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News wrote: ↑Mon May 06, 2019 5:58 amThe volume of tweets and Google Search Volume Index (SVI) were found to be leading price indicators for Bitcoin and Ethereum, according to a research paper published by the Southern Methodist University.
n the paper, researchers gathered data on Twitter mentioning Bitcoin and Ethereum; the same was done using Google trends. Building on the ideas of previous research, the hypothesis was that the number of tweets and their sentiment (positive and negative) can influence prices. In the study, it was uncovered that the number of tweets and Google searches changes first before prices do.
The role of sentiment in technical or market analysis is to uncover people’s attitudes towards an entire market or individual index (in this case Bitcoin and Ethereum). The theory of sentiment analysis is a branch of technical analysis that states that price discounts everything, and that price trends are ultimately a reflection of crowd psychology.
Therefore, in theory, if you could measure how positive or negative the people’s shared views are towards a particular stock or cryptocurrency, you could estimate its price trajectory.
Although in this particular study, tweet volume, and not sentiment, was found to be a leading factor in the price of cryptocurrencies. The lack of sentiment being the leading factor was theorized due to the amount of “noise” there is on Twitter about the currencies compared to actual conversation.
For instance, the researchers found that there 21 million bots on Twitter posting mostly factual information about prices, advertisements, spam etc. Not humans having real discussions about how they feel about either Bitcoin or Ethereum.
The other issue that researchers found with Twitter was that sentiment was mostly positive in nature — even when the prices of Bitcoin and Ethereum were falling.
Despite their findings, the researchers did not completely rule out sentiment analysis using different modeling techniques.People who tweet about cryptocurrencies even when their prices drop have an interest in them beyond investment opportunity making the tweets biased towards positive.