Nailing the Facebook Image: Handy Cheat Sheet

To properly target and engage your audience on Facebook, you need impressive visual assets. Luckily, Facebook offers the freedom to be creative and use eye-catching images in your profile, company page, ads and event invites.

However, there are image dimensions and sizing guidelines that you must follow, or they will not appear as you like and may not be approved at all.

Luckily, TechWyse created this Facebook image sizes and dimensions cheat sheet to lend you a helping hand when crafting your next social media campaign.

Even the savviest social media professionals may not be aware of the Facebook’s image specs. For instance, shared images and shared links require different sizing when it comes to uploading.

Facebook recommends 1200 x 630 px for a shared image. On the other hand, Facebook recommends that shared links should be 1200 x 627 px.

Besides image sizing and dimensions, Facebook also imposes text character limits. They will disapprove/give lesser reach to promoted posts with more than 20% text. This means that you need to make sure the text you are using in your post images must meet this character limit if you want to see your post approved.

Bookmark, download or print the cheat sheet and share it with your team of social media content creators, digital marketers and graphic designers. Hang it on your desk, on your office wall or anywhere you can easily reference it when working out the specifics of the visual assets to accompany your Facebook posts.

Hope it helps!  Good luck.

My Take on the Fake News Controversy

I attended the Daily News Innovation Lab’s session: Proposition: We can Solve the Fake News Problem. It featured an Oxford-style debate on whether there’s a solution to the fake news problem.

Some very smart people from the worlds of media, business, and technology made great arguments for each side. It was entertaining and informative. I’m pleased to say that the optimists won, according to the audience vote at the end.

Why would anyone think we can’t fix the fake news problem? In brief, it is hard to define, pervasive, systemic, and there will always be bad actors trying to game the system. Think of it like hacking, or information warfare. Plus, Google and Facebook make money on fake news, and some say they’re just giving users what they want.

Arguing for the optimists, Jane Elizabeth of American Press Institute said that these systems were created by the people, for the people, and people will solve the problem. Dean Pomerleau of The Fake News Challenge likened it to the Spam epidemic of the early 2000s, which most would agree has been contained, if not completely solved.

I unsuccessfully tried to get a question in at the end about the faulty premise of the debate. How can you even ponder a cure until you’ve more clearly defined the problem? As I pointed out in my last post, there are many varieties of fake news (propaganda, misinformation, counterfeit news sites, and yes, lies, damned lies). And it is almost impossible to define the concept of “news” itself, or “truth.”

Looking beyond this one debate, fake news has inflamed passions, as it may have tilted the US presidential election and encouraged a nut to shoot up a pizzeria. Any discussion about solutions inevitably gets into tricky areas like censorship, free speech, the roles of media and the government, and the responsibility of business.

I don’t think it will be as easy as fighting spam (this CIO article implies that AI has met its match here). But I do think there are fixes, assuming we can agree on a definition, and what might qualify as solving this.

I attempt to do so below, and also share my thoughts on the most contentious issues.

Defining the Problem

We’ll never get rid of misinformation, wacky theories, bias, rumors or propaganda. I propose defining fake news as lies or false information packaged as news. Let’s include counterfeit news sites and any gaming of algorithms and news feeds to propagate false information.

The Social Network’s Role

Some place the problem at the doorstep of social networks and online news aggregators, such as Facebook and Google respectively. Others say that it is not the platform’s jobs to be truth-tellers. Should they hire fact checkers? Who then checks the fact checkers?

Many say that Facebook and Google have no incentive to clean up the mess, as their business models are based on clicks and sharing regardless of veracity. I completely disagree. If they don’t, their brands and reputations (and hence businesses) will take a beating. No one wants to spend time in places where there is lots of junk.

They can and should take measures to combat fake news. I mean, they’re already policing their sites for bullying, obscenity, grisly pictures and other clearly unacceptable things.

It could involve a combination of crowd correction, e.g. a way for users to flag fake news items, and technology akin to spam detection. For all the grousing that it is too hard a problem to solve, check out these articles:

Who Should Judge Truth?

Some argue for greater regulation and transparency. Since algorithms play a growing role in determining what news we see on the networks, shouldn’t we all better understand how they work? Why not make their inner workings public, like open source software?

Others say that doing this would make it easier for bad actors to understand and manipulate the programs.

Can’t the government come up with laws to make sure that news feeds are unbiased and don’t spread false information? Or, perhaps there should be some watchdog group or fact checking organization to keep the networks “honest.”

Again, I think it is incumbent on the tech companies to clean up the mess. But this should not go so far as making them hand over their algorithms. It’s their intellectual property. And I am leery of government oversight or any third party organization that polices truth telling by decree.

I am in favor of setting up a group that proposes standards in fake news detection and eradication. This industry body could factor in interests of all parties – the social networks, government, users, and media to issue guidelines and also audit the networks (on a voluntary basis – think the MPAA movie ratings, the Parental Advisory Label for recorded music, or Comics Code Authority).

If Facebook, Google, Reddit, Apple News and others want to earn the seal of approval, they’d need to open up their systems and algorithms to inspection to show they are not aiding the propagation of fake news.

 

 

 

Internet Society Drills Down on Fake News


I attended the Internet Society’s “Content Rules?!” session the other week.   The panel drilled down on what we now call The Fake News problem (I couch it like this because, as you’ll see it’s not a new one), defining it and exploring causes and solutions.

There’s been a lot already written about fake news. It’s turned into a real meme and hot button, but there’s been lots of noise and confusion. That’s not surprising because it is a complex topic, one that only recently hit our radars in the wake of the election.

Giving it a name gave it legs, a thing to blame (in some cases just because someone doesn’t like an article), and evoked lots of teeth gnashing. The session gave me the opportunity to hear from some very smart people from different sides, better understand the issues and crystallize my thoughts about how we might address the problem.

Not a New Problem

Journalist and American University Professor Chuck Lewis started by explaining that fake news has been around for years in various forms, e.g. government disinformation and propaganda. Toni Muzi Falcone’s DigiDig wrap (in Italian) also discussed this.

“The irony of us feeling victimized by fake news is pretty thick,” he said. “We’ve gone from truth to truthiness to a post-truth society, and now it’s fake news,” said Chuck, “but it’s been going on for centuries.”

He blamed the number of people “spinning information” vs. reporting it, and the ratio of PR people to journalists (which has grown to 5:1), and said it is a crisis for journalism. The big questions are, who decides what is true, and how do you set standards for 200+ countries? We’ve traditionally relied on the press to be content mediation experts.

“We are at a critical, disturbing crossroad,” Lewis said, as “No one wants the government to be the mediators.”

A Systemic Problem

Compounding the problem are the changing ways we get info, and the growing influence of social networks. Gilad Lotan, head of data science at Buzzfeed, discussed this.

He’s studied political polarization in Israel. Gilad showed some fancy social graphs that tracked the spreading of stories in the wake of IDF’s bombing of a Palestinian school. Two different story lines emerged. Neither was “fake” Gilad explained; “They just chose to leave certain pieces of info out in order to drive home points of a narrative.”

Gilad further discussed how your network position defines the stories you see; this leads to polarization and homophily (a fancy way of saying echo chamber). He also explained the role of algorithmic ranking systems. “You’re much more likely to see content which aligns with your viewpoints,” he said. This spawns “personalized propaganda spaces.”

It gives bad actors a way to game the system. Gilad illustrated this via what had been the elephant in the room – the 2016 US presidential election. He shared images that showed phantom groups manipulating the spread of information.

“The awareness of how algorithms work gave them a huge advantage. To this day, if you search for ‘Hillary’s Health’ on YouTube or Google, you see conspiracy theories at the top.”

Moderator Aram Sinnreich, associate professor at American University added: “My impression as a media scholar and critic… is that there’s been a lot of finger-pointing… everyone feels that there’s been a hollowing out of the Democratic process… undermining of the traditional role that the media has played as the gatekeeper of the shared narrative and shared truths; people want to hold the platforms accountable.”

Flavors of Fake News

Andrew Bridges, a lawyer who represents tech platforms, said that it is important to define the problem before considering solutions. The knee-jerk reaction has been to try to turn social networks into enforcement agencies, but that would be a mistake, according to Bridges. That’s because there are seven things calling fake news that could have different solutions (I list them with the examples he cited):

  1. Research and reporting with a pretense of being objective (e.g., major newspapers)
  2. Research and reporting in service of a cause (National Review, Nation, New Republic)
  3. Pretend journalism – claim to be a news source but is a curator (Daily Kos)
  4. Lies – the ones that Politifact and others give Pinocchio noses or “pants on fire” awards
  5. Propaganda – the systematic pattern of lying for political gain
  6. Make-believe news, like Macedonian sites.  They make up news from whole cloth.
  7. Counterfeit sites – they make you think you are at ABC News.com, for example

Then, he dramatically challenged the panel and audience to label certain big ticket topics as fake news or not: Evolution, global warming, the importance of low-fat diets, the importance of low carb diets.

Bridges said that there’s not necessarily a quick fix or tech solution to the problem. “These things have been out there in society, in front of our eyes for years.”  He likened the problem to gerrymandering, gated communities and questions about Hillary’s health.

Some have proposed algorithmic transparency (not surprisingly, Bridges thinks it is an awful idea; “Opening them up just makes it easier to game the system”).

What could work, according to the lawyer? “I think we should look to algorithmic opacity, and brand values of the organizations applying the algorithm.” What about content moderation? He said “Do we turn it over to a third party, like a Politifact? Who moderates the moderator? We know what moderation is – it’s censorship.”

In Bridges view, education is important. We should teach the importance of research and fact checking, and keep each other honest: “Friends don’t let friends spread fake news.”

Other Challenges

Jessa Lingel, Ph.D. and assistant professor at Annenberg School of Communications, seemed to be the youngest on the panel and spoke up for millennials:

“You can’t promise a generation of Internet-loving people a sense of control and agency over content and not expect this breakdown in trust.” She talked about the growth of citizen-driven journalism and the shift from content generation to interpretation. Jessa bemoaned the digital natives’ loss of innocence:

“We were promised a Democratic web and got a populist one; a web that that connects us to different people, instead we got silos. Geography wasn’t supposed to matter… anyone with an Internet connection is the same… instead, geography matters a lot.”

Jessa siad that algorithmic transparency is important but said that it is not enough. “Opacity? I do want to pay attention to the man behind the curtain. We need more than that tiny little button that explains ‘why did I get this ad?’”

Up Next: More on Solutions

As you have hopefully seen from my post, there are many opinions on the situation, and it’s a complex topic.

What do you think? In my next post, I’ll share my thoughts on fake news problems and solutions.

How do you Solve a Problem Like Big Data?

This post is not about how to analyze big data – it is about impact and implications for laws, business and our society.  How do we ensure that our increasing reliance on data, algorithms and AI does not come at a cost?

Below, I include some great articles on the topic.  Please read on, and would love to hear your thoughts via the comments section below.

Bloomberg: Battling the Tyranny of Big Data

Mark Buchanan explores recent research and efforts, such as the Open Algorithms Projects; he says we must control how data are used, second, open up by making it more widely available, then re-balance power between companies and individuals.

Mashable: We put too much Trust in Algorithms, and it’s Hurting our Most Vulnerable

Algorithms have gone wild in Ariel Bogle’s piece; they incorrectly label welfare recipients as cheats, and blacks, recidivist risks, give rise to “mathwashing.”

Huffington Post: We need to know the Algorithms the Government uses to make important Decisions about Us

Writer Nick Diakopoulos, Fellow at Columbia Tow Center; Assistant Professor of Journalism, University of Maryland, cites similar issues, and shares a case study in transparency in which he “guided students in submitting FOIA requests to each of the 50 states. We asked for documents, mathematical descriptions, data, validation assessments, contracts and source code related to algorithms used in criminal justice, such as for parole and probation, bail or sentencing decisions.”

PHYS ORG: Opinion – Should Algorithms be Regulated?

Offers a point vs. counterpoint; Markus Ehrenmann of Swisscom says “Yes.” Mouloud Dey of SAS says “No.”

Seth Godin’s blog: The Candy Diet

The marketing guru says that algorithms are dumbing down media.

The Drum: In the Post Truth Era, the Quest to Surface Credible Content has only Just Begun

Lisa Lacy reports that Google amended its algorithm to combat holocaust deniers; but if manual intervention is needed for high profile fails, but what about other important issues that don’t get as much attention?

Foundation for Economic Education: What Happens when your Boss is an Algorithm?

Cathy Reisenwitz offers a nice primer, and argues for making algorithms open source.

The New York Times: Data Could be the Next Tech Hot Button for Regulators

Steve Lohr voices concerns about the growing market power of big tech, and explains potential antitrust issues arising from their collection of data. He writes: “The European Commission and the British House of Lords both issued reports last year on digital “platform” companies that highlighted the essential role that data collection, analysis and distribution play in creating and shaping markets. And the Organization for Economic Cooperation and Development held a meeting in November to explore the subject, “Big Data: Bringing Competition Policy to the Digital Era.”

Fake News, AI and Bias, Oh My!

First published on DigiDig

There have been quite a few relevant articles recently, so I thought I would write this post which includes links and brief summaries.

Real Interest in Fake News

Fake news continues to be a hot story that shows what can go wrong when algorithms choose what we read. I covered the topic here blog when it first broke a few weeks ago.

Ryan Holmes of HootSuite wrote for the Observer in The Problem Isn’t Fake News – it’s Bad Algorithms: “As algorithms mature, growing more complex and pulling from a deeper graph of our past behavior, we increasingly see only what we want to see… More dangerous than fake news, however, is all the real news that we don’t see. For many people, Facebook, Twitter and other channels are the primary… place they get their news. By design, network algorithms ensure you receive more and more stories and posts that confirm your existing impression of the world and fewer that challenge it. Overtime, we end up in a “filter bubble”‘

Writing for DigiDay, Lucia Moses explained Why Top Publishers are Still Stuck Distributing Fake News. It is not just about news feed algorithms, but also involves the “intelligence” behind automatically-served programmatic ads (native ads can look like real articles). She shares an example in which the NY Times displayed a fake news ad next to their real story on fake news (got that?).

Algorithms and Bias

One of the primary concerns about algorithms relates to bias. How do biases infect data-driven computations? And in which ways do programs discriminate?

Kristian Hammond answers the first question in the TechCrunch story 5 Unexpected Sources of Bias in AI. He ponders whether bias is a bug or feature, and says: “Not only are very few intelligent systems genuinely unbiased, but there are multiple sources for bias… the data we use to train systems, our interactions with them in the ‘wild,’ emergent bias, similarity bias and the bias of conflicting goals. Most of these sources go unnoticed. But as we build and deploy intelligent systems, it is vital to understand them so we can design with awareness and hopefully avoid potential problems.”

Alvin Chang writes in Vox about How the Internet Keeps Poor People in Poor Neighborhoods. He shares an example of a Facebook ad that violates the Fair Housing Act by excluding certain users from seeing it. This is blatant, but algorithmic discrimination can be a lot more subtle, and thus harder to root out, he explains.

Artificial Intelligence for Dummies

If you are new to algorithms and AI, you might want to read this Digital Trends story, which breaks down the differences between machine learning, AI, neural networks, etc.

 

AI and Algorithms in the News

board-1364652_1920Cross-posted on DigiDig

I have been carefully watching for stories about the growing influence of technology in our lives, and sharing links with the DigiDig team via Toni Muzi Falcone. We discussed turning these into a weekly digest or DigiDigest (I truly hope that puns and weak humor attempts are not lost in translation; otherwise my writing tenure will be short here).

So, without further adieu, I list three very relevant stories.

Mother Nature’s Network – How Algorithms Influence us Every Day

This article describes ways in which algorithms help and hurt us. Cory Rosenberg worries that technology reduces our interests, backgrounds and behaviors to a number, and quotes Michele Willson of Curtin University in Perth, Australia: “Time, bodies, friendships, transactions, sexual preferences, ethnicity, places and spaces are all translated into data for manipulation and storage within a technical system or systems. On that basis alone, questions can be posed as to… how people see and understand their environment and their relations.”
Cory asks: “But isn’t the thought of humans as data an affront to our uniqueness?”
The article share examples of bias, e.g. “Google’s online advertising system shows ads for high-income jobs to males much more so than to females,” and examples of algorithms that help, like in “understanding” preferences in music and dating.

Mashable – Online Shopping Algorithms have us in a Decision Rut

Lance Ulanoff sees a “fundamental flaw in the technology designed to serve up things we might like. They are based entirely on past choices and activities and leave zero room for improvisation and unpredictability.” He bemoans the loss of serendipity in shopping recommendations, for example. It’s a timely topic in the US, as Cyber Monday was yesterday and the holidays are looming.

Lance writes: “If we continue to follow the choices made for us on social, services, subscription and retail sites, we will all soon be living a very vanilla life. Our friends will be the same kinds of people, our social feeds will offer just one point of view and our gift-giving will surprise no one.It is time to stand up and say, ‘You don’t know me.'”

Seems Lance would disagree with Cory’s view on the technology’s benefits.

Quanta Magazine – How to Force our Machines to Play Fair

Quanta writer Kevin Hartnett interviews author and Microsoft Distinguished Scientists Cynthia Dwork, who pioneered ideas behind “differential privacy.” She is now taking on fairness in algorithm design.

Cynthia says: “algorithms… could affect individuals’ options in life.. to determine what kind of advertisements to show people. We may not be used to thinking of ads as great determiners of our options in life. But what people get exposed to has an impact on them.”

She explores individual vs. group fairness and introduces the idea of “fair affirmative action.” Dwork would love to find a metric or way to ensure that “similar people [get] treated similarly,” but concludes that it is a thorny problem that people must first come to terms with before training computers to make these judgments.

In Defense of “Fake News”

More people are wondering about the weird crap that mysteriously appears in their news

Is News Today too Much Like the Magic 8 Ball?

Is News Today too Much Like the Magic 8 Ball?

feeds. How much is fake news? Did disinformation tilt an election? What are Google and Facebook going to do to clean up the mess?

You could almost hear the entire PR industry shifting uncomfortably amidst the backlash. I mean, crafting news (that some might call fake, or at least a stretch) is our stock in trade. We package propaganda as newsworthy information and sell it to the media; and, increasingly publish directly to the Web and social networks.

I understand that the fuss is more about blatant lies, not the average press release. But it highlights the challenges of determining what is newsworthy and true; a role that is increasingly being taken on by algorithms.

The Web and social media gave us all ways to easily share and spread information. This can include rumor, conjecture, commercial information, news, and yes, slander and outright lies.

I would never defend the last two; but will fight for our right to issue press releases, and traffic in other kinds of info. Any good system needs to be able to deal with all of this, i.e. anticipate some BS and surface the most credible and significant information, whether via the wisdom of the crowds, programs or a combination.

It is naïve to think that a publication, editors, or algorithms (which of course are written by humans) can present news without bias. The journalistic piece you just wrote might be pristine, free of opinion; but the very act of deciding which stories to feature shows partiality.

That said, the social networking platforms where more of us are getting news can do a much better job of separating the wheat from the chaff. I thought I’d share some of the great stories I’ve seen about the controversy and takeaways from each.

TechCrunch – How Facebook can Escape the Echo Chamber

Anna Escher says “Facebook is hiding behind its [position that] ‘we’re a tech company, not a media company’ … For such an influential platform that preaches social responsibility and prioritizes user experience, it’s irresponsible …”

She recommends that they bring journalists into the process, remove the influence of engagement on news selection during elections, and expand Trending Topics to show a greater diversity of political stories – not just the ones that are the most popular.

Tim O’Reilly – Media in the Age of Algorithms

Tim’s exhaustive Medium piece looks at all sides. He rails against “operating from an out-of-date map of the world [in which] algorithms are overseen by humans who intervene in specific cases to compensate for their mistakes,“ and says:

“Google has long demonstrated that you can help guide people to better results without preventing anyone’s free speech… They do this without actually making judgments about the actual content of the page. The ‘truth signal’ is in the metadata, not the data.”

Tim makes an analogy between news algorithms and airplanes “Designing an effective algorithm for search or the newsfeed has more in common with designing an airplane so it flies… than with deciding where that airplane flies.”

He cited an example from the history of aircraft design. While it’s impossible to build a plane that doesn’t suffer from cracks and fatigue… “the right approach … kept them from propagating so far that they led to catastrophic failure. That is also Facebook’s challenge.”

Nieman Lab – It’s Time to Reimagine the Role of a Public Editor

Mike Ananny writes about the public editor’s role, and the challenges they face in the increasingly tech-driven environment. He writes:

“Today, it is harder to say where newsrooms stop and audiences begin. Public editors still need to look after the public interest, hold powerful forces accountable, and explain to audiences how and why journalism works as it does — but to do so they need to speak and shape a new language of news platform ethics.”

He asks “Will the public editor have access to Facebook’s software engineers and News Feed algorithms, as she does to Times journalists and editorial decisions?” and says:

“… public editors must speak a new language of platform ethics that is part professional journalism, part technology design, all public values. This means a public editor who can hold accountable a new mix of online journalists, social media companies, algorithm engineers, and fragmented audiences — who can explain to readers what this mix is and why it matters.”

Latest PR Gambit: Publishing on Platforms

Back in the day (“the day” being about 10 years ago), we had a simple message for PR shoe-737084_1920clients who wanted to get in on the social media and blogging action.

It was: “Go forth and blog too. Master the channels that are accessible to all.” Those who took the time to produce quality content, nurture social communities and post consistently saw their online influence grow.

Now, the open web is being challenged by the growth of social networking platforms. They’re places we go to connect, and get entertained and informed. Their news clout is growing, as the networks are increasingly publishers and aggregators of content. The social networks reach vast audiences with precise targeting – compelling attributes for marketers.

In short, if you are in the news business or want to promote your own, you are missing out if you are not on Facebook, LinkedIn, Twitter, etc.

But there are a number of challenges along the way. It takes PR out of our media-centric comfort zones. It’s not obvious how to use social networking channels to accomplish your goals, which generally include coverage KPIs.

Sure, many in PR have jumped on the social media and content marketing bandwagons. We can handle Tweeting and blogging quite well. But getting your news seen and covered or appreciated by the right audiences, especially if your profile does not already have umpteen million friends/followers, is another matter.

Success generally requires a combination of paid and organic promotion as well as an understanding of the algorithms, those wonky programs that determine what appears in our news feeds. But they are black boxes and constantly changing. Plus, ad options may be unfamiliar, and they’re also moving targets.

How does one figure this all out? Listen, read, and more important, experiment. Dip your toes in. Test, validate, then repeat.

Reading this blog is a good start, as it offers commentary, articles about best practices and links to the right resources. The networks can be opaque, when it comes to specifics about their algorithms – but they do inform about changes and make recommendations.

In short, there are no pat answers, although one could invoke advice similar to the words at the beginning of the article: go forth and publish on Facebook (for example). Learn about the secrets of shareable content and how to get into the news feed.

I’ll close with an example from the world of politics, which seems fitting since the election has been front and center. It’s an article that ran awhile back in the NY Times Sunday magazine.

What do you think? Could a similar approach work beyond the field of politics? What ideas does this give you for PR? See the link and excerpts below, and please share your comments.

Inside Facebook’s… Political Media Machine
[Facebook’s] algorithms have their pick of text, photos and video produced and posted by established media organizations… But there’s also a new and distinctive sort of operation that has become hard to miss: political news and advocacy pages made specifically for Facebook, uniquely positioned and cleverly engineered to reach audiences exclusively in the context of the news feed…

These are news sources that essentially do not exist outside of Facebook… cumulatively, their audience is gigantic: tens of millions of people. On Facebook, they rival the reach of their better-funded counterparts in the political media…

But they are, perhaps, the purest expression of Facebook’s design and of the incentives coded into its algorithm — a system that has already reshaped the web…
Truly Facebook-native political pages have begun to create and refine a new approach to political news…. The point is to get [users] to share the post that’s right in front of them. Everything else is secondary.

DigiDig Studies the Impact of AI and Algorithms on Society

banner-1571986_1920Full story is on Flack’s Revenge

I’ve had many great conversations with my friend and PR authority Toni Muzi Falcone about the impact of technology on the field and society at large. Recently he told me about a new effort that he helped conceive – DigiDig – a website and citizen-led group dedicated to studying this area.

They started in Italy (the website for now is almost entirely in Italian) and have an international focus. I asked Toni to tell me more, and he shared the following:

“DigiDig questions the algorithmic society. It is a start-up community, launched on October 9, 2016, of some 150 Italian digitally active and prominent citizens wishing to better understand, discuss and raise awareness of peers on issues related to ‘user power’ vis-à-vis XXI century global robber barons.

The intention is to connect with the many similar or analog groups that populate the global digital space. Our immediate focus includes Brussels and New York, but we also wish to dialog with New Zealand, Kazakhstan and Namibia.

Its promoters are academics, intellectuals, journalists, managers, lobbyists, elected officials, communicators, writers, sociologists, and polemicists.

Following two open house sessions in Rome and Milano last June, a coordinating committee of six was formed and a web space just opened a few days ago containing a shared ‘manifesto’ plus opinions and comments in Italian and English.

The manifesto, titled: ‘the algorithm as a technology of freedom?’, defines its main issue as

(…..) the active and critical observation of the true nature of the global process reorganizing social and economic life, focused on the development and exchange of cognitive products of artificial intelligence.

As algorithms simplify digital procedures as well as the automation of humanity’s most delicate and discretionary activities, we cannot accept that such process proceeds in disrespect of the elementary rules of transparency, information and access to participation to its decision-making processes and operational standards.

If it is true that –as often affirmed by creators, shareholders and executives of those global groups – we are in fact confronted with a new ‘public sphere and/or space’ (and we very much believe it is so) – we also insist that the mechanisms creating new alphabets, social structures and determining influences over individual choices, need to be understandable, shared, socially negotiable and integrated.(…).

No membership fees, but requests for contributions via PayPal at info@digidig.it

Breaking into Facebook’s News Feed: 3 Stories, 9 Tips

Facebook has made quite a few changes to its algorithm and news feed in recent months, as has been news-1592592_1280chronicled on this blog.  Digiday said that some publishers are responding by focusing more efforts on SEO.

But where does this leave brands and marketers who want to target Facebook users with news and content?

You need to change with times. These days, your content should be informative, relevant and entertaining – it helps if the topics resonate with your friends and family.

There were quite a few good posts that recommended strategies in light of the updates.  Here were three that stood out, and three tips for each.

In A Publisher’s Guide to Facebook’s News Feed Updates, the Newswhip blog shared these tips:

  1. Focus on organic reach and stories shared by actual users vs. brand pages
  2. Use engagement metrics to inform strategy and content creation
  3. Stay attuned to what interests your readers and work hard to serve a niche audience

The same blog follow up with more good advice: How to Adapt to Facebook’s “Personally Informative” News Feed. It offered a helpful pointer to how Facebook defines Personally Informative. This means staying in tune with audience interests. Newswhip recommends:

  1. Creating an RSS aggregator featuring the news sources favored by your desired audience
  2. Building your personal brand – the changes favor peer-to-peer sharing
  3. Being genuine, avoiding clickbait and deception

To the last point, Facebook’s more recent changes target and penalize click bait.  The Hootsuite blog featured a story on How to Get Clicks without resorting to Clickbait.  It recommends:

  1. Be accurate, the headline shouldn’t promise more than the content delivers
  2. Create an emotional connection
  3. Take the time and care to craft an effective headline