This week’s issue – our last in 2019 – is guest-written by my colleague and collaborator Julia Dixon.

Check out Julia’s take on two types of end-of-year data share-outs we’re all seeing lately – and let us know what you think. Happy Holidays — Chris
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Regifted Data

It's been the decade of data. According to Statista, the world generated two zettabytes of data in 2010 (if that means nothing to you, as it did for me, a zettabyte is a byte, the unit for digital information, to the power of 1000). At the end of 2019, we will have produced about 41 zettabytes of data globally. By 2025, that number is expected to grow to 175 zettabytes collected per year. 

We spend every day willingly and unwillingly providing this mammoth amount of data to platforms and corporations. But in the last few years, a December tradition has emerged. A select handful of our data is packaged and presented back to us in the form of end-of-year summaries. This flip of the script has materialized in two familiar categories. 

The first is individualized data deliveries. Facebook's
Year in Review, Snapchat's Year End Story, Apple Music's Replay and Spotify Wrapped provide sharable highlights of all that we posted, liked and listened to in 2019. This year, Spotify Wrapped took the spotlight due to its attention-grabbing design and inherent compatibility with Instagram stories. Within three days of the launch, the Spotify app was downloaded 2.3 million times globally. Spotify Wrapped also became a meme of its own, extending the reach of the widely-shared format even further (see a few of my favorites below).

The second category of regifted data comes in the form of collective summaries. These data recaps are often reimagined to tell an inspiring narrative as famed by Google's Year in Search, Reddit's Year in Review, the new Tik Tok 100 and YouTube Rewind. The latter also made headlines this year for being very poorly received. Viewers pointed out the lack of creative data use and discomfort celebrating the platform among recent controversies including overdue harassment policies and dangerous recommendation algorithms.

Looking at the reception of Spotify vs. YouTube's data releases, authenticity seems to be the differentiator when it comes to sensitive areas like data ethics (and most other things). Even a sliver of transparency can go viral and be good for the bottom line if it feels insightful, personal and aware of the moment. To quote one Twitter
user, "It’s like i know ur selling my data but it’s nice when you let me see it."

This season of our data being shared back with us serves as a good reminder — the best use of data taps into the human desire to share and engage with things we care about, individually and collectively.

Julia Dixon

PS — Speaking of year-end summaries, check out our most popular issue of 2019 along with the most read articles in the categories of Media Forensics, Content Experience, Platform Dominance, Artificial Intelligence and Synthetic Content. From Fortnite to Lil Miquela to trying to understand Tik Tok (OK Boomer), it's been a weird but great year. Intrigued to discover what will drive the next decade.
Thanks for being a subscriber. And of course, if you find this newsletter valuable, we would be grateful if you encouraged others to bring Media Genius into 2020 by directing them here.
What We're Reading
Content Experience
The Decade Tech Lost Its Way
By The New York Times Staff, The New York Times

When the decade began, tech meant promise — cars that could drive themselves, social networks that could take down dictators. It connected us in ways we could barely imagine. But somewhere along the way, the flaws of technology became abundantly clear. What happened? The New York Times provides an experiential look at the decade.

Media Forensics
Newsrooms Begin Tinkering With 5G
By Sara Fischer

5G, for now, is like the new AR or VR. It's not widely accessible, but big newsrooms want to start experimenting with it so that they will be ahead of the curve when it eventually reaches mass consumer adoption.

Media Forensics
Merriam-Webster's Word of the Year Is ‘They’
By Graeme McMillan, Wired

Merriam-Webster says that "they" is its 2019 Word of the Year, noting that the tiny word has undergone a radical transformation in usage in recent years — and has found itself at the heart of wide-ranging cultural conversations in the process.

Synthetic Content
I Created my Own Deepfake — It Took Two Weeks and Cost $552
By Timothy B. Lee, Ars Technica

After experimenting with deepfake software for a couple of weeks, writer Timothy B. Lee finds it remarkable that a neophyte can create a fairly convincing video so quickly and for so little money. And there's every reason to think deepfake technology will continue to get better, faster, and cheaper in the coming years.

Content Experience
The 100 Memes That Defined The 2010s
By Katie Notopoulos, Ryan Broderick, Julia Reinstein, Buzzfeed News

From planking to VSCO girls — this decade, memes became something not just for a handful of internet nerds who lurked on message boards; memes are now for everyone. The online culture of this decade hasn’t just changed the words we use, it’s changed how we express ourselves.

Platform Dominance
Gen-Zers on Tinder Want Someone to March With, Not Just Match With
By Brianna Holt, Quartz

According to Tinder’s 2019 Year In Swipe report, users between the ages of 18 and 24, who now make up the majority of the dating app’s users, were 66% more likely than millennials to mention issues like climate change, gun control or social justice in their bios.

Content Experience
This Thing You Loved as a Kid? It’s for Adults Now
By Jeremy Gordon, The Outline

Our contemporary commercial culture fetishizes nostalgia and infantilization, not just revisiting and reappraising the past, but resuscitating and reimagining content originally made decades ago (for children) into content made now (for kids AND adults).

Emerging Technology
Hulu Launches its Viewer-Friendly ‘Binge Watch Ads’
By Sarah Perez, TechCrunch

Hulu is launching a new kind of ad experience that allows brands to specifically target binge-watchers — that is, viewers who are watching multiple episodes of a favorite program over a long stretch of time. These “binge watch ads” utilize machine learning techniques to predict when a viewer has begun to binge watch a show, then serves up contextually relevant ads that acknowledge a binge is underway.

Deep Take
Predictions for Journalism 2020
By Nieman Lab
Each year, Nieman Lab asks some of the smartest people in journalism and digital media what they think is coming in the next 12 months. Here’s what they had to say.
Copyright © 2019 Weber Shandwick

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