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@RuinDig

RuinDig@RuinDig

  • 2,418フォロー
  • 807フォロワー
  • 87リスト
Stats Twitter歴
3,111日(2015/09/23より)
ツイート数
257,686(82.8件/日)

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2022年05月17日(火)48 tweetssource

5月17日

@needle

Kenji Iguchi@needle

お、気がつけばQuest版のVRChatとRec RoomがそれぞれDestinations APIに対応してるのか。ここのボタンを押すとただQuest版VRChatが起動するというだけでなく、VRChat Homeをすっ飛ばして直接The Black Catワールドに遷移するディープリンクになっている。 pic.twitter.com/Aya0JBPeGB

Retweeted by RuinDig

retweeted at 19:07:56

5月17日

@Yam_eye

山中俊治 Shunji Yamanaka@Yam_eye

私「ウマの後肢は、カカトの骨が大きく真後ろに飛び出していて、これを腱が引っ張ることで地面を蹴るんですね」
石黒浩先生「うわ、まるでロボットじゃないですか。ワイヤー駆動でよく使う構造です」
と言うような話題で盛り上がりました。
「プロトログ - 山中俊治デザインの発生学」展 pic.twitter.com/SDVoYIKtW3

Retweeted by RuinDig

retweeted at 18:48:06

5月17日

@livedoornews

ライブドアニュース@livedoornews

【在庫改善】ビデオカード価格正常化へ、価格を高騰させた仮想通貨需要が減速
news.livedoor.com/article/detail

ASUSの共同CEOであるS.Y.Hsu氏によると、暗号資産のマイニング(採掘)の需要が大きく減少。PCゲーマーからの需要を中心としたビデオカード本来の市場に戻りつつあるとしている。 pic.twitter.com/1raTiBVXxf

Retweeted by RuinDig

retweeted at 17:23:59

5月17日

@Centrairairport

中部国際空港セントレア@Centrairairport

本日からセントレア第1ターミナル3階中央にテレワークブースが設置されました💻️最近駅などでもよく見かけますね!待ち時間にお仕事やWeb会議など、オンライン予約で15分220円からご利用いただけます。電源や個別Wi-Fiも用意されていますよ。
www.centrair.jp/service/telewo pic.twitter.com/BhX11Nabra

Retweeted by RuinDig

retweeted at 11:18:59

 

表示拒否

retweeted at xx:xx:xx

5月17日

@livedoornews

ライブドアニュース@livedoornews

【老舗】和菓子店「紀の国屋」廃業、74年の歴史に幕
news.livedoor.com/article/detail

「相国最中」「おこじゅ」「あわ大福」などで知られ、東京・神奈川に全23店舗を展開。16日をもって廃業すると記し「紀の国屋のお菓子を愛してくださった皆様には大変申し訳ない気持ちでいっぱいです」と伝えた。

Retweeted by RuinDig

retweeted at 02:31:51

5月17日

@paraga

Parag Agrawal@paraga

There are LOTS of details that are very important underneath this high-level description. We shared an overview of the estimation process with Elon a week ago and look forward to continuing the conversation with him, and all of you.

Retweeted by RuinDig

retweeted at 01:32:14

5月17日

@paraga

Parag Agrawal@paraga

Unfortunately, we don’t believe that this specific estimation can be performed externally, given the critical need to use both public and private information (which we can’t share). Externally, it’s not even possible to know which accounts are counted as mDAUs on any given day.

Retweeted by RuinDig

retweeted at 01:32:11

5月17日

@paraga

Parag Agrawal@paraga

Our actual internal estimates for the last four quarters were all well under 5% – based on the methodology outlined above. The error margins on our estimates give us confidence in our public statements each quarter.

Retweeted by RuinDig

retweeted at 01:32:08

5月17日

@paraga

Parag Agrawal@paraga

The use of private data is particularly important to avoid misclassifying users who are actually real. FirstnameBunchOfNumbers with no profile pic and odd tweets might seem like a bot or spam to you, but behind the scenes we often see multiple indicators that it’s a real person.

Retweeted by RuinDig

retweeted at 01:32:05

5月17日

@paraga

Parag Agrawal@paraga

Each human review is based on Twitter rules that define spam and platform manipulation, and uses both public and private data (eg, IP address, phone number, geolocation, client/browser signatures, what the account does when it’s active…) to make a determination on each account.

Retweeted by RuinDig

retweeted at 01:31:58

5月17日

@paraga

Parag Agrawal@paraga

Our estimate is based on multiple human reviews (in replicate) of thousands of accounts, that are sampled at random, consistently over time, from *accounts we count as mDAUs*. We do this every quarter, and we have been doing this for many years.

Retweeted by RuinDig

retweeted at 01:31:56

5月17日

@paraga

Parag Agrawal@paraga

Now, we know we aren’t perfect at catching spam. And so this is why, after all the spam removal I talked about above, we know some still slips through. We measure this internally. And every quarter, we have estimated that <5% of reported mDAU for the quarter are spam accounts.

Retweeted by RuinDig

retweeted at 01:31:53

5月17日

@paraga

Parag Agrawal@paraga

Our team updates our systems and rules constantly to remove as much spam as possible, without inadvertently suspending real people or adding unnecessary friction for real people when they use Twitter: none of us want to solve a captcha every time we use Twitter.

Retweeted by RuinDig

retweeted at 01:31:45

5月17日

@paraga

Parag Agrawal@paraga

The hard challenge is that many accounts which look fake superficially – are actually real people. And some of the spam accounts which are actually the most dangerous – and cause the most harm to our users – can look totally legitimate on the surface.

Retweeted by RuinDig

retweeted at 01:31:43

5月17日

@paraga

Parag Agrawal@paraga

We suspend over half a million spam accounts every day, usually before any of you even see them on Twitter. We also lock millions of accounts each week that we suspect may be spam – if they can’t pass human verification challenges (captchas, phone verification, etc).

Retweeted by RuinDig

retweeted at 01:31:39

5月17日

@paraga

Parag Agrawal@paraga

Some final context: fighting spam is incredibly *dynamic*. The adversaries, their goals, and tactics evolve constantly – often in response to our work! You can’t build a set of rules to detect spam today, and hope they will still work tomorrow. They will not.

Retweeted by RuinDig

retweeted at 01:31:37

5月17日

@paraga

Parag Agrawal@paraga

Next, spam isn’t just ‘binary’ (human / not human). The most advanced spam campaigns use combinations of coordinated humans + automation. They also compromise real accounts, and then use them to advance their campaign. So – they are sophisticated and hard to catch.

Retweeted by RuinDig

retweeted at 01:31:33

5月17日

@paraga

Parag Agrawal@paraga

First, let me state the obvious: spam harms the experience for real people on Twitter, and therefore can harm our business. As such, we are strongly incentivized to detect and remove as much spam as we possibly can, every single day. Anyone who suggests otherwise is just wrong.

Retweeted by RuinDig

retweeted at 01:31:31

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