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Reddit Brings Back its r/place Communal Digital Art Project in April

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Reddit Brings Back its r/place Communal Digital Art Project in April


In the time of NFTs and emerging digital art, this seems like the perfect project for the online community.

This year, marking April Fool’s Day (4/1), Reddit is bringing back its popular r/place project, which enables Reddit users to each control a digital pixel on a larger, community-built digital canvas.

As you can see here, on April 1st, a new place icon will appear alongside the search bar at the top of the app. Tapping on that will enable the user to control a single spot on the broader image.

As explained by Reddit:

Once people navigate to r/place, they’ll see a communal 1000×1000 tile canvas where (logged in) redditors can place a tile or pixel of their color choice (once every 5 minutes by tapping or clicking anywhere on the canvas). People who are logged out of Reddit can view the canvas unfolding in real-time, but can’t place a tile.”

In order to make the larger image into anything legible, Redditors will need to work together, which they’ve done in the past to create complex collages of varying icons, flags and other works.

Reddit r/place example

Reddit initially ran its r/place initiative back in 2017 (the above image being the final result), and users have been calling for its return ever since.

When we first ran r/place in 2017, more than one million redditors placed approximately 16 million tiles on a blank communal digital canvas – resulting in a collective digital art piece. Every year since then, users have asked us to bring it back. It was hands down one of our most popular April Fools’ Day experiences.”

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And as noted, given the renewed focus on digital art, with the rise of NFTs and other projects, like Beeple’s ‘First 5000 Days’, now seems like the perfect time to bring it back.

Beeple's 'First 5,000 Days'

This image, a collection of Beeple’s daily digital artworks, sold for $69.3 million at auction last year, and really legitimized the digital art movement, which sparked the current NFT trend.

Since, of course, NFTs have become a hive of speculation and scams, with everyone that can put together a few basic images seeking to cash in however they can, with ‘rug pulls’ now so common that it’s almost not worth buying into a new project.

And really, the idea that any of these digital images are going to be worth significant money in future seems spurious at best – but even so, there’s huge interest in digital art, which could make Reddit’s r/place project even more popular this time around.

Or it could be a total mess. But that’s part of the beauty of it – and while the end result might not end up in a million dollar art sale, it’ll still be interesting to see what the modern Reddit community ends up reflecting, and which themes and topics shine through in the millions of edited pixels.

You can watch it unfold for yourself in the app, with r/place going live later this week.



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TikTok Rolls Out Comment Downvotes to All Users

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TikTok Rolls Out Comment Downvotes to All Users

After testing them out in the live environment over the last six months, TikTok has today announced that it’s rolling out comment downvotes for all users, as a means to flag inappropriate responses to video clips.

As you can see in this example, TikTok’s ‘Thumbs Down’ comment downvote option will be displayed at the far right of each comment, providing a quick and easy way for users to tag such, in order to help TikTok identify negative behaviors in the app.

Which is the key focus – rather than being an audience response element, like downvotes on Reddit, TikTok’s approach is actually to use the indicator as a means to weed out negative behaviors.

As TikTok explained back in April:

“We’ve started testing a way to let individuals identify comments they believe to be irrelevant or inappropriate. This community feedback will add to the range of factors we already use to help keep the comment section consistently relevant and a place for genuine engagement. To avoid creating ill-feeling between community members or demoralize creators, only the person who registered a dislike on a comment will be able to see that they have done so.

So dislike counts won’t be public, as they are on Reddit, with the purpose, again, being to help TikTok’s moderation team get on top of negative trends, as flagged by its users.

How it will likely work in this respect is that downvoted comments will be displayed to TikTok mods in ascending order, based on total downvote activity across the app, which will then enable them to them wade through the list and pick up on rising negative trends, providing another way to detect and address such in their process.

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That could also help to limit the use of the feature for ‘brigading,’ or using it as a means to launch targeted attacks on people or opinions based on alternative motivations. You can imagine how, for example, people might try to use this feature as a means to downvote conflicting political opinions into oblivion, but as the downvotes themselves don’t impact public display, and are only an indicator for TikTok’s moderation team, that’s less likely to become an issue.

Which would be part of the reason why TikTok’s comfortable pushing ahead with a full launch – and it may well be a good way to help keep things more civil, and more positive in the app.

TikTok actually first began its comment downvote experiment back in 2020, with some researchers spotting the feature in early testing.

TikTok comment downvotes

Both Facebook and Twitter have also been experimenting with comment downvotes for similar purpose, not as a means to better surface or hide user responses, but to help identify negative behaviors based on what users think is bad, which effectively then helps to improve automated algorithms to detect such in future.

Which could be a better use of the option – though it is worth noting that Reddit’s public downvote system does help the platform highlight more relevant conversations and topics, based on actual responses from humans, as opposed to algorithmically identified trends that are guided by clicks, Likes, dwell time, shares, etc.

The problem with algorithmic trends is that divisive, negative content is amplified via this process, because sparking an emotional response, like anger, drives more people to comment and share. The algorithm then takes as an indicator that more people might want to see it, based on engagement response. The system itself has no way of determining the intent of the content, it only goes on binary signals – which means that triggering more reactions, however you can, is the best way to maximize exposure.

That doesn’t happen on Reddit, because such posts are rapidly downvoted into the doldrums of the app.

Giving actual people the chance to drive exposure in this respect may be a more beneficial approach overall, but the bigger players will never go with it because it also makes users less likely to comment, likely because they’re also concerned about their own remarks being downvoted to the pit.

Previous analysis has suggested that more than 98% of Reddit’s monthly active users don’t ever post or comment in the app, which is likely a key consideration that would limit take-up of such in other apps.

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So they go with automated algorithms instead, which also then enables them to wash their hands of any responsibility for whatever type of content gains traction and doesn’t across their networks.

Negative content drives more engagement, and thus, more reach in their apps? ‘We don’t know, it’s based on how users respond, factoring in all forms of engagement, so we’re not responsible for whatever that leads to’.

It does seem that a human-moderated process, via public downvotes, could improve the flow of information in this respect. But the impacts on engagement could also be significant.

In any event, TikTok’s comment downvotes are not designed to help guide the conversation, and could be a valuable supplementary measure to detect rising negative trends.

TikTok says that comment downvotes are being released globally in the app from today.



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