  This paper analyzes correlations and causalities between Bitcoin market
indicators and Twitter posts containing emotional signals on Bitcoin. Within a
timeframe of 104 days (November 23rd 2013 - March 7th 2014), about 160,000
Twitter posts containing "bitcoin" and a positive, negative or uncertainty
related term were collected and further analyzed. For instance, the terms
"happy", "love", "fun", "good", "bad", "sad" and "unhappy" represent positive
and negative emotional signals, while "hope", "fear" and "worry" are considered
as indicators of uncertainty. The static (daily) Pearson correlation results
show a significant positive correlation between emotional tweets and the close
price, trading volume and intraday price spread of Bitcoin. However, a dynamic
Granger causality analysis does not confirm a statistically significant effect
of emotional Tweets on Bitcoin market values. To the contrary, the analyzed
data shows that a higher Bitcoin trading volume Granger causes more signals of
uncertainty within a 24 to 72-hour timeframe. This result leads to the
interpretation that emotional sentiments rather mirror the market than that
they make it predictable. Finally, the conclusion of this paper is that the
microblogging platform Twitter is Bitcoin's virtual trading floor, emotionally
reflecting its trading dynamics.

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