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【英语语言学习】网恋

时间:2016-09-28 05:49来源:互联网 提供网友:yajing   字体: [ ]
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So my name is Amy Webb, and a few years ago I found myself at the end of yet another fantastic relationship that came burning down in a spectacular fashion. And I thought, you know, what's wrong with me? I don't understand why this keeps happening.
 
So I asked everybody in my life what they thought. I turned to my grandmother, who always had plenty of advice, and she said, "Stop being so picky. You've got to date around. And most importantly, true love will find you when you least expect it."
 
Now as it turns out, I'm somebody who thinks a lot about data, as you'll soon find. I am constantly swimming in numbers and formulas and charts. I also have a very tight-knit family, and I'm very, very close with my sister, and as a result, I wanted to have the same type of family when I grew up.
 
So I'm at the end of this bad breakup, I'm 30 years old, I figure I'm probably going to have to date somebody for about six months before I'm ready to get monogamous and before we can sort of cohabitate, and we have to have that happen for a while before we can get engaged. And if I want to start having children by the time I'm 35, that meant that I would have had to have been on my way to marriage five years ago. So that wasn't going to work.
 
If my strategy was to least-expect my way into true love, then the variable that I had to deal with was serendipity1. In short, I was trying to figure out, well, what's the probability of my finding Mr. Right? Well, at the time I was living in the city of Philadelphia, and it's a big city, and I figured, in this entire place, there are lots of possibilities. So again, I started doing some math. Population of Philadelphia: It has 1.5 million people. I figure about half of that are men, so that takes the number down to 750,000. I'm looking for a guy between the ages of 30 and 36, which was only four percent of the population, so now I'm dealing2 with the possibility of 30,000 men. I was looking for somebody who was Jewish, because that's what I am and that was important to me. That's only 2.3 percent of the population. I figure I'm attracted to maybe one out of 10 of those men, and there was no way I was going to deal with somebody who was an avid3 golfer. So that basically meant there were 35 men for me that I could possibly date in the entire city of Philadelphia.
 
In the meantime, my very large Jewish family was already all married and well on their way to having lots and lots of children, and I felt like I was under tremendous peer pressure to get my life going already.
 
So if I have two possible strategies at this point I'm sort of figuring out. One, I can take my grandmother's advice and sort of least-expect my way into maybe bumping into the one out of 35 possible men in the entire 1.5 million-person city of Philadelphia, or I could try online dating. Now, I like the idea of online dating, because it's predicated on an algorithm, and that's really just a simple way of saying I've got a problem, I'm going to use some data, run it through a system and get to a solution. So online dating is the second most popular way that people now meet each other, but as it turns out, algorithms have been around for thousands of years in almost every culture. In fact, in Judaism, there were matchmakers a long time ago, and though they didn't have an explicit4 algorithm per se, they definitely were running through formulas in their heads, like, is the girl going to like the boy? Are the families going to get along? What's the rabbi going to say? Are they going to start having children right away? And the matchmaker would sort of think through all of this, put two people together, and that would be the end of it. So in my case, I thought, well, will data and an algorithm lead me to my Prince Charming? So I decided5 to sign on.
 
Now, there was one small catch. As I'm signing on to the various dating websites, as it happens, I was really, really busy. But that actually wasn't the biggest problem. The biggest problem is that I hate filling out questionnaires of any kind, and I certainly don't like questionnaires that are like Cosmo quizzes. So I just copied and pasted from my résumé.
 
(Laughter)
 
So in the descriptive part up top, I said that I was an award-winning journalist and a future thinker. When I was asked about fun activities and my ideal date, I said monetization and fluency6 in Japanese. I talked a lot about JavaScript.
 
So obviously this was not the best way to put my most sexy foot forward. But the real failure was that there were plenty of men for me to date. These algorithms had a sea full of men that wanted to take me out on lots of dates -- what turned out to be truly awful dates. There was this guy Steve, the I.T. guy. The algorithm matched us up because we share a love of gadgets7, we share a love of math and data and '80s music, and so I agreed to go out with him. So Steve the I.T. guy invited me out to one of Philadelphia's white-table-cloth, extremely expensive restaurants. And we went in, and right off the bat, our conversation really wasn't taking flight, but he was ordering a lot of food. In fact, he didn't even bother looking at the menu. He was ordering multiple appetizers8, multiple entrées, for me as well, and suddenly there are piles and piles of food on our table, also lots and lots of bottles of wine. So we're nearing the end of our conversation and the end of dinner, and I've decided Steve the I.T. guy and I are really just not meant for each other, but we'll part ways as friends, when he gets up to go to the bathroom, and in the meantime the bill comes to our table. And listen, I'm a modern woman. I am totally down with splitting the bill. But then Steve the I.T. guy didn't come back. (Gasping) And that was my entire month's rent. So needless to say, I was not having a good night. So I run home, I call my mother, I call my sister, and as I do, at the end of each one of these terrible, terrible dates, I regale9 them with the details.
 
And they say to me, "Stop complaining." (Laughter) "You're just being too picky."
 
So I said, fine, from here on out I'm only going on dates where I know that there's wi-fi, and I'm bringing my laptop. I'm going to shove it into my bag, and I'm going to have this email template, and I'm going to fill it out and collect information on all these different data points during the date to prove to everybody that empirically, these dates really are terrible. (Laughter) So I started tracking things like really stupid, awkward, sexual remarks; bad vocabulary; the number of times a man forced me to high-five him.
 
(Laughter)
 
So I started to crunch10 some numbers, and that allowed me to make some correlations11. So as it turns out, for some reason, men who drink Scotch12 reference kinky sex immediately.
 
(Laughter)
 
Well, it turns out that these probably weren't bad guys. There were just bad for me. And as it happens, the algorithms that were setting us up, they weren't bad either. These algorithms were doing exactly what they were designed to do, which was to take our user-generated information, in my case, my résumé, and match it up with other people's information. See, the real problem here is that, while the algorithms work just fine, you and I don't, when confronted with blank windows where we're supposed to input13 our information online. Very few of us have the ability to be totally and brutally14 honest with ourselves. The other problem is that these websites are asking us questions like, are you a dog person or a cat person? Do you like horror films or romance films? I'm not looking for a pen pal15. I'm looking for a husband. Right? So there's a certain amount of superficiality in that data.
 
So I said fine, I've got a new plan. I'm going to keep using these online dating sites, but I'm going to treat them as databases, and rather than waiting for an algorithm to set me up, I think I'm going to try reverse-engineering this entire system. So knowing that there was superficial data that was being used to match me up with other people, I decided instead to ask my own questions. What was every single possible thing that I could think of that I was looking for in a mate?
 
So I started writing and writing and writing, and at the end, I had amassed16 72 different data points. I wanted somebody was Jew...ish, so I was looking for somebody who had the same background and thoughts on our culture, but wasn't going to force me to go to shul every Friday and Saturday. I wanted somebody who worked hard, because work for me is extremely important, but not too hard. For me, the hobbies that I have are really just new work projects that I've launched. I also wanted somebody who not only wanted two children, but was going to have the same attitude toward parenting that I do, so somebody who was going to be totally okay with forcing our child to start taking piano lessons at age three, and also maybe computer science classes if we could wrangle17 it. So things like that, but I also wanted somebody who would go to far-flung, exotic places, like Petra, Jordan. I also wanted somebody who would weigh 20 pounds more than me at all times, regardless of what I weighed.
 
(Laughter)
 
So I now have these 72 different data points, which, to be fair, is a lot. So what I did was, I went through and I prioritized that list. I broke it into a top tier and a second tier of points, and I ranked everything starting at 100 and going all the way down to 91, and listing things like I was looking for somebody who was really smart, who would challenge and stimulate18 me, and balancing that with a second tier and a second set of points. These things were also important to me but not necessarily deal-breakers.
 
So once I had all this done, I then built a scoring system, because what I wanted to do was to sort of mathematically calculate whether or not I thought the guy that I found online would be a match with me. I figured there would be a minimum of 700 points before I would agree to email somebody or respond to an email message. For 900 points, I'd agree to go out on a date, and I wouldn't even consider any kind of relationship before somebody had crossed the 1,500 point threshold.
 
Well, as it turns out, this worked pretty well. So I go back online now. I found Jewishdoc57 who's incredibly good-looking, incredibly well-spoken, he had hiked Mt. Fuji, he had walked along the Great Wall. He likes to travel as long as it doesn't involve a cruise ship. And I thought, I've done it! I've cracked the code. I have just found the Jewish Prince Charming of my family's dreams.
 
There was only one problem: He didn't like me back. And I guess the one variable that I haven't considered is the competition. Who are all of the other women on these dating sites? I found SmileyGirl1978. She said she was a "fun girl who is Happy and Outgoing." She listed her job as teacher. She said she is "silly, nice and friendly." She likes to make people laugh "alot."
 
At this moment I knew, clicking after profile after profile after profile that looked like this, that I needed to do some market research. So I created 10 fake male profiles. Now, before I lose all of you -- (Laughter) -- understand that I did this strictly19 to gather data about everybody else in the system. I didn't carry on crazy Catfish-style relationships with anybody. I really was just scraping their data. But I didn't want everybody's data. I only wanted data on the women who were going to be attracted to the type of man that I really, really wanted to marry. (Laughter)
 
When I released these men into the wild, I did follow some rules. So I didn't reach out to any woman first. I just waited to see who these profiles were going to attract, and mainly what I was looking at was two different data sets. So I was looking at qualitative20 data, so what was the humor, the tone, the voice, the communication style that these women shared in common? And also quantitative21 data, so what was the average length of their profile, how much time was spent between messages? What I was trying to get at here was that I figured in person, I would be just as competitive as a SmileyGirl1978. I wanted to figure out how to maximize my own profile online.
 
Well, one month later, I had a lot of data, and I was able to do another analysis. And as it turns out, content matters a lot. So smart people tend to write a lot -- 3,000, 4,000, 5,000 words about themselves, which may all be very, very interesting. The challenge here, though, is that the popular men and women are sticking to 97 words on average that are written very, very well, even though it may not seem like it all the time. The other sort of hallmark of the people who do this well is that they're using non-specific language. So in my case, you know, "The English Patient" is my most favorite movie ever, but it doesn't work to use that in a profile, because that's a superficial data point, and somebody may disagree with me and decide they don't want to go out with me because they didn't like sitting through the three-hour movie.
 
Also, optimistic language matters a lot. So this is a word cloud highlighting the most popular words that were used by the most popular women, words like "fun" and "girl" and "love." And what I realized was not that I had to dumb down my own profile. Remember, I'm somebody who said that I speak fluent Japanese and I know JavaScript and I was okay with that. The difference is that it's about being more approachable and helping22 people understand the best way to reach out to you.
 
And as it turns out, timing23 is also really, really important. Just because you have access to somebody's mobile phone number or their instant message account and it's 2 o'clock in the morning and you happen to be awake, doesn't mean that that's a good time to communicate with those people. The popular women on these online sites spend an average of 23 hours in between each communication. And that's what we would normally do in the usual process of courtship.
 
And finally, there were the photos. All of the women who were popular showed some skin. They all looked really great, which turned out to be in sharp contrast to what I had uploaded.
 
Once I had all of this information, I was able to create a super profile, so it was still me, but it was me optimized24 now for this ecosystem25. And as it turns out, I did a really good job. I was the most popular person online.
 
(Laughter) (Applause)
 
And as it turns out, lots and lots of men wanted to date me. So I call my mom, I call my sister, I call my grandmother. I'm telling them about this fabulous26 news, and they say, "This is wonderful! How soon are you going out?" And I said, "Well, actually, I'm not going to go out with anybody." Because remember, in my scoring system, they have to reach a minimum threshold of 700 points, and none of them have done that. They said, "What? You're still being too damn picky."
 
Well, not too long after that, I found this guy, Thevenin, and he said that he was culturally Jewish, he said that his job was an arctic baby seal hunter, which I thought was very clever. He talked in detail about travel. He made a lot of really interesting cultural references. He looked and talked exactly like what I wanted, and immediately, he scored 850 points. It was enough for a date.
 
Three weeks later, we met up in person for what turned out to be a 14-hour-long conversation that went from coffee shop to restaurant to another coffee shop to another restaurant, and when he dropped me back off at my house that night I re-scored him -- [1,050 points!] -- thought, you know what, this entire time I haven't been picky enough. Well, a year and a half after that, we were non-cruise ship traveling through Petra, Jordan, when he got down on his knee and proposed. A year after that, we were married, and about a year and a half after that, our daughter, Petra, was born. (Applause)
 
Obviously, I'm having a fabulous life, so -- (Laughter) -- the question is, what does all of this mean for you?
 
Well, as it turns out, there is an algorithm for love. It's just not the ones that we're being presented with online. In fact, it's something that you write yourself. So whether you're looking for a husband or a wife or you're trying to find your passion or you're trying to start a business, all you have to really do is figure out your own framework and play by your own rules, and feel free to be as picky as you want.
 
Well, on my wedding day, I had a conversation again with my grandmother, and she said, "All right, maybe I was wrong. It looks like you did come up with a really, really great system. Now, your matzoh balls. They should be fluffy27, not hard."
 
And I'll take her advice on that.

点击收听单词发音收听单词发音  

1 serendipity jDyzZ     
n.偶然发现物品之才能;意外新发现
参考例句:
  • "It was serendipity all the way,"he says.用他的话说是“一直都很走运”。
  • Some of the best effects in my garden have been the result of serendipity.我园子里最珍贵的几件物品是机缘巧合之下意外所得。
2 dealing NvjzWP     
n.经商方法,待人态度
参考例句:
  • This store has an excellent reputation for fair dealing.该商店因买卖公道而享有极高的声誉。
  • His fair dealing earned our confidence.他的诚实的行为获得我们的信任。
3 avid ponyI     
adj.热心的;贪婪的;渴望的;劲头十足的
参考例句:
  • He is rich,but he is still avid of more money.他很富有,但他还想贪图更多的钱。
  • She was avid for praise from her coach.那女孩渴望得到教练的称赞。
4 explicit IhFzc     
adj.详述的,明确的;坦率的;显然的
参考例句:
  • She was quite explicit about why she left.她对自己离去的原因直言不讳。
  • He avoids the explicit answer to us.他避免给我们明确的回答。
5 decided lvqzZd     
adj.决定了的,坚决的;明显的,明确的
参考例句:
  • This gave them a decided advantage over their opponents.这使他们比对手具有明显的优势。
  • There is a decided difference between British and Chinese way of greeting.英国人和中国人打招呼的方式有很明显的区别。
6 fluency ajCxF     
n.流畅,雄辩,善辩
参考例句:
  • More practice will make you speak with greater fluency.多练习就可以使你的口语更流利。
  • Some young children achieve great fluency in their reading.一些孩子小小年纪阅读已经非常流畅。
7 gadgets 7239f3f3f78d7b7d8bbb906e62f300b4     
n.小机械,小器具( gadget的名词复数 )
参考例句:
  • Certainly. The idea is not to have a house full of gadgets. 当然。设想是房屋不再充满小配件。 来自超越目标英语 第4册
  • This meant more gadgets and more experiments. 这意味着要设计出更多的装置,做更多的实验。 来自英汉非文学 - 科学史
8 appetizers dd5245cbcffa48ce7e107a4a67e085e5     
n.开胃品( appetizer的名词复数 );促进食欲的活动;刺激欲望的东西;吊胃口的东西
参考例句:
  • Here is the egg drop and appetizers to follow. 这是您要的蛋花汤和开胃品。 来自互联网
  • Would you like appetizers or a salad to go with that? 你要不要小菜或色拉? 来自互联网
9 regale mUUxT     
v.取悦,款待
参考例句:
  • He was constantly regaled with tales of woe.别人老是给他讲些倒霉事儿来逗他开心。
  • He loved to regale his friends with tales about the many memorable characters he had known as a newspaperman.他喜欢讲些他当记者时认识的许多名人的故事给朋友们消遣。
10 crunch uOgzM     
n.关键时刻;艰难局面;v.发出碎裂声
参考例句:
  • If it comes to the crunch they'll support us.关键时刻他们是会支持我们的。
  • People who crunch nuts at the movies can be very annoying.看电影时嘎吱作声地嚼干果的人会使人十分讨厌。
11 correlations 4a9b6fe1ddc2671881c9aa3d6cc07e8e     
相互的关系( correlation的名词复数 )
参考例句:
  • One would expect strong and positive correlations between both complexes. 人们往往以为这两个综合体之间有紧密的正相关。
  • The correlations are of unequal value. 这些对应联系的价值并不相同。
12 scotch ZZ3x8     
n.伤口,刻痕;苏格兰威士忌酒;v.粉碎,消灭,阻止;adj.苏格兰(人)的
参考例句:
  • Facts will eventually scotch these rumours.这种谣言在事实面前将不攻自破。
  • Italy was full of fine views and virtually empty of Scotch whiskey.意大利多的是美景,真正缺的是苏格兰威士忌。
13 input X6lxm     
n.输入(物);投入;vt.把(数据等)输入计算机
参考例句:
  • I will forever be grateful for his considerable input.我将永远感激他的大量投入。
  • All this information had to be input onto the computer.所有这些信息都必须输入计算机。
14 brutally jSRya     
adv.残忍地,野蛮地,冷酷无情地
参考例句:
  • The uprising was brutally put down.起义被残酷地镇压下去了。
  • A pro-democracy uprising was brutally suppressed.一场争取民主的起义被残酷镇压了。
15 pal j4Fz4     
n.朋友,伙伴,同志;vi.结为友
参考例句:
  • He is a pal of mine.他是我的一个朋友。
  • Listen,pal,I don't want you talking to my sister any more.听着,小子,我不让你再和我妹妹说话了。
16 amassed 4047ea1217d3f59ca732ca258d907379     
v.积累,积聚( amass的过去式和过去分词 )
参考例句:
  • He amassed a fortune from silver mining. 他靠开采银矿积累了一笔财富。
  • They have amassed a fortune in just a few years. 他们在几年的时间里就聚集了一笔财富。 来自《简明英汉词典》
17 wrangle Fogyt     
vi.争吵
参考例句:
  • I don't want to get into a wrangle with the committee.我不想同委员会发生争执。
  • The two countries fell out in a bitter wrangle over imports.这两个国家在有关进口问题的激烈争吵中闹翻了。
18 stimulate wuSwL     
vt.刺激,使兴奋;激励,使…振奋
参考例句:
  • Your encouragement will stimulate me to further efforts.你的鼓励会激发我进一步努力。
  • Success will stimulate the people for fresh efforts.成功能鼓舞人们去作新的努力。
19 strictly GtNwe     
adv.严厉地,严格地;严密地
参考例句:
  • His doctor is dieting him strictly.他的医生严格规定他的饮食。
  • The guests were seated strictly in order of precedence.客人严格按照地位高低就座。
20 qualitative JC4yi     
adj.性质上的,质的,定性的
参考例句:
  • There are qualitative differences in the way children and adults think.孩子和成年人的思维方式有质的不同。
  • Arms races have a quantitative and a qualitative aspects.军备竞赛具有数量和质量两个方面。
21 quantitative TCpyg     
adj.数量的,定量的
参考例句:
  • He said it was only a quantitative difference.他说这仅仅是数量上的差别。
  • We need to do some quantitative analysis of the drugs.我们对药物要进行定量分析。
22 helping 2rGzDc     
n.食物的一份&adj.帮助人的,辅助的
参考例句:
  • The poor children regularly pony up for a second helping of my hamburger. 那些可怜的孩子们总是要求我把我的汉堡包再给他们一份。
  • By doing this, they may at times be helping to restore competition. 这样一来, 他在某些时候,有助于竞争的加强。
23 timing rgUzGC     
n.时间安排,时间选择
参考例句:
  • The timing of the meeting is not convenient.会议的时间安排不合适。
  • The timing of our statement is very opportune.我们发表声明选择的时机很恰当。
24 optimized 81c61ac8ff2adb570ce4c7e7dfed59bd     
adj.最佳化的,(使)最优化的v.使最优化,使尽可能有效( optimize的过去式和过去分词 )
参考例句:
  • We are often asked whether consumer Web sites should be optimized for beginners or intermediates. 我们常常被问到这样的问题:消费类网站究竟应该为新手而优化,还是应该为中间用户而优化? 来自About Face 3交互设计精髓
  • GOOGLE Advertising optimized sequence, greatly increasing the advertising effect. 优化了GOOGLE广告位排列顺序,大大增加了广告效果。 来自互联网
25 ecosystem Wq4xz     
n.生态系统
参考例句:
  • This destroyed the ecosystem of the island.这样破坏了岛上的生态系统。
  • We all have an interest in maintaining the integrity of the ecosystem.维持生态系统的完整是我们共同的利益。
26 fabulous ch6zI     
adj.极好的;极为巨大的;寓言中的,传说中的
参考例句:
  • We had a fabulous time at the party.我们在晚会上玩得很痛快。
  • This is a fabulous sum of money.这是一笔巨款。
27 fluffy CQjzv     
adj.有绒毛的,空洞的
参考例句:
  • Newly hatched chicks are like fluffy balls.刚孵出的小鸡像绒毛球。
  • The steamed bread is very fluffy.馒头很暄。
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