06:30
TED2010

Sebastian Wernicke: Lies, damned lies and statistics (about TEDTalks)

TEDTalksにまつわる真っ赤な嘘と統計の話

Filmed:

素晴しく皮肉の効いた分析により、セバスチャン・ワーニックがTEDTalkを統計分析というツールにかけ、ユーザ評価に基づいた「最適なTEDTalk」を作るための基準を編み出しています。この講演をどのように評価されますか? 「びっくり」? 「説得力なし」? それとも、ただただ「可笑しい」?

- Data scientist
After making a splash in the field of bioinformatics, Sebastian Wernicke moved on to the corporate sphere, where he motivates and manages multidimensional projects. Full bio

If you go on the TED website,
もし今TEDのホームページに行くと
00:16
you can currently find there
延べ1週間を越えるビデオがあり
00:19
over a full week of TEDTalk videos,
130万語に上る
00:21
over 1.3 million
文字起こしデータと
00:24
words of transcripts
何百万という
00:26
and millions of user ratings.
ユーザー評価を見られます
00:28
And that's a huge amount of data.
実に莫大な量のデータです
00:30
And it got me wondering:
それを見てこう思いました
00:33
If you took all this data
「もしこのデータ全てを
00:35
and put it through statistical analysis,
統計分析にかければ TEDTalkを
00:37
could you reverse engineer a TEDTalk?
リバースエンジニアリングして
00:39
Could you create
究極のTEDTalkを
00:41
the ultimate TEDTalk?
作れるかも」
00:43
(Laughter) (Applause)
(拍手)
00:45
And also, could you create
「それにまた
00:47
the worst possible TEDTalk
大目に見てもらえる
00:49
that they would still let you get away with?
最低のTEDTalkも」
00:51
To find this out, I looked at three things:
これを確かめるべく 3つの点に着目しました
00:53
I looked at the topic that you should choose,
選ぶべき題材
00:55
I looked at how you should deliver it
講演のやり方
00:57
and the visuals onstage.
舞台上での見た目です
01:00
Now, with the topic: There's a whole range of topics you can choose,
さて 選べる題材は多岐にわたりますが
01:02
but you should choose wisely,
賢く選択しなくてはいけません
01:05
because your topic strongly correlates
題材はユーザーの反応と
01:07
with how users will react to your talk.
密接な関係があるからです
01:09
Now, to make this more concrete,
話をより具体的にするため
01:12
let's look at the list of top 10 words
統計的にみて
01:14
that statistically stick out
最も好まれるTalkと
01:17
in the most favorite TEDTalks
最も好まれないTalkに
01:19
and in the least favorite TEDTalks.
よく見られる10個の言葉を拾い上げてみました
01:21
So if you came here
TEDでは
01:24
to talk about how French coffee
「フレンチ」「コーヒー」が
01:26
will spread happiness in our brains,
「あなたの」「脳」にもたらす「幸福感」について
01:28
that's a go.
話をすれば 成功間違いなしです
01:31
(Laughter) (Applause)
(拍手)
01:33
Whereas, if you wanted to talk about
一方で 「酸素」「女の子」
01:35
your project involving
「飛行機」が関わる
01:37
oxygen, girls, aircraft --
プロジェクトの話をするつもりなら
01:39
actually, I would like to hear that talk, (Laughter)
個人的には聞いてみたいですが
01:41
but statistics say it's not so good.
統計的にはうまくいきません
01:43
Oh, well.
そして
01:45
If you generalize this,
これをもっと一般化すると
01:47
the most favorite TEDTalks are those
最も好まれるTEDTalkは
01:49
that feature topics we can connect with,
私たちが容易に自分と深く
01:51
both easily and deeply,
関係づけられるもの
01:54
such as happiness, our own body,
「幸福」「体のこと」「食べ物」
01:56
food, emotions.
「感情」などの話題です
01:58
And the more technical topics,
もっと専門性の高い話題
02:00
such as architecture, materials and, strangely enough, men,
「建築」「素材」 それと面白いことに「男」なんかは
02:02
those are not good topics to talk about.
TEDではウケません
02:05
How should you deliver your talk?
次にどのように講演を行うかですが
02:08
TED is famous for keeping
TEDが時間にうるさいことは
02:10
a very sharp eye on the clock,
よく知られています
02:12
so they're going to hate me
だからこのことをお教えすると
02:14
for revealing this, because, actually,
嫌な顔をされると思いますが
02:16
you should talk as long as they will let you. (Laughter)
可能な限り長く話してください
02:18
Because the most favorite TEDTalks
最も好まれているTalkは
02:20
are, on average, over 50 percent longer
好まれてないTalkより
02:23
than the least favorite ones.
平均で50%以上長いのです
02:25
And this holds true for all ranking lists on TED.com
これは個々のランキングリストにも
02:28
except if you want to have a talk
当てはまりますが 例外もあって
02:30
that's beautiful, inspiring or funny.
「美しい」「刺激的」「可笑しい」
02:32
Then, you should be brief. (Laughter) But other than that,
というのを狙うなら簡潔に
02:34
talk until they drag you off the stage.
そうでなければ 引きずり下ろされるまで話し続けましょう
02:36
(Laughter)
(笑い)
02:39
Now, while ...
それから…
02:41
(Applause)
(拍手)
02:43
While you're pushing the clock, there's a few rules to obey.
講演する上で守るべきルールがあります
02:49
I found these rules out by comparing the statistics
私はこのルールを 好かれているTalkと
02:52
of four-word phrases
好かれていないTalkの
02:54
that appear more often in the most favorite TEDTalks
それぞれに現れる4語のフレーズの
02:56
as opposed to the least favorite TEDTalks.
統計を取ることで見つけました
02:59
I'll give you three examples.
3つ例を挙げます
03:01
First of all, I must, as a speaker,
まずなにより 講演者として
03:03
provide a service to the audience and talk about what I will give you,
聴衆に対して「自分に提供できる」ことを話し
03:05
instead of saying what I can't have.
「自分にはできない」と言うべきではありません
03:08
Secondly, it's imperative
第2に「ニューヨークタイムズ」の
03:10
that you do not cite The New York Times.
引用は絶対避けてください
03:12
(Laughter)
(笑い)
03:14
And finally, it's okay for the speaker -- that's the good news --
最後に…これは良い報せですが…講演者が
03:16
to fake intellectual capacity.
知ったかぶりをするのは構いません
03:19
If I don't understand something, I can just say, "etc., etc."
「分らない」ときにはただ「エトセトラ エトセトラ」と言えばいいのです
03:21
You'll all stay with me.
みんな付いてきてくれますから
03:24
It's perfectly fine.
全く問題ありません
03:26
(Applause)
(拍手)
03:28
Now, let's go to the visuals.
次は 見た目の話です
03:32
The most obvious visual thing on stage is the speaker.
ステージの上で一番目に付くものは 講演者本人です
03:34
And analysis shows if you want to be
分析の結果 最も好かれる
03:37
among the most favorite TED speakers,
講演者の仲間入りをするには
03:39
you should let your hair grow a little bit longer than average,
髪の毛を平均より少し長めにのばし
03:41
make sure you wear your glasses and be slightly more dressed-up
眼鏡を忘れずにかけ 平均的な講演者よりも
03:44
than the average TED speaker.
きちっとした身なりをしてください
03:47
Slides are okay, though you might consider going for props.
スライドだけでなく 小道具も使ってみましょう
03:49
And now the most important thing,
そして とても重要なのは
03:52
that is the mood onstage.
ステージの雰囲気です
03:54
Color plays a very important role.
色がとても重要な役割を果たします
03:56
Color closely correlates
Webサイトでの講演の評価は
03:58
with the ratings that talks get on the website.
色と密接な関連があります
04:00
(Applause)
(拍手)
04:03
For example, fascinating talks
たとえば「魅力的」な講演は
04:05
contain a statistically high amount
統計的に
04:07
of exactly this blue color, (Laughter)
平均的な講演と比べて
04:09
much more than the average TEDTalk.
紫色を多く含んでいます
04:11
Ingenious TEDTalks, much more this green color,
「独創的」な講演は緑色が多く…
04:13
etc., et.
エトセトラ エトセトラ
04:15
(Laughter) (Applause)
(拍手)
04:17
Now, personally, I think
このような分析をしたのは
04:24
I'm not the first one who has done this analysis,
私が初めてではないと思われます
04:26
but I'll leave this
しかしこれは皆さんの
04:28
to your good judgment.
ご判断にお任せしましょう
04:30
So, now it's time to put it all together
それでは これらすべてをまとめて
04:33
and design the ultimate TEDTalk.
究極のTEDTalkを作ってみましょう
04:35
Now, since this is TEDActive,
ここはTED Activeですから
04:37
and I learned from my analysis
分析でわかったことを
04:39
that I should actually give you something,
何か形にすべきでしょう
04:41
I will not impose the ultimate
究極のTalkや最悪のTalkを
04:43
or worst TEDTalk on you,
押しつけようとは思いません
04:45
but rather give you a tool to create your own.
皆さんがご自分のを作れる
04:47
And I call this tool the TEDPad.
ツールを用意しました TED Padです
04:49
(Laughter)
(笑い)
04:52
And the TEDPad is a matrix
このTED Padを使うと
04:55
of 100 specifically selected,
特別に選んだ100個の
04:57
highly curated sentences
精選された文章を組み合わせ
04:59
that you can easily piece together to get your own TEDTalk.
ご自分のTEDTalkを作っていただくことができます
05:02
You only have to make one decision,
決断すべきことは1つだけ
05:07
and that is: Are you going to use the white version
良いTalkのためのホワイトバージョンを使って
05:09
for very good TEDTalks,
「創造性」や
05:11
about creativity, human genius?
「人類の英知」についての話をするか
05:13
Or are you going to go with a black version,
それともブラックバージョンにして
05:15
which will allow you to create really bad TEDTalks,
すごくまずいTEDTalkを作り
05:17
mostly about blogs,
「ブログ」や「政治」なんかの
05:19
politics and stuff?
話をするかです
05:21
So, download it and have fun with it.
ぜひダウンロードしてお試しください
05:23
Now I hope you enjoy the session.
このセッションを楽しんでいただけたなら幸いです
05:25
I hope you enjoy designing your own
ご自分の究極のTEDTalkや
05:28
ultimate and worst possible TEDTalks.
最悪のTEDTalkをお作りください
05:30
And I hope some of you will be inspired for next year
そして皆さんの中の誰かが触発されて
05:32
to create this, which I really want to see.
来年のTEDで このような講演を聞かせていただけるのを楽しみにしています
05:35
Thank you very much.
ご清聴ありがとうございました
05:38
(Applause) Thanks.
(拍手)
05:40
Translated by Takahiro Shimpo
Reviewed by Yasushi Aoki

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About the Speaker:

Sebastian Wernicke - Data scientist
After making a splash in the field of bioinformatics, Sebastian Wernicke moved on to the corporate sphere, where he motivates and manages multidimensional projects.

Why you should listen

Dr. Sebastian Wernicke heads the data science department at Solon, a Munich-based consultancy supporting companies and investors in media, entertainment, telecoms, and technology industries. Wernicke originally studied bioinformatics and previously led the strategy and growth of Seven Bridges Genomics, a Cambridge-based startup that builds platforms for genetic analysis.

Before his career in statistics began, Wernicke worked stints as both a paramedic and successful short animated filmmaker. He's also the author of the TEDPad app, an irreverent tool for creating an infinite number of "amazing and really bad" and mostly completely meaningless talks. He's the author of the statistically authoritative and yet completely ridiculous "How to Give the Perfect TEDTalk."

More profile about the speaker
Sebastian Wernicke | Speaker | TED.com