As a mechanical engineer who is also a writer, this sort of thing makes no sense to me. Life isn’t an either or, and it hasn’t been like that for a while. Rather than putting science against the arts, perhaps thinking about creating an economy that works for us all? would be nice

Please please please take your cyber security seriously even if you don’t consider yourself a high risk person. Here are a few easy things to start with. 1/n

Switch from WhatsApp to Signal and enable disappearing messages. Most of us cannot stop using WhatsApp entirely but at least turn off back ups to Google Drive or iCloud. 2/n

Do not have private conversations using the messaging service on any social media platform like Facebook, Instagram or Twitter. 3/n

Switch from Gmail to ProtonMail or any other secure email service provider. 4/n


Switch from Google Docs to CryptPad or RiseUp Pad.

The 2018 State of JavaScript survey is out. They got 20,000 responses and have some delicious, delicious data. I'mma thread in some highlights:

First up: JavaScript flavors. There's TypeScript at 47% adoption, a tad higher than npm's own survey results (which said 46%). npm's survey is coming up again soon and will ask about TypeScript in a lot more detail.

I really, *really* like SoJ's "would not use again" question, which lets people who've abandoned a tech self-identify. This is noticeable in the graph above with Flow users -- 41% of people who've used Flow say they wouldn't use it again.

Now JavaScript frameworks. It's been a full year since npm's survey, so these numbers differ from ours in the directions I expected:
React 65% (vs. 60%)
Vue 29% (vs. 24%)
Ember 5% (vs 4%, I was expecting a bigger rise)

But there's a shocker in here: Angular.

npm's survey had Angular at 40% last year and SoJ has it at either:
- 58% (if you include those who don't want to use it again)
- 24% (if you count only those who like it)
Since npm's question didn't ask if they intend to *continue* using it I think that might explain this.

Two years ago on a weekend, I built a tool to make it easier to evaluate Twitter accounts. Since then 36590 people used it to analyze 55390 different Twitter accounts.

Over the last months @mmkaradeniz and I made a new version. We launched it last night:

@accountanalysis doesn't use machine learning or AI „magic“. Instead of telling users if an account is authentic or not, it helps them to evaluate the accounts themselves.

It visualizes the different features (date, time, type, app, etc.) of Tweets to make them interpretable. /1

@accountanalysis The core concept is still the same, but it looks much better and is easier to operate. Not only for the users, but us developers as well. Enabling us to continuously roll out new features in the future.

Side-by-side screenshots of the old and new version. /2

@accountanalysis Some people had questions what different charts displayed and how they could be interpreted. There are now explanations for all charts, that can be toggled on and off at any time. /3

@accountanalysis The selected/retrieved Tweet count moved to the top to make it clear that not all Tweets of an account are analyzed. 3200 is the API limit by Twitter. It's possible to get more through the Premium API, but I don't think people would pay $100+ for the analysis of one account. /4

The New York Times article about SlateStarCodex is finally out and it is...bad. There's a lot I could parse, but let me just walk you through one paragraph that is so misleading as to be

Take the first sentence of this paragraph. Now, technically the clause--"who proposed a link between race and IQ"--could simply modify "Murray" and have nothing to do w/ SSC.

But 99% of readers are going to assume that the clause actually defines SSC's alignment with Murray. In other words, the author is strongly implying that SSC shares Murray's racist beliefs.

And that would be big(!)...if it were at all true. It is not. Indeed, if you go to the hyperlink, you'll find that SSC's purported "alignment" has nothing to do with Murray's "Bell Curve."

What SSC & Murray agree about is that poverty is partly hereditable and thus very sticky, so much so that the proposition job retraining programs will meaningfully address mass economic disruption is a pie-in-the-sky fantasy.

A quick thread on intelligence analysis in the context of cyber threat intelligence. I see a number of CTI analysts get into near analysis paralysis phases for over thinking their assessments or over obsessing about if they might be wrong. (1/x)

Consider this scenario. A CTI analyst identifies new intrusions and based on the collection available and their expertise note that the victims are all banks. Their consumer wants to know when threats specifically target banks (not just that banks are victims).

The CTI analyst has, from their collection, at this time, and based on their expertise enough to make an activity group (leveraging the Diamond Model in this example) that meet's the requirement of their consumer. So what's the problem?

The CTI analyst begins to over think it. "What if I had more collection? Would my analysis change? I really don't *know* they aren't also targeting mining companies in Australia as I don't have collection there."

The analyst knows their analysis is going to be shared. Maybe even public. "What if another team or professional intelligence firm has more collection and ends up noting that it isn't banking specific at all. Banks are victims, not targets. Will my consumer distrust me later?"