fbpx

 

YouTube might be getting a lot more social and conversational in the near future.

TechCrunch reports the Google-owned video platform is currently testing a new in-app messaging feature on iOS and Android that will allow users to exchange clips, texts and links without ever having to leave the app.

But there’s one catch: The functionality is solely available in Canada for the time being. Google product manager Shimrit Ben Yair told Canada’s Financial Post the decision to run trials on Canadian soil has to do with the fact that it’s the country that shares videos more than anyone else in the world.

 

The messaging platform is pretty straightforward and has no specific video-centric features. Still, the move towards in-app messaging could have much larger implications for the future of YouTube.

A few months back, Google toyed around with the idea of giving certain channels the option to send direct messages to their audience. It also briefly tested with in-app messaging last year in May.

As our own Justin Pot remarked back then, the move was likely aimed at encouraging creators and fans to interact more on YouTube itself, rather than resorting to other platforms like Facebook, Twitter and Reddit.

While it’s unclear whether Google has any plans to roll out the feature to all users in the future, the experiment is a strong indication that the company hasn’t quite given up on turning YouTube into more of a social network.

In case you want to sneak a peek at YouTube’s new messaging feature, get one of your Canadian friends to add you to a conversation – that should give you an early preview.

 

Check out the video below to get a better idea of how the messaging platform looks like.

Source : thenextweb.com

 

Categorized in Social

(Natural News) Mark Zuckerberg and his team of social engineers are hoping to push the Facebook platform one step closer to singularity by developing new ways to invade the human mind in order to spy on people’s thoughts. According to reports, the social media giant is tasking a team of neuroscientists with developing a so-called “brain-computer interface” that will supposedly allow users to talk to each other telepathically, while also allowing Facebook to intercept this flow of communication for around-the-clock monitoring.

Known conspicuously as the “Building 8,” or B8, team, the crew working on the project is using advanced neuroscience and electrical engineering to build a platform whereby it will one day be possible for Facebook to use artificial intelligence to map the thoughts and movements of users’ brain in order to exploit them. The technology will have the ability to “capture a thought,” to quote the words of Zuckerberg, who explained how it will all work at a question and answer session he attended back in 2016.

 

In essence, the technology will give Facebook the ability to enter the human brain and extrapolate whatever is going on there, taking this information “in its ideal and perfect form in your head and shar[ing] that with the world,” Zuckerberg says. “The B8 team will apply DARPA-style breakthrough development at the intersection of ambitious science and product development,” reads a jobs announcement posted by Facebook about what the new project will entail. “It will operate on aggressive, fixed timelines, with extensive use of partnerships in universities, small and large businesses.”

Using Facebook contributes to the enslavement of humanity by machines

In an attempt to merge humans with machines, this latest Facebook endeavor is an absolute privacy and security nightmare that threatens to allow near-unlimited access into the human brain by advanced computer systems. Much like how Amazon’s “Alexa” can listen to speech and follow commands, Facebook’s B8 project will be able to listen to and track a person’s thoughts.

An alarming ramification of such a prospect is the idea that Facebook, potentially working in lockstep with government spying programs like those at the National Security Agency (NSA), might gain access to the private thoughts of individuals who would rather keep such information to themselves. Facebook’s attempts to create a more “realistic and immersive” experience with its products could end up creating a thought prison of epic proportions. 

Whether such technology ever comes to fruition remains to be seen, but this certainly wouldn’t be the first time that Facebook as pushed the limits of spying and control — nor is it the first time that emerging Facebook technology has had such nefarious underpinnings.

Facebook officials claim that users who are to become targets of active government monitoring or surveillance will be notified in advance, suggesting that anyone who has not received such a notice likely has nothing to worry about in terms of spying. But a statement released by Facebook’s security chief Alex Stamos about the company’s policy on this infers that only government “attacks” will be subject to such notification, and what exactly constitutes an attack?

“While we have always taken steps to secure accounts that we believe to have been compromised, we decided to show this additional warning if we have a strong suspicion that an attack could be government-sponsored,” Stamos says. “We do this because these types of attacks tend to be more advanced and dangerous than others, and we strongly encourage affected people to take the actions necessary to secure all of their online accounts.”

Stay informed on the abuse of technology to enslave humanity at GLITCH.news.

Sources:

Source : naturalnews.com

Categorized in Science & Tech

Two billion photos find their way onto Facebook’s family of apps every single day and the company is racing to understand them and their moving counterparts with the hope of increasing engagement. And while machine learning is undoubtedly the map to the treasure, Facebook and its competitors are still trying to work out how to deal with the spoils once they find them.

Facebook AI Similarity Search (FAISS), released as an open-source library last month, began as an internal research project to address bottlenecks slowing the process of identifying similar content once a user’s preferences are understood. Under the leadership of Yann LeCun, Facebook’s AI Research (FAIR) lab is making it possible for everyone to more quickly relate needles within a haystack.

 

On its own, training a machine learning model is already an incredibly intensive computational process. But a funny thing happens when machine learning models comb over videos, pictures and text — new information gets created! FAISS is able to efficiently search across billions of dimensions of data to identify similar content.

In an interview with TechCrunch, Jeff Johnson, one of the three FAIR researchers working on the project, emphasized that FAISS isn’t so much a fundamental AI advancement as it is a fundamental AI-enabling technique.

Imagine you wanted to perform object recognition on a public video that a user shared to understand its contents so you could serve up a relevant ad. First you’d have to train and run that algorithm on the video, coming up with a bunch of new data.

From that, let’s say you discover that your target user is a big fan of trucks, the outdoors and adventure. This is helpful, but it’s still hard to say what advertisement you should display — a rugged tent? An ATV? A Ford F-150?

To figure this out, you would want to create a vector representation of the video you analyzed and compare it to your corpus of advertisements with the intent of finding the most similar video. This process would require a similarity search, whereby vectors are compared in multi-dimensional space.

In this representation of a similarity search, the blue vector is the query. The distance between the “arrows” reflects their relative similarity.

In real life, the property of being an adventurous outdoorsy fan of trucks could constitute hundreds or even thousands of dimensions of information. Multiply this by the number of different videos you’re searching across and you can see why the library you implement for similarity search is important.

“At Facebook we have massive amounts of computing power and data and the question is how we can best take advantage of that by combining old and new techniques,” posited Johnson.

Facebook reports that implementing k-nearest neighbor across GPUs resulted in an 8.5x improvement in processing time. Within the previously explained vector space, nearest neighbor algorithms let us identify the most closely related vectors.

More efficient similarity search opens up possibilities for recommendation engines and personal assistants alike. Facebook M, its own intelligent assistant, relies on having humans in the loop to assist users. Facebook considers “M” to be a test bed to experiment with the relationship between humans and AI. LeCun noted that there are a number of domains within M where FAISS could be useful.

“An intelligent virtual assistant looking for an answer would need to look through a very long list,” LeCun explained to me. “Finding nearest neighbors is a very important functionality.”

Improved similarity search could support memory networks to help keep track of context and basic factual knowledge, LeCun continued. Short-term memory contrasts with learned skills like finding the optimal solution to a puzzle. In the future, a machine might be able to watch a video or read a story and then answer critical follow-up questions about it.

More broadly, FAISS could support more dynamic content on the platform. LeCun noted that news and memes change every day and better methods of searching content could drive better user experiences.

Two billion new photos a day presents Facebook with a billion and a half opportunities to better understand its users. Each and every fleeting chance at boosting engagement is dependent on being able to quickly and accurately sift through content and that means more than just tethering GPUs.

Source : techcrunch.com

Categorized in Social

SAN FRANCISCO — When Steve Wozniak co-founded Apple with Steve Jobs in 1976, the two Steves assumed it would last forever.

Woz still believes that's true. In fact, he's convinced Apple, Google and Facebook will be bigger in 2075, the theme of next weekend's Silicon Valley Comic Con (SVCC), “The Future of Humanity: Where Will We Be in 2075?”

The three-day conference, which Wozniak helped create last year, explores the intersection of pop culture and technology. This year's guests includes the 30th anniversary cast reunion of Star Trek: The Next Generation, actors William Shatner and John Cusack, former astronaut Buzz Aldrin and renowned architect Greg Lynn.

 

SVCC is expected to draw 75,000 to 100,000 from April 21-23 to downtown San Jose. In addition to a start-up village and space exploration zone, its exhibit floor showcases entertainment companies, comic book vendors, and technology exhibits for virtual reality, robotics and smart devices. Panels and film presentations will weigh in on flying cars, aliens, Mars, the implantation of computers into brains and other space-age stuff, show organizers say.

Wozniak is no stranger to predictions. In 1982, he said portable laptops would emerge. And he has strong opinions on how we'll live in 58 years.

"Apple will be around a long time, like IBM (which was founded in 1911)," Wozniak said in an interview on Friday. "Look at Apple's cash ($246.1 billion, as of the end of its last fiscal quarter). It can invest in anything. It would be ridiculous to not expect them to be around (in 2075). The same goes for Google and Facebook."

Woz shared some other predictions on what type of planet we can expect in 2075:

— New cities. Deserts could be ideal locations for cities of the future, designed and built from scratch, according to Wozniak. There, housing problems will not exist and people will shuttle among domed structures. Special wearable suits will allow people to venture outside, he said.

— The influence of artificial intelligence. Within all cities, AI will be ubiquitous, Wozniak says. Like a scene straight from the movie Minority Report, consumers will interact with smart walls and other surfaces to shop, communicate and be entertained. Medical devices will enable self-diagnosis and doctor-free prescriptions, he says. "The question will be ethical, on whether we can eliminate the need for physicians," he says.

Mars covered in clouds viewed by the Hubble Space Telescope,Mars covered in clouds viewed by the Hubble Space Telescope, May 2016. (Photo: NASA / HUBBLE / HANDOUT, EPA)
 — Mars colony. Woz is convinced a colony will exist on the Red Planet. Echoing the sentiments of Amazon CEO Jeff Bezos, whose Blue Origin start-up has designs on traveling to Mars, Wozniak envisions Earth zoned for residential use and Mars for heavy industry.

— Extraterrestrials. With apologies to those who believe in aliens, Wozniak says there is a "random chance" that Earthlings will communicate with another race. "It's worth trying," he says, "but I don't have high hopes."

The trick with predicting the future, Wozniak readily acknowledges, is that it changes so quickly. "Who could have foreseen the rise of an Uber a decade ago?' he says, before pausing.

"She has more power in her hand than Superman," Wozniak, broadly smiling, says, pointing at a colleague's iPhone. "To make such strides in computing... It shows you how exciting the future can be."

Source : usatoday.com

Categorized in Others

When you search "Facebook Live" on Google today, these are the most popular results you'll see:

Not "Facebook Live tips and tricks." Not "Facebook live funniest videos." All the most popular searches for Facebook Live revolve around murders, torture, and death. This is probably not what Facebook had in mind when it introduced Facebook Live to the public last April.

With the exception of the "Chewbacca Mom" video, Facebook Live only seems to get in the news cycle when a horrific incident occurs on the platform. Some examples:

 

These are just a handful of the dozens of examples you'll find online.

Facebook Live is currently in the news because, according to Cleveland police, an Ohio resident named Steve Stephens killed an elderly man on Facebook Live on Sunday and claimed to have killed more than a dozen other people in the same broadcast. State and local police are still searching for Stephens, with authorities and Cleveland Mayor Frank Johnson asking the man to turn himself in.

Now, it's important to note that live-streaming video platforms on the internet are a relatively new medium. And as Facebook, Twitter, Amazon and others continue investing in live video, it's unclear what, if anything, should be done when these incidents occur — from hiding these videos from web search, to preventing these gruesome and sad tragedies from being broadcast live in the first place. The fact is, even if Facebook is quick to take down these offending videos, it doesn't take much for these incidents to become news stories, which in turn leads people to search for the original videos through Google and other search engines. So as live video becomes more of a thing, hopefully we'll see Facebook and others make efforts to address this complex and sensitive issue.

Source : uk.businessinsider.com

 

Categorized in Social

Getting a new job, recovering from an abusive relationship, engaging in new kinds of activism, moving to a different countrythese are all examples of reasons one might decide to start using Facebook in a more private way. While it is relatively straightforward to change your social media use moving forward, it can be more complicated to adjust all the posts, photos, and videos you may have accumulated on your profile in the past. Individually changing the privacy settings for everything you have posted in the past can be impractical, particularly for very active users or those who have been using Facebook for a long time.

The good news is that Facebook offers a one-click privacy setting to retroactively change all your past posts to be visible to your friends only. With this tool, content on your timeline that you’ve shared to be visible to Friends of Friends or Public will change to be visible by Friends only. And the change will be “sticky”it cannot be reversed in one click, and would be very difficult to accidentally undo.

 

Watch this video for a step-by-step tutorial to change this setting and make your posts more private.

Privacy info. This embed will serve content from youtube.com

Keep in mind that, if you tagged someone else in a past post, that post will still be visible to them and to whatever audience they include in posts they are tagged in. And, if you shared a past post with a “custom” audience (like “Friends Except Acquaintances” or “Close Friends”), this setting won’t apply

Finally, this setting can only change the audience for posts that you have shared. When others tag you in their posts, then they control the audience. So share this blog post and video with your friends and encourage them to change their settings, because privacy works best when we work together.

Source : eff.org

Categorized in Internet Privacy

Amazon’s Alexa can summon an Uber and satisfy a four-year-old’s demand for fart noises. Siri can control your Internet-connected thermostat. Each serve millions of users each day. But a lucky group of around 10,000 people, mostly in California, know that Facebook’s assistant, named M, is the smartest of the bunch.

Recommend and reserve a romantic hotel in Morocco that’s also suitable for small children? No problem. Get quotes from local contractors for landscaping your front yard? Consider it done. Facebook’s experimental assistant, offered inside the company’s Messenger app, shows the value of having a true digital butler in your pocket. Instead of just retrieving simple pieces of information from databases, M can understand complex orders and take actions like booking theater tickets or contacting companies for information.

 

M is so smart because it cheats. It works like Siri in that when you tap out a message to M, algorithms try to figure out what you want. When they can’t, though, M doesn’t fall back on searching the Web or saying “I'm sorry, I don’t understand the question.” Instead, a human being invisibly takes over, responding to your request as if the algorithms were still at the helm. (Facebook declined to say how many of those workers it has, or to make M available to try.)

That design is too expensive to scale to the 1.2 billion people who use Facebook Messenger, so Facebook offered M to a few thousand users in 2015 as a kind of semi-public R&D project. Entwining human workers and algorithms was intended to reveal how people would react to an omniscient virtual assistant, and to provide data that would let the algorithms learn to take over the work of their human “trainers.”

“Everybody in this field is dreaming of creating the assistant that will finally be very, very, very smart,” says Alex Lebrun, who started the project. M is supposed to open a path to truly doing it.

 

Now two years down that path, Facebook’s research project can justifiably be called successful. Users like M, and the theory that software could learn to take over some work from the human trainers has been borne out. Yet M is still far from the point where it could be offered to the other 99.9 percent of Messenger users, and progress has been harder won than expected.

“We knew it was a huge challenge, but it’s even bigger than I thought,” says Lebrun. “The learning rate, the growth of the automation—we’ve seen that it would be slower than we hoped.” M’s story is a reminder of how far artificial intelligence has come in recent years—and how far it has to go.

M is for moonshot

People are surprisingly game to talk with dumb machines. The first chatbot was created in 1964, by MIT professor Joseph Weizenbaum. It trotted out canned lines in response to specific keywords, most successfully when playing the role of a therapist. To Weizenbaum’s annoyance, many people who tried it, including his own secretary, were smitten despite knowing that the bot, called Eliza, knew nothing. “I had not realized that extremely short exposures to a relatively simple computer program could induce powerful delusional thinking in quite normal people,” he later wrote.

Making a chatbot that helps you by getting things done, not just acting as a sounding board or confessor, is much harder. When a virtual servant is asked to do something, a vague or deflecting response won’t cut it. Today’s software is poor at understanding language and the world, so virtual assistants, such as Siri or Alexa, must be explicitly programmed to handle any given task.

That’s why bots on the market have restricted repertoires. And it probably explains why suggestions last year that chatbots were set to transform how we use computers much as mobile apps did, stoked by Microsoft, Facebook, and some tech investors, don’t seem to have amounted to much. “Bots are right now in the trough of despair,” says Greg Cohn, CEO of Burner, a mobile privacy company that has started helping Airbnb hosts create a simple bot to answer common questions from guests. “To industry observers it feels like they’re overhyped and under-delivering.”

Lebrun built M because he had spent more than a decade building conventional, narrow chatbots and dreamed of offering much more. He joined Facebook in early 2015 when the social network acquired Wit.ai, a company he cofounded to help businesses create chatbots for functions like customer support. Lebrun had previously sold a chatbot company to the speech recognition giant Nuance.

“Every single bot on the market, including mine, was rule-based, and you know that one day you’ll reach a ceiling and never go through,” says Lebrun. “Our children don’t work with rules or scripts, and one day they become smarter than you.”

M was initially offered only to Facebook employees, and then to some heavy Messenger users in California. And it didn’t take long to demonstrate that algorithms could indeed learn to do some of the work being done by the humans powering the assistant.

Facebook’s artificial-intelligence research group used M to test a new type of learning software called a memory network, which had shown aptitude at answering questions about simple stories. The software uses a kind of working memory to salt away important information for later use, a design Google is also testing to improve software’s reasoning skills.

Weizenbaum had suggested back in 1964 that something like this could make Eliza smarter, and within weeks it worked for M. Lebrun remembers being surprised after thanking the assistant for ordering movie tickets. It automatically generated the response “You’re welcome. Enjoy the movie.” M had learned to remember and use the context of the task it was helping with. “We were really blown away,” says Lebrun. “Nobody wrote a program to do that.”

Memory networks went on to do more. They now kick in if someone asks M to get flowers delivered, for example, automatically using key info from the request, such as budget or address, to generate suggestions from online florists. The human trainer then chooses which to offer the user.

Other discoveries have been less cheering. One is the huge appetite M unlocks in its users. With limited, fully automated assistants like Siri or Alexa, people tend to settle into using a few functions they find to work reliably. With M, they don’t.

“People try first to ask for the weather tomorrow; then they say ‘Is there an Italian restaurant available?’ Next they have a question about immigration, and after a while they ask M to organize their wedding,” says Lebrun. “We knew it would be dangerous, and it’s wider than our expectations.”

Human trainers gamely do their best when they receive tough queries like “Arrange for a parrot to visit my friend,” but sometimes they decline to help altogether. Even if M were to automatically turn down the most complex of user queries, though, the sheer variety of their requests makes the goal of having algorithms take over from human trainers harder to reach. A technique called deep learning has recently made machine learning more powerful (memory networks are an example). But learning to handle a wide variety of complex scenarios, with little data on each because they don’t arise often, is not the kind of problem deep learning excels at. “It’s much smarter, and it can learn very complex tasks, but it needs a lot of data,” says Lebrun.

Long haul

Slower-than-expected progress has led Facebook to reimagine its project. Last week a feature called M Suggestions appeared in Messenger, similar in function to the kinds of limited bots M is meant to displace. It looks at your chats with friends for clues that you might want to do things like order a ride with Uber, or send someone money, and offers a button to achieve those goals with a single tap.

“We decided to find a use case where we can accelerate delivering value to users,” says Laurent Landowski, who joined Facebook with Lebrun as cofounder of Wit.ai and now oversees M. (Lebrun returned to his native France in January, joining Facebook’s AI research lab in Paris.)

The original, human-dependent M is still out there, delivering much greater value to its few lucky users. Facebook says it is committed to the project, and the current moment in artificial intelligence is a good one for long-term bets. In the last couple of years, deep learning has upended established techniques and expectations for software that processes language, says Justine Cassell, a professor at Carnegie Mellon. “We’re in the glory days of these new machine-learning algorithms,” she says. Indeed, Google’s translation accuracy recently jumped to an almost human level.

That doesn’t mean it’s a foregone conclusion that software can learn to play butler by watching humans do it. “I don’t think we know yet,” says Cassell. But Facebook’s researchers say they have plenty of ideas to explore.

One is getting the automated side of M to learn from positive or negative feedback in the messages users send, using a technique inspired by the process of training animals with rewards (see “10 Breakthrough Technologies 2017: Reinforcement Learning”). M might advance faster if not solely dependent on aping what its human contractors do. To spark ideas in the broader research community, Facebook’s team has released tools to help others test and compare unscripted assistant bots. And promising new techniques can now also be tested at larger scale, in M Suggestions.

Lebrun and Landowski think that they’re still on track to eventually bring the real M to the masses. “Sometimes we say this is three years, or five years—but maybe it’s 10 years or more,” says Landowski.

Lebrun adds, “It’s so hard, and we make progress slowly, but I think we have everything we need.” He could be right, but you can also imagine someone who met Eliza in 1964 saying much the same thing.

Source : technologyreview.com

Categorized in Social

In general, social interaction helps people create and foster relationships. Although, as social networks have expanded over the past decade, their downsides have become apparent. Connecting virtually can lead to a decline in face-to-face relationships and meaningful activities, a sedentary lifestyle, internet addiction and low self-esteem.

The average Facebook user spends almost an hour on the platform every day, and a recent Deloitte study revealed that the first thing many smartphone owners do when they wake up is open their social media apps.

study co-authored by researchers from Yale University and the University of California, San Diego, uncovered how Facebook use influences a person’s well-being. Analyzing data from 5,208 adults over a two-year period, the researchers found that the average Facebook user’s well-being over declined time.

Over the two-year period, the researchers collected data in three waves. Each time, they measured a person’s well-being -- based on factors such as life satisfaction, self-reported mental and physical health and body mass index. They compared that data to each person’s Facebook usage, taking note of when respondents liked others’ posts, created posts and clicked on links.

 

Also, to help paint a picture of a respondent’s real-world (not online) social network and compare it to that person’s Facebook usage, the researchers asked respondents to name up to four friends with whom they discuss important topics and up to four friends with whom they spend their free time.

Nothing beats an in-person social relationship, the researchers found. Real-world relationships were positively associated with a person’s overall well-being, while Facebook interactions were negatively associated with overall well-being. And, while the researchers expected the action of liking others’ Facebook posts to have the strongest negative impact on one’s well-being (because it initiates social comparison), they found that all three actions (clicking on links, liking others’ content and creating posts) were similarly associated with diminished well-being.

Overall, the co-authors found that the decline of one’s well-being is a product of not just the quality of their social media interactions, but the quantity of them (time spent on them) as well.

Social networking companies have recognized the opportunity for them to foster valuable, healthy, offline connections. Facebook founder Mark Zuckerberg published a letter in February 2017 describing his vision for Facebook as a platform that builds real-life support systems. Tinder has recently developed new products within its app to encourage users to meet in person.

 

“While screen time in general can be problematic, the tricky thing about social media is that while we are using it, we get the impression that we are engaging in meaningful social interaction,” co-authors Holly B. Shakya and Nicholas A. Christakis write in Harvard Business Review. “Our results suggest that the nature and quality of this sort of connection is no substitute for the real world interaction we need for a healthy life.”

Source: entrepreneur.com

Categorized in Social
Facebook may have revolutionized how we stay in touch with friends and family, but a new study has found that too much time on social media actually leads to increased feelings of isolation.

The study, published Monday in the American Journal of Preventive Medicine, examined feelings of social isolation among more than 1,787 US adults between the ages of 19 and 32. 

The researchers defined social isolation as the lack of a sense of belonging, true engagement with others, and fulfilling relationships.

Participants were given a questionnaire which assessed how socially isolated a person felt, as well as how much and how often they used 11 popular social media platforms – Facebook, YouTube, Twitter, Google Plus, Instagram, Snapchat, Reddit, Tumblr, Pinterest, Vine, and LinkedIn.

 

The researchers found that participants spent an average of just over an hour (61 minutes) on social media each day, and visited social media sites a median of 30 times each week.

Twenty-seven percent of the participants reported feeling high levels of social isolation, with researchers concluding that greater social media use was linked to greater feelings of social isolation.

For instance, those who used social media more than two hours daily were around twice as likely to report feeling high levels of social isolation. Those who visited social media sites 58 times or more per week were about three times as likely to report feeling high levels of social isolation.

“We are inherently social creatures, but modern life tends to compartmentalize us instead of bringing us together,” lead author Brian Primack, director of the Center for Research on Media, Technology and Health at the University of Pittsburgh, said in a press release. 

“While it may seem that social media presents opportunities to fill that social void, I think this study suggests that it may not be the solution people were hoping for,” he continued.

The researchers noted that part of the problem could be that social media can give people the impression that others are leading happier lives, because people sometimes portray themselves unrealistically online.

Another theory is that people spending a lot of time on social media have less time for real-world interactions, and that such sites can make people feel excluded – such as when a person sees their friends at a party they weren't invited to.

However, the problem doesn't necessarily stem directly from social media. The researchers said it's possible that those who already felt socially isolated are simply more likely to spend a lot of time on social media.

“We do not yet know which came first – the social media use or the perceived social isolation,” co-author Elizabeth Miller, professor of pediatrics at the University of Pittsburgh, said in a statement.

“It’s possible that young adults who initially felt socially isolated turned to social media. Or it could be that their increased use of social media somehow led to feeling isolated from the real world.”

 

Miller also said it “could be a combination of both,” but noted that if social isolation came first, it does not seem to be alleviated by spending time online.

Source : rt.com 

Categorized in Social

1. Teach your friends how to *actually* pronounce your name.

Teach your friends how to *actually* pronounce your name.
Facebook
Go to your profile page, then About, click Details About You, then under Name pronunciation, click “How do you say your name?“
 
Nicole Nguyen / BuzzFeed
This is how it shows up on your profile!
Categorized in Social

airs logo

Association of Internet Research Specialists is the world's leading community for the Internet Research Specialist and provide a Unified Platform that delivers, Education, Training and Certification for Online Research.

Get Exclusive Research Tips in Your Inbox

Receive Great tips via email, enter your email to Subscribe.

Follow Us on Social Media