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Can Effective Regulation Reduce the Impact of Divisive Content on Social Networks?



Amid a new storm of controversy sparked by The Facebook Files, an expose of various internal research projects which, in some ways, suggest that Facebook isn’t doing enough to protect users from harm, the core question that needs to be addressed is often being distorted by inherent bias and specific targeting of Facebook, the company, as opposed to social media, and algorithmic content amplification as a concept.

That is, what do we do to fix it? What can be done, realistically, that will actually make a difference; what changes to regulation or policy could feasibly be implemented to reduce the amplification of harmful, divisive posts that are fueling more angst within society as a result of the increasing influence of social media apps?

It’s important to consider social media more broadly here, because every social platform uses algorithms to define content distribution and reach. Facebook is by far the biggest, and has more influence on key elements, like news content – and of course, the research insights themselves, in this case, came from Facebook.

The focus on Facebook, specifically, makes sense, but Twitter also amplifies content that sparks more engagement, LinkedIn sorts its feed based on what it determines will be most engaging. TikTok’s algorithm is highly attuned to your interests.

The problem, as highlighted by Facebook whistleblower Frances Haugen is algorithmic distribution, not Facebook itself – so what ideas do we have that can realistically improve that element?

And the further question then is, will social platforms be willing to make such changes, especially if they present a risk to their engagement and user activity levels?

Haugen, who’s an expert in algorithmic content matching, has proposed that social networks should be forced to stop using engagement-based algorithms altogether, via reforms to Section 230 laws, which currently protect social media companies from legal liability for what users share in their apps.

As explained by Haugen:

“If we had appropriate oversight, or if we reformed [Section] 230 to make Facebook responsible for the consequences of their intentional ranking decisions, I think they would get rid of engagement-based ranking.”

The concept here is that Facebook – and by extension, all social platforms – would be held accountable for the ways in which they amplify certain content. So if more people end up seeing, say, COVID misinformation because of algorithmic intervention, Facebook could be held legally liable for any impacts.

That would add significant risk to any decision-making around the construction of such algorithms, and as Haugen notes, that may then see the platforms forced to take a step back from measures which boost the reach of posts based on how users interact with such content.

Essentially, that would likely see social platforms forced to return to pre-algorithm days, when Facebook and other apps would simply show you a listing of the content from the pages and people you follow in chronological order, based on post time. That, in turn, would then reduce the motivation for people and brands to share more controversial, engagement-baiting content in order to play into the algorithm’s whims.

The idea has some merit – as various studies have shown, sparking emotional response with your social posts is key to maximizing engagement, and thus, reach based on algorithm amplification, and the most effective emotions, in this respect, are humor and anger. Jokes and funny videos still do well on all platforms, fueled by algorithm reach, but so too do anger-inducing hot takes, which partisan news outlets and personalities have run with, which could well be a key source of the division and angst we now see online.

To be clear, Facebook cannot solely be held responsible for such. Partisan publishers and controversial figures have long played a role in broader discourse, and they were sparking attention and engagement with their left-of-center opinions long before Facebook arrived. The difference now is that social networks facilitate such broad reach, while they also, through Likes and other forms of engagement, provide direct incentive for such, with individual users getting a dopamine hit by triggering response, and publishers driving more referral traffic, and gaining more exposure through provocation.

Really, a key issue in when considering the former outcome is that everyone now has a voice, and when everyone has a platform to share their thoughts and opinions, we’re all far more exposed to such, and far more aware. In the past, you likely had no idea about your uncle’s political persuasions, but now you know, because social media reminds you every day, and that type of peer sharing is also playing a role in broader division.

Haugen’s argument, however, is that Facebook incentivizes this – for example, one of the reports Haugen leaked to the Wall Street Journal outlines how Facebook updated its News Feed algorithm in 2018 to put more emphasis on engagement between users, and reduce political discussion, which had become an increasingly divisive element in the app. Facebook did this by changing its weighting for different types of engagement with posts.

Facebook algorithm diagram

The idea was that this would incentivize more discussion, by weighting replies more heavily – but as you can imagine, by putting more value on comments, in order to drive more reach, that also prompted more publishers and Pages to share increasingly divisive, emotionally-charged posts, in order to incite more reactions, and get higher share scores as a result. With this update, Likes were no longer the key driver of reach, as they had been, with Facebook making comments and Reactions (including ‘Angry’) increasingly important. As such, sparking discussion around political trends actually became more prominent, and exposed more users to such content in their feeds.

The suggestion then, based on this internal data, is that Facebook knew this, it knew that this change had ramped up divisive content. But they opted not to revert back, or implement another update, because engagement, a key measure for its business success, had indeed increased as a result.

In this sense, removing the algorithm motivation would make sense – or maybe, you could look to remove algorithm incentives for certain post types, like political discussion, while still maximizing the reach of more engaging posts from friends, catering to both engagement goals and divisive concerns.

That’s what Facebook’s Dave Gillis, who works on the platform’s product safety team has pointed to in a tweet thread, in response to the revelations.

As per Gillis:

At the end of the WSJ piece about algorithmic feed ranking, it’s mentioned – almost in passing – that we switched away from engagement-based ranking for civic and health content in News Feed. But hang-on – that’s kind of a big deal, no? It’s probably reasonable to rank, say, cat videos and baby photos by likes etc. but handle other kinds of content with greater care. And that is, in fact, what our teams advocated to do: use different ranking signals for health and civic content, prioritizing quality + trustworthiness over engagement. We worked hard to understand the impact, get leadership on board – yep, Mark too – and it’s an important change.

This could be a way forward, using different ranking signals for different types of content, which may work to enable optimal amplification of content, boosting beneficial user engagement, while also lessening the motivation for certain actors to post divisive material in order to feed into algorithmic reach.

Would that work? Again, it’s hard to say, because people would still be able to share posts, they’d still be able to comment and re-distribute material online, there are still many ways that amplification can happen outside of the algorithm itself.

In essence, there are merits to both suggestions, that social platforms could treat different types of content differently, or that algorithms could be eliminated to reduce the amplification of such material.

And as Haugen notes, focusing on the systems themselves is important, because content-based solutions open up various complexities when the material is posted in other languages and regions.

“In the case of Ethiopia, there are 100 million people and six languages. Facebook only supports two of those languages for integrity systems. This strategy of focusing on language-specific, content-specific systems for AI to save us is doomed to fail.”

Maybe, then, removing algorithms, or at least changing the regulations around how algorithms operate, would be an optimal solution, which could help to reduce the impacts of negative, rage-inducing content across the social media sphere.

But then we’re back to the original problem that Facebook’s algorithm was designed to solve – back in 2015 Facebook explained that it needed the News Feed algorithm not only to maximize user engagement, but also to help ensure that people saw all the updates of most relevance to them.

As it explained, the average Facebook user, at that time, had around 1, 500 posts eligible to appear in their News Feed on any given day, based on Pages they’d liked and their personal connections – while for some more active users, that number was more like 15,000. It’s simply not possible for people to read every single one of these updates every day, so Facebook’s key focus with the initial algorithm was to create a system that uncovered the best, most relevant content for each individual, in order to provide users with the most engaging experience, and subsequently keep them coming back.

As Facebook’s chief product officer Chris Cox explained to Time Magazine:

“If you could rate everything that happened on Earth today that was published anywhere by any of your friends, any of your family, any news source, and then pick the 10 that were the most meaningful to know today, that would be a really cool service for us to build. That is really what we aspire to have News Feed become.”

The News Feed approach has evolved a lot since then, but the fundamental challenge that it was designed to solve remains. People have too many connections, they follow too many Pages, they’re members of too many groups to get all of their updates, every day. Without the feed algorithm, they will miss relevant posts, relevant updates like family announcements and birthdays, and they simply won’t be as engaged in the Facebook experience.

Without the algorithm, Facebook will lose out, by failing to optimize for audience desires – and as highlighted in another of the reports shared as part of the Facebook Files, it’s actually already seeing engagement declines in some demographic subsets.

Facebook engagement over time

You can imagine that if Facebook were to eliminate the algorithm, or be forced to change its direction on this, that this graph will only get worse over time.

Zuck and Co. are therefore not likely to be keen on that solution, so a compromise, like the one proposed by Gillis, may be the best that can be expected. But that comes with its own flaws and risks.   

Either way, it is worth noting that the focus of the debate needs to shift to algorithms more broadly, not just on Facebook alone, and whether there is actually a viable, workable way to change the incentives around algorithm-based systems to limit the distribution of more divisive elements.

Because that is a problem, no matter how Facebook or anyone else tries to spin it, which is why Haugen’s stance is important, as it may well be the spark that leads us to a new, more nuanced debate around this key element.


Reports Show that Facebook Usage is Up, as Meta Continues to Develop its AI Targeting Models



Reports Show that Facebook Usage is Up, as Meta Continues to Develop its AI Targeting Models

While Facebook is no longer the cool app, especially among younger audiences, it remains a key platform for many users, and its capacity to keep people updated on important updates from friends and family is likely to ensure that many continue to return to the app every day for some time yet.

But more than that, Facebook usage is actually increasing, according to internal insights viewed by The Wall Street Journal, which also include some interesting notes on overall Facebook and Instagram usage trends.

As per WSJ:

Data gathered in the middle of the fourth quarter showed that time spent on [Facebook] was up worldwide, including in developed markets, over the course of a year.”

Which seems unusual, given the subsequent rise of TikTok, and short form video more generally. But actually, Facebook has been able to successfully use the short-form video trend to drive more usage – despite much criticism of the platform’s copycat Reels feature.

Indeed, Reels consumption is up 20%, and has become a key element in Meta’s resurgence.  

How is it finding success? Increased investment in AI, which has driven big improvements in the relevance models that fuel both Reels and its ads, which are also now driving better response.

On Reels, Meta’s systems are getting much better at showing users the Reels content that they’re most likely to be interested in. You’ve likely noticed this yourself – what was initially a mess of random clips inserted into your Facebook feed has now become more focused, and you’re probably finding yourself expanding a Reels clip every now and then, just to see what it’s about.

Reels has actually been too successful:

“Because ads in Reels videos don’t currently sell for as much as those sold against regular posts and stories, Reels’ growing share of content consumption was denting ad revenue. To protect the company’s earnings, the company cut back on promoting Reels, which lowered watch time by 12%.

So again, while Meta has been criticized for stealing TikTok’s format, it’s once again shown, just as it did with Stories, that this is a viable and beneficial pathway to keeping users engaged in its apps.

You might not like it, but replication works in this respect.

But for marketers, it’s likely the development of Meta’s AI targeting tools for ads that’s of most interest.

Over time, many performance advertisers have been increasingly recommending that marketers trust Meta’s AI targeting, with newer offerings like Advantage+ driving strong results, with far less manual targeting effort.

Advantage+ puts almost total trust in Meta’s AI targeting systems. You can choose a couple of targeting options for your campaigns, but for the most part, the process is designed to limit manual impact, in order to let Meta’s systems determine the right audience for your ads.

Which may feel like you’re ceding too much control, but according to Meta, its continued AI investment is now driving better results.

Heavy investment in artificial intelligence tools has enabled the company to improve ad-targeting systems to make better predictions based on less data, according to the interviews and documents […] That, along with shifting to forms of advertising less dependent on harvesting user data from off its platforms, are key to the company’s plans to overcome an Apple privacy change that restricted Meta’s capacity to gather information about what its users do outside its platforms’ walls, the documents show.”

That’s likely worth considering in your process, putting more trust in Meta’s targeting systems to drive better results. At the least, it may be worth experimenting with Meta’s evolving AI for ad targeting. 

It’s not all good news. Meta also notes that while time spent in its apps is on the rise, creation and engagement is declining, with fewer people posting to both Facebook and Instagram than they have in the past.

That’s particularly true among younger audiences, while notably, usage of Instagram Stories is also in decline, down 10% on previous levels.

So while Meta is driving more engagement from Reels, which draws on content from across the app, as opposed to the people and Pages you follow, that’s also led to a decline in user posting.

Is that a bad thing? I mean, logically, engagement is important in keeping people interested in the app, and Meta also relies on those signals to help refine its ad targeting. So it does need users to be sharing their own content too, but if it can get more people spending more time in its apps, that will help it maintain advertiser interest.

In essence, despite all of the reports of Facebook’s demise, it remains a key connective platform, in various ways, while Meta’s improving ad targeting systems are also helping to drive better results, which will keep it as a staple for brands moving forward.

If you were thinking of diversifying your social media marketing spend this year, maybe don’t reduce Facebook investment just yet.

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Effective Ways To Personalize Your Customer Touch Points Even More In 2023



Effective Ways To Personalize Your Customer Touch Points Even More In 2023

Will 2023 be the year of personalization? Consumers hope so. For the past two years, shoppers have been craving the personal touch: In 2021, McKinsey & Company noted that 71% of customers expected companies to deliver personalization. In 2022, a Salesforce survey found that 73% of people expected brands to understand their needs and expectations. So, this year is looking like one where personalization can no longer be seen as a “nice to have.”

The problem, of course, is how to get more personalized. Many companies have already started to dabble in this. They greet shoppers by name on landing pages. They rely on CRMs and other tools to use historical information to send shoppers customized recommendations. They offer personalized, real-time discounts to help buyers convert their abandoned shopping cart items to actual purchases.

These are all great ideas. The only problem is that they’ve become widespread. They don’t move the needle on the customer experience anymore. Instead, they’re standard, expected, and kind of forgettable. That doesn’t mean you can afford to stop doing them. It just means you must devise other ways to pepper personalization throughout your consumer interactions.

If you are scratching your head on how to outdo 2022’s personalization in 2023, try implementing the following strategies:

1. Go for full-blown engagement on social media.

One easy way to give the personal touch is through your social media business pages. Social media use just keeps growing. In 2022, there were about 266 million monthly active users (or MUAs) on Facebook, one billion on Instagram, and 755 million on TikTok. Not all these active users will fall into your target audiences, but plenty of them will.

Make engaging with your social followers one of this year’s goals. People spend a lot of time on social media. It’s where many of them “live,” so it only makes sense that it should be a place to drive personalization.

One quick way to ratchet up your company’s personal touch on social media is to personalize all your retargeted ads. Quizzes can also offer a chance for personalization. Simply set up an engaging quiz and allow people to share their results. It’s a fun way to build brand recognition and bond with consumers. Of course, there’s nothing wrong with going very personal and answering all comments. Depending on your team’s size and the number of comments you receive, this might be a viable option.

2. Leverage AI to go beyond basic demographics.

Most companies rely on customer demographic information to bolster personalization efforts. The only trouble with this tactic is that demographics can’t tell the whole story. It’s impossible to get a lot of context about individual users (such as their lifestyles, personal preferences, and motivators) just from knowing their age, gender, or location. Though demographic data is beneficial, it can cause some significant misses.

Michael Scharff, CEO and cofounder of Evolv AI, explains the workaround for this problem: “The most natural, and therefore productive, personalization efforts use demographics as a foundation and then layer in user likes, dislikes, behaviors, and values.”

You can leverage AI’s predictive and insightful capabilities to uncover real-time user insights. Scharff recommends this technique because it allows you to stay in sync with the fast-moving pace of consumer behavior changes. He adds that AI can be particularly beneficial with the coming limits to third-party cookie access because it can be a first-party data source, allowing you to maintain customer knowledge and connection.

To flesh out your organization’s strategy, look to other companies that have gone beyond demographics. Take Netflix, for example, which constantly tweaks its AI algorithm to help improve personalized content recommendations. Bottom line? Going deeper than surface information makes all the sense in the world if you want to show customers you know them well.

3. Keep your data spotless.

The better your data, the better your personalization efforts. Period. Unfortunately, you are probably sitting on a lot of unstructured or otherwise tricky-to-use (or impossible-to-use) data. One recent Great Expectations survey revealed that 77% of data practitioners have data quality problems, and 91% say that this is wreaking havoc on their companies’ performance.

You can’t personalize anything with corrupt or questionable data. So, do your best to find ways to clean your data promptly and routinely. For example, you might want to invest in a more centralized data system, particularly if the personalization data you rely on is scattered in various places. Having one repository of data truth makes it easier to know if the information on hand is ready to use.

Another way to tame your data is to automate as many data processes as possible. Reducing manual manipulation of data lessens the chance of human error. And you’ll feel more confident with all your personalization efforts if you can trust the reliability and health of your data.

4. Go for nontechnical personalization.

It’s the digital age, but that doesn’t mean every touchpoint has to be digitized. Consumers often react with delight and positivity when they receive personalization in decidedly nontech forms. (Yes, you can use tech to keep track of everything. Just don’t make it part of the actual personalized exchange!)

Consider writing handwritten thank-you notes to customers after they’ve called in for support or emailed your team, for instance. Or send an extra personalized gift to buyers who make a specific number of purchases. These interactions aren’t technical but can differentiate your customer experience from your competitors’ experiences.

A groundbreaking Deloitte snapshot taken right before the pandemic showed that people were hungry for connection. By folding nondigital experiences into your personalization with customers, you’re showing them that you see them first as valued humans. That’s compelling and appealing, making them more apt to give you their loyalty in return.

Putting a personal spin on all your consumer interactions takes a little time. It’s worth your energy, though. You’ll wind up with stronger brand-buyer connections, helping you edge ahead of your competitors even more.

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Planning for 2023: What Social Media Marketers Need to Win in 2023



Planning for 2023: What Social Media Marketers Need to Win in 2023

January is, for many, a month of reflection, goal-setting, strategizing and planning for the year ahead. 

In line with this, we’ve kicked off the new year with a series of articles covering the latest stats, tips and strategies to help social media marketers build an effective game plan for 2023.

Below, you’ll find links to our 2023 social media planning series, which includes:

  • Content strategy guidelines to help you define your brand’s content mission and set SMART goals
  • Organic posting tips for Facebook, Instagram, TikTok, Twitter, LinkedIn, Snapchat and Pinterest 
  • Explainers on how to research key topics of interest in your niche, understand the competitive landscape, and help you find your audience and connect with them where they’re active
  • A holiday calendar and notes on the best days and times to post to each of the major platforms


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