  Non-Fungible Token (NFT) is evolving with the rise of the cryptocurrency
market and the development of blockchain techniques, which leads to an emerging
NFT market that has become prosperous rapidly then followed by a cooldown.
Nevertheless, the overall rise procedure of the NFT market has not been well
understood. To this end, we consider that social media communities evolving
alongside the market growth, are worth exploring and reasoning about, as the
mineable information might unveil the market behaviors. We explore the
procedure from the perspective of NFT Twitter communities and its impact on the
NFT price moves with two experiments. We perform a Granger causality test on
the number of tweets and the NFT price time series and find that the number of
tweets has a positive impact on (Granger-causes) the price or reversely for
larger part of the 19 top authentic projects but seldom copycat projects.
Besides, to investigate the price moves predictability, we experiment on
predicting Markov normalized NFT price (representing the direction and
magnitude of price moves) given tweets-extracted word features and interpret
the feature importance to find insights. Our results show that social media
words as the predictors result in all 19 top projects having a testing accuracy
evidently above the baseline. Based on the feature importance analysis, we find
that both general market-related words and NFT event-related words have a
markedly positive contribution in predicting price moves. We summarize the
characteristics including categorization and sentiment for the words with the
top and least feature importance.
