Arbeitspapier

Dynamic topic modelling for cryptocurrency community forums

Cryptocurrencies are more and more used in official cash ows and exchange of goods. Bitcoin and the underlying blockchain technology have been looked at by big companies that are adopting and investing in this technology. The CRIX Index of cryptocurrencies hu.berlin/CRIX indicates a wider acceptance of cryptos. One reason for its prosperity certainly being a security aspect, since the underlying network of cryptos is decentralized. It is also unregulated and highly volatile, making the risk assessment at any given moment difficult. In message boards one nds a huge source of information in the form of unstructured text written by e.g. Bitcoin developers and investors. We collect from a popular crypto currency message board texts, user information and associated time stamps. We then provide an indicator for fraudulent schemes. This indicator is constructed using dynamic topic modelling, text mining and unsupervised machine learning. We study how opinions and the evolution of topics are connected with big events in the cryptocurrency universe. Furthermore, the predictive power of these techniques are investigated, comparing the results to known events in the cryptocurrency space. We also test hypothesis of self-fulling prophecies and herding behaviour using the results.

Sprache
Englisch

Erschienen in
Series: SFB 649 Discussion Paper ; No. 2016-051

Klassifikation
Wirtschaft
Econometric and Statistical Methods: Other
General Financial Markets: General (includes Measurement and Data)
Thema
Dynamic Topic Modelling
Cryptocurrencies
Financial Risk

Ereignis
Geistige Schöpfung
(wer)
Linton, Marco
Teo, Ernie Gin Swee
Bommes, Elisabeth
Chen, Cathy Yi-Hsuan
Härdle, Wolfgang Karl
Ereignis
Veröffentlichung
(wer)
Humboldt University of Berlin, Collaborative Research Center 649 - Economic Risk
(wo)
Berlin
(wann)
2016

Handle
Letzte Aktualisierung
10.03.2025, 11:42 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Arbeitspapier

Beteiligte

  • Linton, Marco
  • Teo, Ernie Gin Swee
  • Bommes, Elisabeth
  • Chen, Cathy Yi-Hsuan
  • Härdle, Wolfgang Karl
  • Humboldt University of Berlin, Collaborative Research Center 649 - Economic Risk

Entstanden

  • 2016

Ähnliche Objekte (12)