However, removing human writers from Trending doesn’t necessarily eliminate bias. Human bias can be embedded into algorithms, and extremely difficult to strip out. That’s one of the conclusions from a study (pdf) of a popular algorithm used for processing language from Princeton University and the University of Bath released as a draft yesterday (Aug. 25). It’s currently under review for publication in a journal. Read More
The reason a lot of these companies are tagging their selfies with #machinelearning is that they have some cool algorithm. Sweet I.P. bro! News flash: algos are not intelligent. Algos take in data that you hand-picked, and probably pre-formatted, complete some operation you specified explicitly, and produce results which are predictable.Intelligence is not predictable. Intelligence does whatever IT thinks is best.
Facebook relies on editors’ judgment for trending news feed, documents show
But the documents show that the company relies heavily on the intervention of a small editorial team to determine what makes its “trending module” headlines – the list of news topics that shows up on the side of the browser window on Facebook’s desktop version. The company backed away from a pure-algorithm approach in 2014 after criticism that it had not included enough coverage of unrest in Ferguson, Missouri, in users’ feeds. Read More
Facebook’s algorithm will control journalism if we let it
Gizmodo‘s Michael Nunez delved into the lives of Facebook’s contract journalists in a well-shared piece:
Over time, the work became increasingly demanding, and Facebook’s trending news team started to look more and more like the worst stereotypes of a digital media content farm. Managers gave curators aggressive quotas for how many summaries and headlines to write, and timed how long it took curators to write a post.
For example, we’ve found that there are stories people don’t like or comment on that they still want to see, such as articles about a serious current event, or sad news from a friend. Based on this finding, we previously updated News Feed’s ranking to factor in how much time you spend reading a post within News Feed, regardless of whether you opened the article. We also previously updated News Feed’s ranking to take into account times when someone clicked on an article and came straight back to News Feed as we learned that this often happened when the article someone clicked on wasn’t what they had expected from the post or the headline.
How big data is unfair
As we’re on the cusp of using machine learning for rendering basically all kinds of consequential decisions about human beings in domains such as education, employment, advertising, health care and policing, it is important to understand why machine learning is not, by default, fair or just in any meaningful way.
This runs counter to the widespread misbelief that algorithmic decisions tend to be fair, because, y’know, math is about equations and not skin color.
As online users, we’ve become accustomed to the giant, invisible hands of Google, Facebook, and Amazon feeding our screens. We’re surrounded by proprietary code like Twitter Trends, Google’s autocomplete, Netflix recommendations, and OKCupid matches. It’s how the internet churns. So when Instagram or Twitter, or the Silicon Valley titan of the moment, chooses to mess with what we consider our personal lives, we’re reminded where the power actually lies. And it rankles.
The question is: Do algorithmic feeds create a better user experience or do they enable social platforms to better serve advertisers?
When Instagram announced that it would be using an algorithm to order content, the decision was justified in part by the claim that users are missing out on 70 percent of the content they’re subscribed to; an algorithm could potentially show users more of what they follow. This provides a natural boost to advertisers, given how Instagram users engage with brands on the platform.
Tell us in the comments your thoughts about Algorithmic vs Chonological:
Expect a more thorough analysis to follow, this made us laugh in the debate of Instagram’s new algorithmic timeline/feed. Currently we are enjoying the humorous reactions to the change. Not unlike previous ones, but funny because IG is the darling for everyone except us!
Online abuse can be cruel – but for some tech companies it is an existential threat. Can giants such as Facebook use behavioural psychology and persuasive design to tame the trolls? [8 Minute Read]
Fan Is A Tool-Using Animal
Below are some highlights of the talk, or take-away points to the talk that seemed to be far-reaching when dealing with social media. Read the whole thing by clicking the picture above or following the link at the bottom. Read More
Tales of your Downfall are greatly exaggerated, they always are
Another Day, another rumor that sparks furious condemnation of Twitter for daring to change. Of course it trends. Its users, power or otherwise, influencer or not, seem to have very strong feelings about something they neither know much about or have investigated more than say, listening to what others have tweeted. Except to say Twitter is ‘becoming Facebook’ … algorithm this…non-chronological…
Further to this, one has to wonder why all the complaining, why grab the pitchforks, light the torches, swear (rather less than persuasively) you’ll stop using it…
Like Bitly, Twitter has a great real-time data set and very smart data scientists and engineers. But instead of relying on a primarily computational solution, Twitter treats real-time search more like a CAPTCHA problem. With this kind of messy data, lots of human brains can find meaning much faster and more accurately than lots of lines of code. So Twitter uses a real-time computation system called Storm to identify search spikes, then Mechanical Turk (Amazon’s crowdsourcing online platform for small jobs) to farm out annotating that data to human beings all over the world. The annotations basically take the spiking search term and tag it for relevance and intent. A human annotator (Twitter calls them “judges”) can tell Twitter’s systems whether searches for “Stanford” refer to a university or to its football team, or that searches for “Big Bird” aren’t primarily referencing a children’s show, but a political debate. This helps Twitter make trending topics smarter and more coherent.
Many of these interests look a lot like Pages you would ordinarily follow — celebrities, hobbies, brands, etc. — although their relative audience sizes can be surprising. Japanese pop duo Puffy AmiYumi (139,218,340) beats Beyoncé (80,634,320). The Minions (75,372,780) beat Kanye West (74,589,850). Disney on Ice (36,144,060) beats Game of Thrones (34,527,750). And the hobby “cat communication” (4,663,340), whatever that is, beats Sarah Palin (4,645,190). On the other extreme, the Power Macintosh 7100, Amazon MP3s, and the Applebee’s in Amman, Jordan all have audiences of fewer than 30.
But those interactions are only a rough proxy for what Facebook users actually want. What if people “like” posts that they don’t really like, or click on stories that turn out to be unsatisfying? The result could be a news feed that optimizes for virality, rather than quality—one that feeds users a steady diet of candy, leaving them dizzy and a little nauseated, liking things left and right but gradually growing to hate the whole silly game. How do you optimize against that? (read more at link below: 22 minute read)
Today, you’d be lucky to find a cheap knockoff in a world dominated by crappy promotional infographics churned out for viral attention. Nicholas Felton, the data viz guru who once designed Facebook’s Timeline, now builds apps. Jer Thorp is as interested in reverse-engineering algorithms and data art as he is in producing pure data visualization. Even the infographics on the portfolio-sharing site Behance are on the downswing. “Infographic posting generally rose steadily from 2007 to 2012, where it peaked, and has begun to decline since then,” Sarah Rapp, Head of Behance Community Data & Insights, Adobe
Facebook uses an algorithm determined by your profile information, stories you share, and links you click on to serve you ads based on your interests. It also keeps a running tally of the general topics it thinks you like hidden deep within your settings. Strangely, the topics it’s sorted into are … super specific.
+Commentary: This was an interesting look into why Facebook ads have never worked, may never work, and are ultimately useless. When using this article to investigate my own personal settings or “topics” it was hilarious how off-the-chart wrong they were at capturing not only my own general interests, but how off-base they were with regards to things I’d be interested in if they were ad keywords.
As we’ve pointed out here previously when it comes to Google Ads Keyword Planner, they can, if you know what you are looking for and if you are versed in how to find them, realize the whole internet ad thing is built upon a house of cards. That doesn’t mean it doesn’t make money, or that it is not useful to a small business, it just means that unlike the large ad agencies & multi-national corporations you can’t waste tons of money testing out a bunch of different things. Most small business owners that I’ve spoken to recently think that social media is vastly overrated as a tool to connect them to the business they want.
Facebook lets you filter bad memories out of your nostalgia
Facebook is a nostalgia machine, with features like “Year in Review” and “On This Day” summoning photos and posts from the past in an attempt to entertain users. However, these memories aren’t always welcome, and the social network has often been accused of “inadvertent algorithmic cruelty” — accidentally confronting users with painful memories, like images of dead friends and relatives, without warning. To avoid this the company is introducing a pair of filters for its “On This Day” tool, letting users specify individuals and dates they don’t want to be reminded of.
+Commentary: So when they created “On This Day” they clearly did know that people often have meltdowns, crisis, and very sad things they share openly with their friends. Many years ago, as it was becoming popular there were several live-suicides, prior to them introducing a self-harm reporting process. Surely someone on their UX & UI teams, a few of the engineers, maybe the team that handles the reportage process brought this to their attention?
Don’t get me wrong, enjoying that trip down memory lane is great for me personally, and since I’ve only lost a few friends recently, it is actually refreshing to see the comedic routines we engaged in for the past few years. Even if they are at times tinged with a touch of sadness. They compensate for the fact that he’s no longer here & not posting, so it is like his “Greatest Hits” of Social Media. Read More
I try to save the most over-used of clichés for special moments, and that’s exactly what this week feels like for Twitter. You may disagree, of course — Wall Street does, having driven the stock down yesterday to just a dollar above its IPO price (and 38% down from its first day close) — but that’s why the cliché works: things may seem dark, but I’m optimistic that the horizon has just the slightest glimmer of light.
Long time readers know that while I love and value the product, I’m no Twitter fanboy. The company’s user retention issues were apparent well before the IPO, and the company had a clear product problem that, ultimately and correctly, cost CEO Dick Costolo his job.
[…] Read More
[Trigger Warning: Teen Exploitation, Pornography & Sexual Predators]
Jessie discovered it accidentally.
“It was on the popular page,” he told me. “I thought it was just a hot guy with his shirt off.”
Jessie, a 20-something male in New York, had clicked on what he thought was an innocuous selfie on Instagram, the kind of photo we’ve come to expect from a generation which thinks the best way to prove your worth is to purse your lips while staring into a water-stained bathroom mirror. But the image, it turned out, wasn’t of a “hot guy” — it was of a young boy.
“Like, 11-years-old young boy,” Jessie said.
Jessie was creeped out, but what he noticed next disturbed him most: The picture had received thousands upon thousands of likes.