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  3. One day in 2008 an anonymous Twitter user posted a message: "I am certainly not bored, way busy! feel great!" That is all well a

One day in 2008 an anonymous Twitter user posted a message: "I am certainly not bored, way busy! feel great!" That is all well a

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问题     One day in 2008 an anonymous Twitter user posted a message: "I am certainly not bored, way busy! feel great!" That is all well and good, one might think, but utterly uninteresting to anyone besides the author and, perhaps, a few friends. Not so, according to Johan Bollen, of Indiana University Bloomington, who collected the tweet, along with plenty of others sent that day. All were rated for emotional content. Many proved similarly chirpy, scoring high on confidence, energy and happiness. Indeed, Dr Bollen reckons, on the day the tweet was posted, America’s collective mood perked up a notch. When he and his team examined all the data for the autumn and winter of 2008, they found that Twitter users’ collective mood swings coincided with national events. Happiness shot up around Thanksgiving, for example.
    The idea of tapping web-based data to build a real-time measure of users’ emotions and preferences is not new. Nor is that of using the results to predict their behaviour. Interest in internet forecasting was sparked by a paper published in 2009 by Hal Varian, Google’s chief economist. He found that the peaks and troughs in the volume of Google searches for certain products, such as cars and holidays, preceded fluctuations, in sales of those products. Other researchers have shown that searches for job-related terms are a good predictor of unemployment rates and that mentions of political candidates on Twitter correlate with electoral outcomes.
    Dr Bollen spotted another curious correlation. When he compared trends in the national mood with movements of the Dow Jones Industrial Average(DJIA)he noticed that changes in one of the mood measure’s seven components, anxiety, predicted swings in the share-price index. Spikes in anxiety levels were followed, around three days later, by dips in the price of shares. Why this happens remains unclear, but one possible explanation is that the falling prices were caused by traders’ tendency to exit risky positions when feeling strung up.
    Dr Bollen’s algorithm, which he described in a paper published in February in the Journal of Computational Science, has been licensed to Derwent Capital Markets, a hedge fund based in London. Derwent will use it to help guide the investments made with a ￡25m($41m)fund that the firm hopes to launch in the next few months. Other funds are rumoured to be using similar tricks already.
    All such initiatives face a problem, though. Humans excel at extracting meaning and sentiment from even the tiniest snippets of text, a task that stumps machines. To a computer, a tweet that reads "Feeling joyful after my trip to the dentist. Yeah, really" says that the author has been to the dentist and is now happy. Researchers have recently made strides in teaching machines to recognise such sarcasm, as well as double meanings or cultural references.
Share-price goes down probably because of______.
选项 A、the hedge funds’ tricks having been revealed
B、people’s concern about political election
C、experts’prediction of swings in the index
D、people’s tendency to retreat investment when anxious
答案D
解析 属信息推断题。通过题干可定位至第三段最后一句，股票价格下降的一个可能原因便是投资者在感到焦虑时就倾向于撤资，选项D符合题意。选项A和选项B均出现在文章其他位置，与题目无关，故排除。选项D犯了偷梁换柱的错误，利用与原文相像的词语来设置干扰，但里面的experts文中并未提及，故错误。
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