When Bitcoin encounters information in an online forum: Using text mining to analyse user opinions and predict value fluctuation
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| Udgivet i: | PLoS One vol. 12, no. 5 (May 2017), p. e0177630 |
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| Andre forfattere: | , , , , |
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Public Library of Science
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| Online adgang: | Citation/Abstract Full Text Full Text - PDF |
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| 024 | 7 | |a 10.1371/journal.pone.0177630 |2 doi | |
| 035 | |a 1898439241 | ||
| 045 | 2 | |b d20170501 |b d20170531 | |
| 084 | |a 174835 |2 nlm | ||
| 100 | 1 | |a Young Bin Kim | |
| 245 | 1 | |a When Bitcoin encounters information in an online forum: Using text mining to analyse user opinions and predict value fluctuation | |
| 260 | |b Public Library of Science |c May 2017 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a Bitcoin is an online currency that is used worldwide to make online payments. It has consequently become an investment vehicle in itself and is traded in a way similar to other open currencies. The ability to predict the price fluctuation of Bitcoin would therefore facilitate future investment and payment decisions. In order to predict the price fluctuation of Bitcoin, we analyse the comments posted in the Bitcoin online forum. Unlike most research on Bitcoin-related online forums, which is limited to simple sentiment analysis and does not pay sufficient attention to note-worthy user comments, our approach involved extracting keywords from Bitcoin-related user comments posted on the online forum with the aim of analytically predicting the price and extent of transaction fluctuation of the currency. The effectiveness of the proposed method is validated based on Bitcoin online forum data ranging over a period of 2.8 years from December 2013 to September 2016. | |
| 610 | 4 | |a Korea University | |
| 653 | |a Economic | ||
| 653 | |a Accessibility | ||
| 653 | |a Internet | ||
| 653 | |a Computer science | ||
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| 653 | |a Deception | ||
| 653 | |a Bulletin boards | ||
| 653 | |a Communities | ||
| 653 | |a Keywords | ||
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| 653 | |a Washing | ||
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| 653 | |a Currency | ||
| 653 | |a Big Data | ||
| 653 | |a Social networks | ||
| 653 | |a Digital currencies | ||
| 653 | |a Sentiment analysis | ||
| 653 | |a User behavior | ||
| 653 | |a Data mining | ||
| 700 | 1 | |a Lee, Jurim | |
| 700 | 1 | |a Park, Nuri | |
| 700 | 1 | |a Choo, Jaegul | |
| 700 | 1 | |a Jong-Hyun, Kim | |
| 700 | 1 | |a Kim, Chang Hun | |
| 773 | 0 | |t PLoS One |g vol. 12, no. 5 (May 2017), p. e0177630 | |
| 786 | 0 | |d ProQuest |t Health & Medical Collection | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/1898439241/abstract/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text |u https://www.proquest.com/docview/1898439241/fulltext/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/1898439241/fulltextPDF/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |