Ilya Redkin

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Development of linguistic technologies and penetration of social media provide powerful possibilities to investigate users' moods and psychological states of people. In this paper we discussed possibility to improve accuracy of stock market indicators predictions by using data about psychological states of Twitter users. For analysis of psychological states(More)
We analyze the possibility of improving the prediction of stock market indicators by adding information about public mood expressed in Twitter posts. To estimate public mood, we analysed frequencies of 175 emotional markers words, emoticons, acronyms and abbreviations in more than two billion tweets collected via Twitter API over a period from 13.02.2013 to(More)
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