While the “Like” button on Facebook has traditionally been a quick and fun way to respond to a post, the truth is that it’s not always appropriate. “Liking” certain posts — say, the news of a pet’s death or a post about global warming — just feels wrong. Thankfully, starting today, that’s about to change. The social network has just announced a brand new feature called Reactions (which we’ve already heard about a few times ), which is essentially an extension of the Like button. Now, in addition to the thumbs-up Like we’re all familiar with, there’s Love, Haha, Wow, Sad and Angry. Love is signified by a heart symbol while the rest are animated emoji. To see them, simply press and hold on the Reactions button — it’s where the thumbs-up Like button is currently — select which one you want, and release. If the post has a slew of different reactions to it, you’ll see a summary of the three most frequent reaction icons. On the other end, the person receiving them will get notifications saying someone “reacted” to the post. Introducing Reactions from Facebook on Vimeo . “People come to Facebook and share all kinds of things, ” says Sammi Krug, the product manager behind Reactions. “And we kept hearing feedback from people that there wasn’t an easy way to express empathy for these different kinds of posts.” Zuckerberg in particular took the user feedback to heart and pulled a bunch of people together to start work on a solution about a year or so ago. From there, the team did a ton of research — from conducting surveys to analysis of the most popular stickers — to figure out just what reactions to add. When they whittled it down to about six, Facebook then began testing it — you can see we saw a sneak peek of Reactions as early as last October — in about seven different countries. “One of the things we really wanted to be careful of, is will this translate well” says Krug. “We wanted these reactions to be globally understood.” That’s one of the reasons Reactions is launching with just five additional icons instead of the original six that we saw in October. That’s because the “Yay” reaction just didn’t test well globally and was a little too vague in some markets. The rest, however, proved to be popular enough, with Love being the most popular out of all the new Reactions (The Like button, however, still reigned supreme). So does that mean we’re stuck with the six or so Reactions we have now? Not at all. “Once this actually rolls out, we’ll learn more about how people use the feature, ” says Krug. “We’ll continue to iterate it over time, based on user feedback.” Reactions will roll out globally starting today on iOS , Android , the desktop as well as the mobile browser. You’ll start to see the change occur over the next couple of days, though bear in mind that you do need to be on the latest version of the Facebook app to get the feature. Still, we had to ask, why isn’t there a “dislike” button? “It would have been too binary, ” says Krug. “This way, though, you’ll have more ways to express yourself. That’s the goal.” Source: Facebook
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Facebook officially expands beyond the Like with Reactions
schwit1 writes: Here’s a tricky task. Pick a photograph from the web at random. Now try to work out where it was taken using only the image itself. If the image shows a famous building or landmark, such as the Eiffel Tower or Niagara Falls, the task is straightforward. But the job becomes significantly harder when the image lacks specific location cues or is taken indoors or shows a pet or food or some other detail. Nevertheless, humans are surprisingly good at this task. To help, they bring to bear all kinds of knowledge about the world such as the type and language of signs on display, the types of vegetation, architectural styles, the direction of traffic, and so on. Humans spend a lifetime picking up these kinds of geolocation cues. So it’s easy to think that machines would struggle with this task. And indeed, they have. Today, that changes thanks to the work of Tobias Weyand, a computer vision specialist at Google, and a couple of pals. These guys have trained a deep-learning machine to work out the location of almost any photo using only the pixels it contains. Read more of this story at Slashdot.