With Elon Musk killing off third-party Twitter apps with zero grace period and zero class, one of the absolute staples of my techie lifestyle was abruptly taken away from me.

Ever since Tweetbot launched in April 2011, it has been on my iPhone home screen. For over a decade, it was the literally first app I'd open when I wake up. Whenever I had a few minutes to spare because I was waiting for files to transfer or I was waiting in line, I would open Tweetbot. When I was following some breaking news in real-time; Kobe's death, Lakers championships, good presidencies, one shitty presidency, many world-wide tragedies, but even more inspiring moments.

Tweetbot — specifically, it's iCloud timeline position syncing — was one of the two anchors that kept me happily committed to the Apple ecosystem.

Even though Tweetbot is no more, its legacy will carry on in the form of Ivory for Mastodon.

Long live, Tweetbot.

With Elon's hostile takeover of Twitter and massive layoffs — which includes key engineers who maintain the infrastructure — it's starting to sound like Twitter is one server crash away from losing everything…

Hello, Mastodon. You're lookin' kinda good today.

https://techhub.social/@mel

The Verge:

Instagram has begun testing a way to share posts with a more limited group of friends. Called favorites, the feature attempts to improve on earlier social network friend lists, encouraging users to post more often by giving them more control over their audience. If it rolls out broadly, the feature could turn Instagram into the default place to share for more groups of friends — and reshape the social dynamics of Instagram in the process.

Before Instagram developed favorites, users tried to build versions of it for themselves. They created so-called “Finstagrams” — private Instagram accounts followed only a handful of their closest friends. Or they posted photos publicly and then deleted them after their close friends had acknowledged them with a like.

This is something I've felt should be standard across any mainstream social network: the ability to distinguish Friends from Followers so users have more control over what they share.

Twitter makes the assumption that when you follow a person, you want to follow all of their posts. But I don't think that's a good assumption — I follow a person because I want to follow a particular interest they post about.

How many of you guys are techies who just love to see your favorite tech personalities blow up your feeds with TV shows or football or politics that you don't care about?

I've always loved the way Pinterest was set up — the main focus is you follow a person's interests in the form of Pinterest Boards, not the person.

If micro.blog is truly meant for microblogging as opposed to being a traditional social network, then we should make it easy to follow an person's interests (i.e. an account's categories).

One possible solution is presenting interests/categories like this: @username/channel

So some examples would be:

• @theverge/apple
• @gruber/baseball
• @parislemon/football
• @amc/TheWalkingDead_EST
• @amc/TheWalkingDead_PST
• @espn/nba_highlights
• @espn/warriors_news
• @samsung/usa
• @samsung/korea

Granted, most of those examples are with real-time live-tweeting in mind, but you get the idea.

Of course, the simplest alternative solution is to say, "just create another account", but keeping all categories under the same roof strengthens the main account. Plus, nobody likes to rebuild a following for a new account from scratch.

The idea is not to just "be better than Twitter"; I'm trying to solve the problem that following specific interests should be much more efficient than what is currently out there.

I'm embracing the idea that microblogging does not equal tweeting. And I'd argue that if microblogging is really about sharing content instead of having conversations, we should have more efficient ways of organizing what we share and how we follow it.

Benedict Evans:

This change in assumptions applies to the sensor itself as much as to the image: rather than thinking of a ‘digital camera,' I’d suggest that one should think about the image sensor as an input method, just like the multi-touch screen. That points not just to new types of content but new interaction models. You started with a touch screen and you can use that for an on-screen keyboard and for interaction models that replicate a mouse model, tapping instead of clicking. But next, you can make the keyboard smarter, or have GIFs instead of letters, and you can swipe and pinch. You go beyond virtualising the input models of an older set of hardware on the new sensor, and move to new input models. The same is true of the image sensor. We started with a camera that takes photos, and built, say, filters or a simple social network onto that, and that can be powerful. We can even take video too. But what if you use the screen itself as the camera - not a viewfinder, but the camera itself? The input can be anything that the sensors can capture, and can be processed in any way that you can write the software.

Exactly why social media has evolved from text status updates to photos & video to visual storytelling.

Meanwhile, while we can change what a camera or photo mean, the current explosion in computer vision means that we are also changing how the computer thinks about them. Facebook or your phone can now find pictures of your friend or your your dog, on the beach, but that’s probably only the most obvious application - more and more, a computer can know what's in a image, and what it might represent. That will transform Instagram, Pinterest or of course Tinder. But it will also have all kinds of applications that don't seem obvious now, rather as location has also enabled lots of unexpected use cases. Really, this is another incarnation of the image sensor as input rather than camera - you don't type or say 'chair' or take a photo of the chair - you show the computer the chair. So, again, you remove layers of abstraction, and you change what you have to tell the computer - just as you don't have to tell if where you are. Eric Raymond proposed that a computer should 'never ask the user for any information that it can autodetect, copy, or deduce'; computer vision changes what the computer has to ask. So it's not, really, a camera, taking photos - it's more like an eye, that can see.

Andrew Watts, a teen, breaks down how his generation views all of the different social networks. Here are my highlights:

Facebook:

It’s dead to us. Facebook is something we all got in middle school because it was cool but now is seen as an awkward family dinner party we can't really leave.

Instagram:

Facebook gets all of the photos we took — the good, the bad, etc—while Instagram just gets the one that really summed up the event we went to. It is much more selective, and honestly people spend more time on the captions to make them relevant/funny.

Snapchat:

Snapchat is a somewhat intimate network of friends who I don't care if they see me at a party having fun. [...]

There aren't likes you have to worry about or comments—it’s all taken away. Snapchat has a lot less social pressure attached to it compared to every other popular social media network out there. This is what makes it so addicting and liberating. If I don’t get any likes on my Instagram photo or Facebook post within 15 minutes you can sure bet I'll delete it. Snapchat isn't like that at all and really focuses on creating the Story of a day in your life, not some filtered/altered/handpicked highlight. It’s the real you.

Tumblr:

Tumblr is like a secret society that everyone is in, but no one talks about. Tumblr is where you are your true self and surround yourself (through who you follow) with people who have similar interests. It’s often seen as a “judgment-free zone” where, due to the lack of identity on the site, you can really be who you want to be.

I've been using Snapchat for the past few months, and admittedly, it took me a while to "get it." The more I used it, I realized it's a nice way of sending photos to close friends for those "Hey I saw this and thought of you" -type moments

But then I started adding more friends. And the more friends I added, the more random, impersonal, obviously mass-sent messages started coming my way.

Most of these messages were things I'd scroll past if they were on my Instagram timeline. But no, because it was Snapchat, I'd receive a push notification for every single one. Every single selfie. Every single low-quality food porn pic. Every single video from a club that is too dark and too loud to provide any value.

It just got too annoying.

Thankfully, Instagram Direct is here and there are a few key differentiators that make it more suited for me.

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