TEDNYC
Lux Narayan: What I learned from 2,000 obituaries
勒克斯·纳拉扬: 我们能从2000份讣告中学到什么
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勒克斯·纳拉扬的一天以一盘炒鸡蛋和一个问题开始：“今天谁死了？”他为什么要这样做？他分析了纽约时报超过20个月间的2000份讣告，纳拉扬从中收集了概括了那些人一生的成就的简短话语。接下来他将与我们分享，这些不朽的文字在如何生活方面能教会我们什么。
Lux Narayan - Entrepreneur
Lux Narayan is a perpetual learner of various things -- from origami and molecular gastronomy to stand-up and improv comedy. Full bio
Lux Narayan is a perpetual learner of various things -- from origami and molecular gastronomy to stand-up and improv comedy. Full bio
Double-click the English transcript below to play the video.
00:12
Joseph Keller used to jog
around the Stanford campus,
around the Stanford campus,
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约瑟夫·凯勒以前常绕着
斯坦福大学校区慢跑，
斯坦福大学校区慢跑，
00:16
and he was struck by all the women
jogging there as well.
jogging there as well.
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而他对许多同样在慢跑的女性
感到很震惊。
感到很震惊。
为什么她们的马尾辫
会那样左右扫来扫去呢？
会那样左右扫来扫去呢？
00:21
Why did their ponytails swing
from side to side like that?
from side to side like that?
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00:25
Being a mathematician,
he set out to understand why.
he set out to understand why.
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作为一名数学家，他开始探究原因。
00:29
(Laughter)
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（笑声）
凯勒教授对许多东西都很好奇：
00:30
Professor Keller was curious
about many things:
about many things:
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为什么茶壶上会沾水，
00:32
why teapots dribble
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还有蚯蚓是如何蠕动的。
00:34
or how earthworms wriggle.
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00:36
Until a few months ago,
I hadn't heard of Joseph Keller.
I hadn't heard of Joseph Keller.
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在几个月前，
我还从未听说过约瑟夫·凯勒。
我还从未听说过约瑟夫·凯勒。
我在《纽约时报》上读到了他，
00:40
I read about him in the New York Times,
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00:43
in the obituaries.
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出现在讣告中。
《纽约时报》专门用了
半幅版面来讲述他，
半幅版面来讲述他，
00:44
The Times had half a page
of editorial dedicated to him,
of editorial dedicated to him,
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这也算是这种影响力的报刊里
级别最高的版面了。
级别最高的版面了。
00:48
which you can imagine is premium space
for a newspaper of their stature.
for a newspaper of their stature.
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00:53
I read the obituaries almost every day.
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我几乎每天都会看讣告。
可以理解的是，
我妻子觉得我相当有病，
我妻子觉得我相当有病，
00:56
My wife understandably thinks
I'm rather morbid
I'm rather morbid
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我的每一天从一盘炒鸡蛋开始，
再加一句：“看看今天谁死了。”
再加一句：“看看今天谁死了。”
00:59
to begin my day with scrambled eggs
and a "Let's see who died today."
and a "Let's see who died today."
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（笑声）
01:04
(Laughter)
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01:06
But if you think about it,
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不过仔细想想，
01:07
the front page of the newspaper
is usually bad news,
is usually bad news,
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报纸的头版通常刊登的
都是负面新闻，
都是负面新闻，
暗示着人类的失败。
01:10
and cues man's failures.
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如果你想在负面新闻中
找到一些好的成就，
找到一些好的成就，
01:12
An instance where bad news
cues accomplishment
cues accomplishment
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就得去末版的讣告里找了。
01:15
is at the end of the paper,
in the obituaries.
in the obituaries.
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01:19
In my day job,
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在日常工作时，
01:20
I run a company that focuses
on future insights
on future insights
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我经营一家公司，
致力于提供对未来的预测，
致力于提供对未来的预测，
01:23
that marketers can derive
from past data --
from past data --
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是从过去的企业数据中分析得出的，
算是一种后知后觉的分析。
01:25
a kind of rearview-mirror analysis.
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01:29
And we began to think:
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然后我们开始思考：
要是我们用后知后觉方式
来分析《纽约时报》上的讣告呢？
来分析《纽约时报》上的讣告呢？
01:30
What if we held a rearview mirror
to obituaries from the New York Times?
to obituaries from the New York Times?
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01:36
Were there lessons on how you could get
your obituary featured --
your obituary featured --
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你未来的讣告会怎么写，
它能教会你什么？
它能教会你什么？
01:40
even if you aren't around to enjoy it?
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虽然你本人已经没法活着拜读了。
（笑声）
01:42
(Laughter)
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这样的讣告是不是和炒鸡蛋更配呢？
01:43
Would this go better with scrambled eggs?
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（笑声）
01:46
(Laughter)
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01:48
And so, we looked at the data.
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于是，我们研究了数据。
01:51
2,000 editorial, non-paid obituaries
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2000份由报社编辑的无偿的讣告，
01:56
over a 20-month period
between 2015 and 2016.
between 2015 and 2016.
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来自2015和2016年里的20个月。
这2000例死亡，或是说2000条生命，
能教给我们什么呢？
能教给我们什么呢？
02:00
What did these 2,000 deaths --
rather, lives -- teach us?
rather, lives -- teach us?
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首先我们研究了用语。
02:04
Well, first we looked at words.
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这是一个讣告的标题。
02:06
This here is an obituary headline.
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为了了不起的李光耀先生而写。
02:08
This one is of the amazing Lee Kuan Yew.
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如果去掉开头结尾，
02:11
If you remove the beginning and the end,
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你会看到一段文字优美、
描述准确的叙述辞，
描述准确的叙述辞，
02:13
you're left with a beautifully
worded descriptor
worded descriptor
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它尝试用寥寥数语精确描述
个人成就或是一生经历。
个人成就或是一生经历。
02:16
that tries to, in just a few words,
capture an achievement or a lifetime.
capture an achievement or a lifetime.
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仅仅是读这些就已经很令人着迷了。
02:21
Just looking at these is fascinating.
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这有一些人物描述，
是关于最近两年去世的名人。
是关于最近两年去世的名人。
02:24
Here are a few famous ones,
people who died in the last two years.
people who died in the last two years.
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尝试猜猜他们是谁。
02:27
Try and guess who they are.
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颠覆流派传统的艺术家
02:28
[An Artist who Defied Genre]
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这是美国歌手“王子”。
02:30
That's Prince.
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二十世纪的拳击巨人
02:32
[Titan of Boxing and the 20th Century]
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没错。
02:34
Oh, yes.
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拳王阿里
02:35
[Muhammad Ali]
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02:36
[Groundbreaking Architect]
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开创性的建筑师
扎哈·哈迪德。
02:38
Zaha Hadid.
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然后我们对这些叙述辞
02:40
So we took these descriptors
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做了一种叫做自然语言处理的操作，
02:42
and did what's called
natural language processing,
natural language processing,
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其实就是把文字放进一个程序里，
02:45
where you feed these into a program,
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它会筛去多余的字词，
02:46
it throws out the superfluous words --
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例如“这”、“和”，
这种很容易能比划明白的字，
这种很容易能比划明白的字，
02:48
"the," "and," -- the kind of words
you can mime easily in "Charades," --
you can mime easily in "Charades," --
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02:53
and leaves you with the most
significant words.
significant words.
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只把最重要的词语留下。
我们不止对上述4个标题做了处理，
02:55
And we did it not just for these four,
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而是整整2000份叙述辞。
02:57
but for all 2,000 descriptors.
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呈现的结果如下。
02:59
And this is what it looks like.
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03:03
Film, theatre, music, dance
and of course, art, are huge.
and of course, art, are huge.
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电影，戏剧，音乐，舞蹈……
当然，还有艺术占比很大。
当然，还有艺术占比很大。
03:08
Over 40 percent.
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超过四成了。
03:10
You have to wonder
why in so many societies
why in so many societies
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你必须要细想看看，
为何在许多社会中，
为何在许多社会中，
我们会坚持让我们的孩子从事
工程、医药、商业、法律等工作，
工程、医药、商业、法律等工作，
03:13
we insist that our kids pursue
engineering or medicine or business or law
engineering or medicine or business or law
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并认定它们代表着成功。
03:17
to be construed as successful.
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03:19
And while we're talking profession,
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既然我们谈到了职业，
让我们再看看年龄。
03:21
let's look at age --
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他们获得成就的平均年龄。
03:22
the average age at which
they achieved things.
they achieved things.
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这个数字是37岁。
03:25
That number is 37.
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03:28
What that means is,
you've got to wait 37 years ...
you've got to wait 37 years ...
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这说明你必须要等上37年，
03:31
before your first significant achievement
that you're remembered for --
that you're remembered for --
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才能首次获得足以让你留名的成就，
这是平均值。
03:35
on average --
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44年后，在你81岁去世时才会留名，
03:36
44 years later, when you
die at the age of 81 --
die at the age of 81 --
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这也是平均值。
03:39
on average.
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（笑声）
03:40
(Laughter)
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这说明我们要有耐心。
03:41
Talk about having to be patient.
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（笑声）
03:42
(Laughter)
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当然这也因职业而异。
03:44
Of course, it varies by profession.
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03:46
If you're a sports star,
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如果你是运动明星，
你多半会在20多岁时进入巅峰。
03:47
you'll probably hit
your stride in your 20s.
your stride in your 20s.
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如果你像我一样是个40来岁的人，
03:49
And if you're in your 40s like me,
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你大概还能在政界搞出点名堂。
03:52
you can join the fun world of politics.
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（笑声）
03:54
(Laughter)
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政客在45岁左右才做出人生首件，
也许是唯一值得称道的事迹。
也许是唯一值得称道的事迹。
03:55
Politicians do their first and sometimes
only commendable act in their mid-40s.
only commendable act in their mid-40s.
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03:59
(Laughter)
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（笑声）
也许你会好奇"其他"是什么，
04:00
If you're wondering what "others" are,
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这里有些例子。
04:02
here are some examples.
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04:04
Isn't it fascinating, the things people do
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这些不是很有趣吗？
人们所做的事情，为人所铭记的事情？
04:06
and the things they're remembered for?
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麦克斯·波伏娃：放弃科学成为邪教主教
04:08
(Laughter)
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乔治·德·派尔斯：9位总统的裁缝
卡罗·多达：裸胸娱乐的先驱
卡罗·多达：裸胸娱乐的先驱
04:12
Our curiosity was in overdrive,
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我们的好奇心彻底控制不住了，
我们不满足于仅仅分析叙述辞。
04:14
and we desired to analyze
more than just a descriptor.
more than just a descriptor.
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04:18
So, we ingested the entire
first paragraph of all 2,000 obituaries,
first paragraph of all 2,000 obituaries,
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所以我们又分析了
2000份讣告的第一段，
2000份讣告的第一段，
但我们把讣告分为两组来分析：
04:23
but we did this separately
for two groups of people:
for two groups of people:
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一组是名人，一组是不出名的人。
04:26
people that are famous
and people that are not famous.
and people that are not famous.
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名人，例如“王子”、阿里、扎哈·哈迪德，
04:29
Famous people -- Prince,
Ali, Zaha Hadid --
Ali, Zaha Hadid --
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不出名的人，例如乔斯琳·库伯，
04:32
people who are not famous
are people like Jocelyn Cooper,
are people like Jocelyn Cooper,
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加里牧师，
04:36
Reverend Curry
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罗娜·凯利等等。
04:37
or Lorna Kelly.
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我敢说大多数名字你都没有听过。
04:38
I'm willing to bet you haven't heard
of most of their names.
of most of their names.
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他们是杰出的人，有着杰出的成就，
但并不出名。
但并不出名。
04:42
Amazing people, fantastic achievements,
but they're not famous.
but they're not famous.
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04:46
So what if we analyze
these two groups separately --
these two groups separately --
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所以，如果我们分别分析这两组，
出不出名有什么区别？
04:49
the famous and the non-famous?
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它会告诉我们什么呢？
04:51
What might that tell us?
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请看吧。
04:52
Take a look.
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04:56
Two things leap out at me.
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两样东西吸引了我的注意。
04:58
First:
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第一：
05:00
"John."
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“约翰”。
（笑声）
05:01
(Laughter)
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05:03
Anyone here named John
should thank your parents --
should thank your parents --
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所有名叫“约翰”的人要好好感谢父母。
（笑声）
05:07
(Laughter)
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还要提醒你的孩子
在你死后把你的讣告剪下来。
在你死后把你的讣告剪下来。
05:08
and remind your kids to cut out
your obituary when you're gone.
your obituary when you're gone.
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05:13
And second:
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第二：
05:15
"help."
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“帮助”。
05:18
We uncovered, many lessons
from lives well-led,
from lives well-led,
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我们从这些杰出的生命中，
从这些被文字记录的人身上
学到了好多东西。
学到了好多东西。
05:22
and what those people immortalized
in print could teach us.
in print could teach us.
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这种过程是对生命万花筒的极好检验，
05:24
The exercise was a fascinating testament
to the kaleidoscope that is life,
to the kaleidoscope that is life,
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而更加迷人的是，
05:29
and even more fascinating
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在绝大多数的讣告中，
05:32
was the fact that the overwhelming
majority of obituaries
majority of obituaries
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无论主角是否出名，
05:35
featured people famous and non-famous,
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他们都做了看似不平凡的事。
05:38
who did seemingly extraordinary things.
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他们在生命长河中留下了闪光的点滴。
05:41
They made a positive dent
in the fabric of life.
in the fabric of life.
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他们伸出了援手。
05:44
They helped.
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05:46
So ask yourselves as you go
back to your daily lives:
back to your daily lives:
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所以在日常生活中请扪心自问：
我该如何用我的才能帮助这个社会？
05:49
How am I using my talents to help society?
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因为这其中最重要的道理就是：
05:52
Because the most powerful lesson here is,
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如果有更多的人在活着时
多想想如何留下身后名，
多想想如何留下身后名，
05:55
if more people lived their lives
trying to be famous in death,
trying to be famous in death,
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这个世界将会更加美好。
05:59
the world would be a much better place.
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06:03
Thank you.
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谢谢。
（掌声）
06:04
(Applause)
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ABOUT THE SPEAKER
Lux Narayan - EntrepreneurLux Narayan is a perpetual learner of various things -- from origami and molecular gastronomy to stand-up and improv comedy.
Why you should listen
Lakshmanan aka Lux Narayan mans the helm of Unmetric, a social media intelligence company that helps digital marketers, social media analysts, and content creators harness social signals to track and analyze competitive content and campaigns, and to create better content and campaigns of their own.
Prior to founding Unmetric, Narayan was a co-founder at Vembu Technologies, an online data backup company. He also helped found and volunteered at ShareMyCake, a non-profit started by his wife that focuses on encouraging children to use their birthdays to channel monetary support towards a cause of their choosing.
As Unmetric's CEO, he leads a team of 70 people distributed across the company's operations in Chennai and New York City.
Outside of work, he is a perpetual learner of various things -- from origami and molecular gastronomy to stand-up and improv comedy. He enjoys reading obituaries and other non-fiction and watching documentaries with bad ratings. Narayan makes time every year for trekking in the Himalayas or scuba diving in tropical waters, and once he learns to fly, he hopes to spend more time off land than on it.
Lux Narayan | Speaker | TED.com