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  3. Chances are your friends are more popular than you are. It is a basic feature of social networks that has been known about for s

Chances are your friends are more popular than you are. It is a basic feature of social networks that has been known about for s

admin2018-08-10  54
问题     Chances are your friends are more popular than you are. It is a basic feature of social networks that has been known about for some time. Consider both an enthusiastic party hostess with hundreds of acquaintances and an ill-tempered guy, who may have one or two friends. Statistically speaking, the average person is much more likely to know the hostess simply because she has so many more friends. This, in essence, is what is called the "friendship paradox": the friends of any random individual are likely to be more central to the social web than the individual himself.
    Now researchers think this seemingly depressing fact can be made to work as an early warning system to detect outbreaks of contagious diseases. By studying the friends of a randomly selected group of individuals, epidemic disease experts can isolate those people who are more connected to one another and are therefore more likely to catch diseases like the flu early. This could allow health authorities to spot outbreaks weeks in advance of current monitoring methods.
    In a report, Nicholas Christakis from Harvard University and James Fowler from the University of California, San Diego put the friendship paradox to good use. In a trial carried out last autumn, they monitored the spread of flu through students and their friends at Harvard University, and found that their social links were indeed causing them to get infected sooner.
    As this result came after the outbreak, the researchers tried to come up with a real-time measure that could potentially provide an early warning sign of an outbreak as it began to spread. Currently, the conventional methods used to assess an infection lag an outbreak by a week or two. Google’s Flu Trends is at best simultaneous with an outbreak. Dr. Christakis and Dr. Fowler suggest that a compound method might be developed in which the search inquiries of a group of highly connected individuals could be scanned for signs of the flu.
    Although the technique has so far only been demonstrated for the flu and in the social surroundings of a university, the researchers nevertheless think that it could help predict other infectious diseases and do so on a larger scale. Nor should it be difficult to implement. Public-health officials already conduct random sampling, so getting the participants to name a few friends too should not be troublesome. When it comes to infectious diseases, your friends really do say a lot about you.
According to Paragraph 4, Google’s Flu Trends _____.
选项 A、lags an outbreak
B、precedes an outbreak
C、accompanies an outbreak
D、predicts an outbreak
答案C
解析 根据题干可直接定位到第四段。该段称“谷歌的流感动向充其量只能同步报道传染病爆发的”(at best simultaneous with an outbreak)，故C项“伴随爆发同时发生”为答案。
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