Don’t call it slacktivism — public grief is an important human act 


What I understand now is that to some degree, we weren’t mourning in any concrete, specific way. We were making ourselves available the only way we knew how, through a kind of performance of grief, a way of saying, “We are here, and we know you are in pain, even if we can’t understand it.”


via Don’t call it slacktivism — public grief is an important human act | Vox


 

Shop Straight From Instagram?


Buy What You ‘Like?’

But for retailers, Instagram has proven difficult to monetize. The photo app doesn’t allow links on individual posts.

instagram-logoBilled as the “missing link” between traffic and revenue, the technology allows fans to click the one link Instagram permits (atop a brand’s profile page) then displays an elegant grid of all the items up for sale from the retailer’s feed. One more click takes a user to the store’s secure mobile site.

Like2Buy also functions as a curation tool for shoppers. By ‘liking’ a photo of a handbag, or lipstick, or anything, Instagrammers can create their own wishlist or save products to buy later.

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Facebook Bottleneck?


But even the most tech-minded media company still has the same distribution bottleneck: Facebook. Over 80 percent of Moviepilot’s traffic comes from the social network, where it links to roughly 100 of its articles a week via its dozen Facebook pages, which have 29 million fans, collectively. That, of course, exposes the site to some significant risks, considering that Facebook hasn’t been shy about tweaking its algorithm.

“That’s definitely something that keeps us up at night,” Bauckhage said. “On the other hand, we wouldn’t be as big as we are now without Facebook. It’s a great opportunity, but it’s also a great risk.”


via Moviepilot cashes in on a platform approach | Digiday.


 

Inside a counterfeit Facebook farm


Most of the accounts Casipong creates are sold to these digital middlemen — “click farms” as they have come to be known. Just as fast as Silicon Valley conjures something valuable from digital ephemera, click farms seek ways to create counterfeits. Just Google “buy Facebook likes” and you’ll see how easy it is to purchase black-market influence on the internet: 1,000 Facebook likes for $29.99; 1,000 Twitter followers for $12; or any other type of fake social media credential, from YouTube views to Pinterest followers to SoundCloud plays. Social media is now the engine of the internet, and that engine is running on some pretty suspect fuel.

Casipong plays her role in hijacking the currencies of social media — Facebook likes, Twitter followers — by performing the same routine over and over again. She starts by entering the client’s specifications into the website Fake Name Generator, which returns a sociologically realistic identity: Ashley Nivens, 21, from Nashville, Tennessee, now a student at New York University who works part-time at American Apparel. Casipong then creates an email account. The email address forms the foundation of Ashley Nivens’ Facebook account, which is fleshed out with a profile picture from photos that Braggs’ workers have scraped from dating sites. The whole time, a proxy server makes it seem as though Casipong is accessing the internet from Manhattan, and software disables the cookies that Facebook uses to track suspicious activity.

[…]

Click farms jeopardize the existential foundation of social media — the idea that the interactions on it are between real people. Just as importantly, they undermine the assumption that advertisers can use the medium to efficiently reach real people who will shell out real money. More than $16 billion was spent worldwide on social media advertising in 2014; this money is the primary revenue for social media companies. But if social media is no longer made up of real people, what is it?


via Inside a counterfeit Facebook farm | The Week.


 

Metrics-driven newsroom culture


“Metrics inspire a range of strong feelings in journalists, such as excitement, anxiety, self-doubt, triumph, competition, and demoralization,” Petre writes. Depending on how they’re implemented, metrics can have vastly divergent effects on editorial culture. But regardless of how newsrooms shield their staff, Petre found, the emotional effect remains.

[…]

After all, metrics alone don’t create a newsroom culture, it’s the way they’re interpreted.

[…]

More tellingly, staffers said their willingness to experiment was dampened by pressure to feed the numbers.

[…]

With traffic as the complete arbiter of merit, reporters responded rationally.

[…]

And, she observed, editors spoke about metrics after-the-fact—when they justified a decision—rather than factoring them in during the decision making process. Yet none of this prevented reporters from gut-checking the analytics themselves, scouring the site’s “most-emailed” and “most-viewed” displays, unsure how seriously to take inclusion (or exclusion) from those daily round-ups.

 

NOTE: Read the entire article at the link below which is an interesting view on HOW-NOT-TO interpret metrics:


via When metrics drive newsroom culture | Columbia Journalism Review.


 

Big Data, Machine Learning, and the Social Sciences


Discovering finer-grained signals, however, such as those often associated with data about minorities, can be much harder. Luciano Floridi, a philosopher, addresses this point in a recent paper of his. He says,

The real, epistemological problem with big data is small patterns. […] [But] small patterns may be significant only if properly aggregated. So what we need is a better understanding of which data are worth preserving.

In other words, fine-grained patterns may not be readily visible using existing computational techniques. He continues,

And this is a matter of grasping which questions are or will be interesting. […] [T]he game will be won by those who ‘know how to ask and answer questions.’

Again, this underscores the need for social scientists, who are trained to ask and answer important questions about society; however, it also highlights one of my biggest concerns about some of the big data research and development coming out of the computer science community.

via Big Data, Machine Learning, and the Social Sciences | Medium.

Don’t Believe the Hype


The Problems With Facebook’s Polarization Study

And it’s not clear that Facebook can or should be arguing that it plays a smaller filtering role than individuals, given how the study was conducted in the first place and given that the two findings do not seem directly comparable. “I cannot remember a worse apples to oranges comparison I’ve seen recently, especially since these two dynamics, algorithmic suppression and individual choice, have cumulative effects,” writes Zeynep Tufekci of the University of North Carolina.


via The Problems With Facebook’s Polarization Study | Science of Us.


 

#TheDress by the numbers


So what did we learn from #TheDress?

  1. Innocuous things can lead to gigantic gains in Web traffic.
  2. Keeping an eye on conversations across the social Web and finding an inroad is now the dominant way to get your client’s content seen by broader audiences.
  3. Having an editorial assembly line capable of a quick turnaround is pivotal to that insertion of brand content.

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Google and Facebook are our frenemy. Beware.


The growing pact between large publishers of news and large platforms for social media is an alliance born out of desperation on the part of publishers and opportunity on the part of technology companies. Ultimately, there is little doubt that the largest news and information companies in the world will be formed out of a hybrid of these current entities.
[…]
When I delivered the Reuters Memorial Lecture in Oxford last year, my theme was that of the growing imperative for some kind of detente between media companies and the Silicon Valley platform companies that now form the backbone of the free press. It is inevitable that we’re moving toward a closer relationship between companies that produce the news and platform companies that maintain plausible deniability when it comes to their role as publishers. The infamous Facebook news algorithm, the method by which it sorts and delivers stories into your News Feed, has also drawn increasing scrutiny. As these closed systems replace broadcast infrastructure and regulated media, how do apply accountability to commercial platforms?


via Google and Facebook are our frenemy. Beware.Columbia Journalism Review.


 

Making better social media maps


OK

Location-based data from social media can be interesting to analyze and map, but there are a lot of inherent challenges with the data. The main one, which designers often ignore, is that it’s safe to make inferences straight from the tweets alone. That is, there’s an assumption that the data is representative of the real-life population when in fact there are a ton of social implications to consider.


via Making better social media maps | Flowing Data.