博伦教授认为,从互联网上研究整体的社会情绪状态确实有价值。但追踪人们在社交媒体论坛上就某家公司发表的看法不那么有用。他解释道:“仅仅因为信息相关,并不代表信息具有预测性。
His study “Twitter Mood Predicts the Market set out to categorise the mood of tweets through text analysis. The results, published in the Journal of Computational Science in 2011, revealed that a change in calmness online is manifested in market movements, with a strong predictive correlation with the rise and fall of the Dow Jones Industrial Average index.
他的研究以“用Twitter情绪预测市场为标题,尝试通过文本分析对微博帖子的情绪进行分类。研究结果在2011年发表于《计算科学杂志》(Journal of Computational Science)。其结果揭示出,网络平静状态的变化反映在市场变动中,与道琼斯工业平均指数(Dow Jones Industrial Average)涨跌具有强烈的预测相关性。
Despite his doubts about social media stock picking, Prof Bollen believes broader internet mood analysis could lead to something big, and likens the pursuit to the Californian gold rush. He has set up a venture called Guidewave in an at-tempt to strike gold. “We’re looking for hidden societal undercurrents, he says.
尽管他质疑通过社交媒体选择股票的方法,但博伦教授认为,整体的互联网情绪分析能产生重大收获,就像当年加州淘金热一样。他建立了一家Guidewave的企业,试图发现“金矿。他说:“我们在寻找隐藏的社会潜流。
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