AbstractThis paper describes early work trying to predict stock market indicators such as Dow Jones, NASDAQ and S&P 500 by analyzing Twitter posts. We collected the twitter feeds for six months and got a randomized subsample of about one hundredth of the full volume of all tweets. We measured collective hope and fear on each day and analyzed the correlation between these indices and the stock market indicators. We found that emotional tweet percentage significantly negatively correlated with Dow Jones, NASDAQ and S&P 500, but displayed significant positive correlation to VIX. It therefore seems that just checking on twitter for emotional outbursts of any kind gives a predictor of how the stock market will be doing the next day
Background: As Twitter has become a global microblogging site, it s influ-ence in the stock market h...
Behavioral finance researchers have shown that the stock market can be driven by emotions of market ...
This paper examines the investor reaction of firm-specific pessimistic sentiment extracted from Twit...
AbstractThis paper describes early work trying to predict stock market indicators such as Dow Jones,...
Different theories state that future market values strongly depend on psychological and financial fa...
[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] The stock markets in the rece...
Social media platforms such as Facebook and Twitter have enormous amounts of data that can be extrac...
Textual data potentially carries information not found in quantitative data but is equally invaluabl...
In this paper we apply sentiment analysis of Twitter data from July through December, 2013 to find c...
This work concentrates on exploring the influence of social networks to financial markets. We have i...
This experiment analyzes “tweets” gathered from Twitter and determines whether the positive or negat...
This study aims to investigate if the sentiment expressed on Twitter has an effect on individual sto...
Emerging interest of trading companies and hedge funds in mining social web has created new avenues ...
We analyze the possibility of improving the prediction of stock market indicators by adding ...
Stock market movements forecast based on sentiment analysis is certainly a field worth investigating...
Background: As Twitter has become a global microblogging site, it s influ-ence in the stock market h...
Behavioral finance researchers have shown that the stock market can be driven by emotions of market ...
This paper examines the investor reaction of firm-specific pessimistic sentiment extracted from Twit...
AbstractThis paper describes early work trying to predict stock market indicators such as Dow Jones,...
Different theories state that future market values strongly depend on psychological and financial fa...
[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] The stock markets in the rece...
Social media platforms such as Facebook and Twitter have enormous amounts of data that can be extrac...
Textual data potentially carries information not found in quantitative data but is equally invaluabl...
In this paper we apply sentiment analysis of Twitter data from July through December, 2013 to find c...
This work concentrates on exploring the influence of social networks to financial markets. We have i...
This experiment analyzes “tweets” gathered from Twitter and determines whether the positive or negat...
This study aims to investigate if the sentiment expressed on Twitter has an effect on individual sto...
Emerging interest of trading companies and hedge funds in mining social web has created new avenues ...
We analyze the possibility of improving the prediction of stock market indicators by adding ...
Stock market movements forecast based on sentiment analysis is certainly a field worth investigating...
Background: As Twitter has become a global microblogging site, it s influ-ence in the stock market h...
Behavioral finance researchers have shown that the stock market can be driven by emotions of market ...
This paper examines the investor reaction of firm-specific pessimistic sentiment extracted from Twit...