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Autor
Skuza Michał (Lodz University of Technology), Romanowski Andrzej (Lodz University of Technology)
Tytuł
Sentiment Analysis of Twitter Data within Big Data Distributed Environment for Stock Prediction
Źródło
Annals of Computer Science and Information Systems, 2015, vol. 5, s. 1349-1354, rys.,tab., bibliogr. 16 poz.
Słowa kluczowe
Uczenie maszynowe, Analiza wydźwięku, Analiza danych
Machine learning, Sentiment analysis, Data analysis
Uwagi
summ.
Abstrakt
This paper covers design, implementation and evaluation of a system that may be used to predict future stock prices basing on analysis of data from social media services. The authors took advantage of large datasets available from Twitter micro blogging platform and widely available stock market records. Data was collected during three months and processed for further analysis. Machine learning was employed to conduct sentiment classification of data coming from social networks in order to estimate future stock prices. Calculations were performed in distributed environment according to Map Reduce programming model. Evaluation and discussion of results of predictions for different time intervals and input datasets proved efficiency of chosen approach is discussed here(original abstract)
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Bibliografia
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Cytowane przez
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ISSN
2300-5963
Język
eng
URI / DOI
http://dx.doi.org/10.15439/2015F230
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