Predicting companies stock price direction by using sentiment analysis of news articles
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Published version
Date
2019-07-19
DOI
Authors
Vodenska, Irena
Dodevska, Lodi
Petreski, Victor
Mishev, Kostadin
Gjorgjevikj, Ana
Chitkushev, Lou
Trajanov, Dimitar
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Published version
OA Version
Citation
Irena Vodenska, Lodi Dodevska, Victor Petreski, Kostadin Mishev, Ana Gjorgjevikj, Lou Chitkushev, Dimitar Trajanov. 2019. "Predicting companies stock price direction by using sentiment analysis of news articles." Computer Science and Education in Computer Science, Volume 1, Issue 1, pp. 37 - 42.
Abstract
This paper summarizes our experience teaching
several courses at Metropolitan College of Boston University Computer Science department over five years. A number of innovative teaching techniques are presented in this paper. We
specifically address the role of a project archive, when designing a course. This research paper explores survey results from every running of courses, from 2014 to 2019. During each class, students participated in two distinct surveys: first, dealing with key learning outcomes, and, second, with teaching techniques used. This paper makes several practical recommendations based on the analysis of collected data. The research validates the value of a sound repository of technical term projects and the role such repository plays in effective teaching and learning of computer science courses.
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Copyright New Bulgarian University, University of Applied Sciences Fulda, and Boston University Metropolitan College
Copyright New Bulgarian University, University of Applied Sciences Fulda, and Boston University Metropolitan College