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  3. Hit songs are big business, so there is an incentive for composers to try to tease out those ingredients that might increase the

Hit songs are big business, so there is an incentive for composers to try to tease out those ingredients that might increase the

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问题    Hit songs are big business, so there is an incentive for composers to try to tease out those ingredients that might increase their chances of success. This, however, is hard. Songs are complex mixtures of features. How to analyze them is not obvious and is made more difficult still by the fact that what is popular changes over time. But Natalia Komarova, a mathematician at the University of California, Irvine, thinks she has cracked the problem. As she writes in Royal Society Open Science this week, her computer analysis suggests that the songs currently preferred by consumers are danceable, party-like numbers. Unfortunately, those actually writing songs prefer something else.
   Dr Komarova and her colleagues collected information on music released in Britain between 1985 and 2015. They looked in public repositories of music "metadata" that are used by music lovers and are often tapped into by academics. They compared what they found in these repositories with what had made it into the charts.
   Metadata are information about the nature of a song that can give listeners an idea of what that song is like before they hear it. The repositories presented Dr Komarova and her team with more than 500, 000 songs that had been tagged by algorithms which had been trained to detect numerous musical features. The tags included a dozen binary variables (dark or bright timbre; can or cannot be danced to; vocal or instrumental; sung by a man or a woman; and so on). The team fed all of this information into a computer and compared the features of songs that had made it into the charts (roughly 4% of those in the repositories) with those of songs that had not.
   Overall, the team’s results suggested that songs tagged as happy and bright have become rarer during the past 30 years; the opposites have therefore appeared with greater frequency. That was not, however, reflected in what made it into the charts. Chart successes were happier and brighter (though also less relaxed), than the average songs released during the same year. Chart toppers were also more likely than average songs to have been performed by women. All this is important information for executives of music companies.
   Dr Komarova used these results to train her computer to try to predict whether a randomly presented song was likely to have been a hit in a given year. The machine correctly predicted success 75% of the time, compared with the 4% rate that guessing success at random from the music database would yield — something else music executives might pay attention to.
   Content is not everything. As might be expected, circumstances — particularly any fame already attaching to a recording artist or artists — had an effect, too. But not a huge one. Adding in information about who was performing a song increased the accuracy of prediction to 85%. That suggests that musical fame is actually attached to talent, rather than to hype. And this, perhaps, is a third lesson for an industry that some believe is not wedded to talent enough.
Content is not everything because______.
选项 A、music companies decide the mainstream culture of songs
B、artists’ interest and high demand of salary influence the charts
C、circumstances, especially any fame already attaching to recording artists had an effect
D、artists’ fame had an extremely huge effect on songs
答案C
解析 该题定位至第6段。题目问内容并非一切的原因是什么。该段二、三句主要讲述了对音乐能否成功也具有影响的因素： “环境——尤其是那些已经依附于唱片艺术家或个人艺术家的名声——也对歌曲产生了影响，但影响不是很大。”第五句还指出“音乐名气实际上是与才华挂钩的，而不是炒作”。选项A、B在文中并未提及，D项夸大了名声的作用，因此答案为C项。
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