Threads vs. Twitter: What’s the Difference?
The Instagram-linked app joins the crowded microblogging fray
The Instagram-linked app joins the crowded microblogging fray
If you’re wondering what it’s like to use the new Threads app, just close your eyes and picture Twitter but with a lot less Elon Musk—and that’s exactly the point.
Meta—owner of Instagram, Facebook and WhatsApp—on Wednesday launched its latest service, called Threads. While linked to Instagram (you even need an Instagram account to sign up for Threads), the new app’s primary focus is sharing short snippets of text. Users can post up to 500 characters or share videos up to five minutes long.
Welcome to Mark Zuckerberg’s new Metaverse. No virtual-reality spectacles or legless 3-D avatars here. Just good ol’ fashioned words…in a good ol’ fashioned social-media feed…on your good ol’ fashioned smartphone.
“There’s a hunger for something new,” Connor Hayes, Meta’s vice president of product, said in an interview. He added that public figures and creators have specifically been looking for an alternative to Twitter that “feels more productive and positive.”
Since Musk took over Twitter in October, the company has had numerous technical issues, changed its blue-check-mark verification policies and faced criticism from users and advertisers for how it moderates content. This past weekend, Musk limited how many posts users could see, saying he wants to combat “extreme levels of data scraping.”
That’s left a potential opening for competitors. There’s Mastodon, Bluesky, Spill. Is Threads any better than those? Are there privacy concerns—as with other Meta apps? Is it easy to set up and close a Threads account? Can Twitter actually be beaten?
Here are our answers and first impressions after using the app for the past day.
Threads is Meta’s latest social-media app, and this one directly takes on Twitter with short missives you can share with followers. It lets you post text, photos, links and videos.
Thanks to some serious Twitter copying and pasting, Threads is simple to use. Download the iOS or Android app and you’ll be prompted to log in with your Instagram account and fill out your Threads profile. You can choose to keep following the same people you follow on Instagram or pick just some of them—or none at all.
The Home tab includes a feed of posts. Tap the button with an abstract-looking paper and pen to compose a new Thread, and tap the paper clip icon to add a photo or video. You can mention other people by using the @ symbol in front of their usernames and “repost.”
The app is available in more than 100 countries, though not in the European Union.
You can’t join Threads without an Instagram account, but the new service operates as its own app. Do we really need another app on our phones? Nope, but here we are.
If you really don’t want to download another app, you can access the service from the Threads.net website, similar to how you can use Instagram in a browser. Hayes said there are no plans right now for a dedicated Mac or Windows app.
Because of the Instagram integration, setting up Threads is fast and easy. Quitting it—not so much. You can’t completely delete your Threads profile unless you also delete your Instagram account, the app’s privacy policy says.
If you really don’t want to use Threads but want to keep Instagram, you can deactivate your account, which hides your profile, Threads, replies and likes. Deactivating Threads doesn’t impact your Instagram account.
Adam Mosseri, the head of Instagram, on Thursday said that because Threads is powered by Instagram, it’s currently one account. “But we’re looking into a way to delete your Threads account separately,” he said on Threads.
On the surface Threads is a Twitter clone, but dig deeper and you can find some real differences:
It takes just a few minutes of using Threads to see where Meta rushed things. “There are a bunch of features that are coming that weren’t quite ready for launch,” Hayes said.
Here are some features found on Twitter that we expect on Threads:
Well, us. (Follow WSJ here, Joanna here and Ann-Marie here!) But we certainly cannot sing like Shakira and Nick and Joe Jonas. Or act like Zooey Deschanel and Beanie Feldstein. Or tell jokes like Ellen DeGeneres and Jack Black. Or stream shows like Netflix or cook up burgers like Shake Shack. Or even take off into the skies like American Airlines. Big names and companies seem to be joining the service by the minute.
Check the Threads listing in the Apple App Store and you’ll see that Meta may collect loads of data from the app: Health & Fitness, Purchases, Financial Info, Location, Contacts…The list goes on.
Hayes said that list doesn’t give much context about why or under what circumstances that sort of data would be used. Instead, he pointed us to Threads’s two privacy policies: the Meta privacy policy and a new supplemental Threads-specific policy due to the coming ActivityPub integration. Threads also allows you to designate your account and your posts as public or private.
Still, this is Meta we’re talking about. If you have been a Facebook or Instagram user, it has built up quite a bit of data about you over the years. Expect this to just be another app that feeds into that.
It sure looks like the closest thing to it. Threads has an edge over most Twitter competitors because it uses Instagram to immediately build your following and populate your feed. Heck, in just the first four hours, it had over five million sign-ups, according to Zuckerberg’s own Thread. The app hit 30 million sign-ups as of Thursday morning, he posted.
But as Zuckerberg (or an actor playing him) was once famously told, sort of: “Thirty million sign-ups isn’t cool. You know what’s cool? A billion sign-ups.”
(OK, that might not happen this week, but it’s probably what he’s aiming for.)
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Technology and semiconductor shares fell sharply as investors questioned the debt financing the AI infrastructure boom and confronted higher rates and Chinese competition.
Technology and semiconductor shares fell sharply as investors questioned the debt financing the AI infrastructure boom and confronted higher rates and Chinese competition.
A sharp technology sell-off has exposed a new anxiety on global markets: whether the enormous borrowing behind the artificial-intelligence infrastructure boom can generate sufficient returns as interest rates rise and Chinese competition intensifies.
The artificial-intelligence investment boom has powered technology shares, semiconductor manufacturers and data-centre operators to extraordinary heights. Last week, investors were given a reminder that much of this expansion is being built with borrowed money.
The technology-heavy Nasdaq Composite fell 4.5 per cent over the week ended October 16, its weakest performance since late June. Semiconductor shares suffered an even deeper correction, with the Philadelphia Semiconductor Index losing about 11.4 per cent.
The selling spread quickly through global markets. Micron Technology fell 14.6 per cent over the week, while South Korea’s Samsung Electronics and SK Hynix dropped approximately 18 per cent and 24 per cent respectively.
This was more than a routine bout of profit-taking. Investors were reassessing three interconnected risks: higher interest rates, the rapidly expanding debt burden attached to AI infrastructure and the prospect of stronger competition from Chinese memory-chip manufacturers.
Artificial intelligence requires a physical infrastructure network of enormous scale. Data centres must be built, advanced processors purchased, power supplies secured and cooling systems installed before customers begin generating meaningful revenue from them.
Technology companies are increasingly supplementing their own cash with corporate bonds, syndicated loans, equipment leases, private credit and project-level financing.
JPMorgan describes the emerging funding model as a combination of conventional corporate borrowing and project finance tied to individual data-centre assets. In Australia, the Reserve Bank estimates that syndicated loans accounted for approximately three-quarters of data-centre financing during 2025 and 2026 to date.
The numbers are becoming large enough to affect broader credit markets. The Federal Reserve Bank of Dallas has cited Wall Street estimates suggesting AI-related investment-grade bond issuance could approach US$300 billion in 2026 alone.
That borrowing is not automatically problematic. Debt can be an efficient way to finance long-lived infrastructure when future revenue is sufficiently predictable. The concern is that AI technology, customer demand and computing economics are changing much faster than the repayment schedules attached to the assets.
A data centre financed today may carry debt for years. Investors must therefore make assumptions about future utilisation rates, electricity prices, chip performance, customer concentration and the amount businesses will ultimately pay for AI computing.
When interest rates rise, those assumptions become less forgiving.
September’s US inflation data intensified the pressure. Consumer prices increased 3.7 per cent over the year, ahead of market expectations and up from 3.4 per cent in August.
The hotter reading reduced confidence that interest rates would fall quickly and pushed bond yields higher. That matters particularly for companies whose valuations depend on profits expected well into the future, as well as highly leveraged infrastructure operators that may need to refinance.
CoreWeave has emerged as a closely watched test case. The specialist cloud-computing company has accumulated substantial debt and lease obligations to build AI capacity, while relying on a concentrated group of large technology customers.
Its shares fell sharply during the sell-off, while the cost of insuring its debt against default climbed. CoreWeave has argued that its contracted backlog more than covers its obligations and that financial markets do not always understand its business model. Nevertheless, its securities have become a proxy for investor confidence in debt-funded AI infrastructure.
Oracle, another major investor in AI computing capacity, fell 8.8 per cent in Friday trading, while CoreWeave dropped 15.5 per cent.
The question is shifting from how much AI infrastructure can be built to how profitably it can be operated.
Interest rates were not the only catalyst. Reports of advances by Chinese memory-chip producer ChangXin Memory Technologies raised concerns that lower-cost Chinese products could increase competition across the global semiconductor industry.
Memory chips are essential to AI systems, but the industry is historically cyclical. Periods of tight supply and high pricing can encourage rapid investment, eventually producing oversupply and falling margins.
The prospect of a well-funded Chinese competitor expanding its technological capabilities unsettled investors in Samsung, SK Hynix and Micron. It also demonstrated that AI-related demand does not insulate chipmakers from conventional competitive pressures.
That combination—slower rate cuts, more expensive financing and potentially cheaper supply—challenged the assumption that every company exposed to AI would enjoy continually expanding margins.
The sell-off does not establish that the AI boom is ending. Demand for computing power remains strong, the largest technology companies continue to generate formidable cash flows and many infrastructure projects are backed by long-term customer contracts.
What has changed is the market’s willingness to overlook the price and financing structure of that growth.
The most resilient companies are likely to be those able to fund investment from operating cash flow, secure long-duration customers and demonstrate that new capacity will earn returns comfortably above its financing costs.
More speculative operators may face greater scrutiny, particularly where debt is expensive, customers are concentrated or expected revenue depends on demand that has not yet materialised.
For Australian investors, the lesson extends beyond US technology shares. Local data-centre operators, infrastructure funds, electricity suppliers and property groups are increasingly exposed to the same investment cycle.
Artificial intelligence may remain one of the defining growth themes of the decade. But last week’s correction showed that enthusiasm for the technology does not eliminate financial discipline.
The next stage of the AI boom will be judged not only by computing power, model performance or demand for chips, but by something more traditional: whether the assets being financed can generate enough cash to repay the money borrowed to build them.
Nasdaq Composite: Down 4.5 per cent for the week ended October 16, 2026
Philadelphia Semiconductor Index: Down approximately 11.4 per cent
Micron Technology: Down approximately 14.6 per cent
Samsung Electronics: Down approximately 18 per cent
SK Hynix: Down approximately 24 per cent
US September inflation: 3.7 per cent annually
Estimated 2026 AI-related investment-grade issuance: Approximately US$300 billion
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