Reference

1. Sungjoo Ha - Finding attractive technical patterns in cryptocurrency markets
2. Ross C. Phillips & Denise Gorse - Predicting cryptocurrency price bubbles using social media data and epidemic modelling
3. Zhengyao Jiang & Jinjun Liang - Cryptocurrency portfolio management with deep reinforcement learning
4. D. Garcia C. Tessone P. Mavrodiev N. Perony "The digital traces of bubbles: feedback cycles between socio-economic signals in the Bitcoin economy" Journal of The Royal Society Interface vol. 11 no. 99 2014.
5. R. Heimer "Peer Pressure: Social Interaction and the Disposition Effect" Review of Financial Studies vol. 29 no. 11 pp. 3177-3209 2016.
6.  J. Bollen H. Mao X. Zeng "Twitter mood predicts the stock market" Journal of Computational Science vol. 2 no. 1 pp. 1-8 2011.
7.  D. Garcia F. Schweitzer "Social signals and algorithmic trading of Bitcoin" Royal Society Open Science vol. 2 no. 9 2015.
8. S. Abdullah X. Wu "An Epidemic Model for News Spreading on Twitter" 2011 IEEE 23rd International Conference on Tools with Artificial Intelligence 2011.
9. Y. Kim J. Kim W. Kim J. Im T. Kim S. Kang C. Kim "Predicting Fluctuations in Cryptocurrency Transactions Based on User Comments and Replies" PLOS ONE vol. 11 no. 8 2016.
10. AlexanderBrauneis - Price discovery of cryptocurrencies: Bitcoin and beyond
11. AndrewPhillip - A new look at Cryptocurrencies