospects, it is proposed to collect and analyze data on the emotional state of a person not only by profession, but also with the addition of large filters: company, socio-demographic parameters, sphere of work, and so on. Also in the future, based on successfully implemented algorithms for determining the emotion of the text, you can implement a sentiment model for Russian-language texts.

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