The rise and fall of popular web browsers since 1994

In today’s highly connected and fast-paced world, we have access to a vast amount of information.

Historically, however, this has not always been the case.

Travel back in time just 20 years ago to 2002 and you would find that the vast majority of people were still waiting for the daily newspaper or the evening news to help fill in the information gap.

In fact, for most of 2002, Google lagged behind Yahoo! and MSN. Meanwhile, early incarnations of social media (MySpace, Friendster, etc.) were just starting to come online, and Facebook, YouTube, Twitter, and the iPhone didn’t exist yet.

The media waves so far

From time to time, new technological developments and changing societal preferences turn the dominant form of communication on its head.

These transitions appear to be accelerating over time, adjusting to the accelerated advancement of technology.

  • proto-media (50,000+ years)
    Humans could spread their message only through human activity. Speech, oral tradition and handwritten text were the most common mediums to convey a message.
  • Analogue and early digital media (1430-2004)
    The invention of the printing press, and later radio, television, and the computer, brought powerful forms of one-way and cheap communication to the masses.
  • Connected Media (since 2004)
    The birth of Web 2.0 and social media enables participation and content creation for everyone. A tweet, blog post, or TikTok video from anyone can go viral and reach the whole world.

Each new media wave has its own pros and cons.

For example, Connected Media was a big step forward as it allowed everyone to join the conversation. On the other hand, algorithms and the sheer volume of content that needs to be searched have also created many disadvantages. To name just a few problems with media today: filter bubbles, sensationalism, clickbait and so on.

Before we delve into what we believe to be the next media wave, let’s first break down common characteristics and issues with previous waves.

Wave Zero: Proto Media

Before the first wave of media, it took dedication and a lifetime to get a message out.

Add to this the fact that even in 1500 only 4% of the world’s citizens lived in cities and you can see how difficult it was to communicate effectively with the masses during that time.

Or, to paint a more vivid picture of what proto-media was like, information could only travel at the speed of a horse.

Wave 1: Analogue and early digital media

In this first wave, new technological advances enabled widespread communication for the first time in history.

Newspapers, books, magazines, radio, television, film, and early websites all fit within this framework, allowing the owners of these assets to spread their message widely.

Since printing books or broadcasting television news programs required large amounts of infrastructure, capital or connections were required to gain access. Because of this, large corporations and governments were usually the gatekeepers, and ordinary citizens had limited influence.

attribute description
📡 Information flow disposable
💰 Barriers to entry Very high
📰 Distribution Controlled by mass media companies and the government
🏆 Incentive In order to cast a wide net and not alienate viewers or advertisers

Importantly, these mediums only allowed one-way communication – meaning they could send a message, but the general public was limited in their response (i.e. a letter to the editor or a phone call to a radio station).

Wave 2: Connected media

Innovations like Web 2.0 and social media have changed the game.

Beginning in the mid-2000s, barriers to entry began to fall and eventually it became free and easy for anyone to voice their opinion online. As the internet exploded with content, sorting became the main problem to solve.

For better or for worse, algorithms started feeding people what they loved so they could consume even more. As a result, everyone competing for eyeballs was suddenly tweaking content to try and “win” the algorithm game in order to gain virality.

attribute description
📡 Information flow Two ways
💰 Barriers to entry Very low
📰 Distribution Controlled by technology companies and algorithms
🏆 Incentive Casting a tight net, addressing and mobilizing a specific audience

Viral content is often compelling and interesting, but it comes with trade-offs. Content can be made artificially compelling by sensationalizing, using clickbait, or playing lightly with facts. It can be very purposeful to resonate emotionally within a particular filter bubble. It can be designed to infuriate a particular group and mobilize them into action – even if it is extreme.

Despite the many benefits of connected media, we are seeing more polarization than ever in society. Groups of people cannot relate to each other or discuss problems because they cannot agree on even basic facts.

Perhaps the most frustrating? Many people don’t realize that they are deep within their own bubble, being fed only information they agree with. They are unaware that there are other legitimate viewpoints. Everything is black and white, and gray thinking is becoming increasingly rare.

Wave 3: Disk

Between 2015 and 2025, the amount of data collected, created and replicated around the world will increase by 1,600%.

For the first time ever, a significant amount of data is becoming “open source” and available to everyone. There have been massive advances in data storage and verification, and even ownership of information can now be tracked on the blockchain. Both the media and the population are becoming more data literate, and they are also becoming aware of the societal disadvantages that result from connected media.

As this new wave emerges, it’s worth examining some of its attributes and unifying concepts in more detail:

  • Transparency:
    Data literate users will start demanding that data is transparent and comes from trusted, factual sources. Or, if a source is not rock solid, users will demand that methodology limitations or possible biases be openly exposed and discussed.
  • Verifiability and trust:
    How do we know that the data shown is legitimate and reputable? Platforms and media will increasingly want to prove to users that data has been verified back to the original source.
  • Decentralization and Web3:
    Anyone can access the vast amounts of public data available today, which means reports, analysis, ideas and insights can come from an ever-expanding group of stakeholders. Web3 and decentralized ledgers allow us to provide trust, attribution, accountability, and even content ownership when needed. This can eliminate the middleman, which is often big tech companies, and allow users to monetize their content more directly.
  • Storytelling of data
    Rising data literacy and the explosion of data storytelling is a key approach to making sense of big data by combining data visualization, storytelling, and meaningful insights.
  • Data Creator Economy:
    Democratized data and the rise of storytelling are intersecting to create a potential new data teller ecosystem. This is what we are increasingly focusing on at Visual Capitalist and we encourage you to support our Kickstarter project in this regard (only 6 days leftat the time of publication)
  • Open ecosystem:
    Just as open source has revolutionized the software industry, we will see more and more data widely available. Incentives can, in some cases, shift from retaining ownership of data to disclosing it for others to use, remix and publish, and attribution to the original source.
  • Data > Opinion:
    Data media will bias facts over opinions. It’s less about opinion, bias, silly, and telling others what to think, and more about enabling an increasingly data-literate population to access the facts themselves and form their own nuanced opinions about them.
  • Global data standards:
    As data continues to proliferate, it will be important to codify and standardize it where possible. This will lead to global standards that will make communication even easier.

Early pioneers of data carriers

The data media ecosystem is just beginning, but here are some early pioneers we like:

  • Our world in data:
    Led by economist Max Roser, OWiD does an excellent job of bringing global economic data together in one place and making it easy for others to remix these insights and communicate effectively.
  • USAFacts:
    Founded by Microsoft’s Steve Ballmer to be an impartial source of US government data.
  • fred:
    This Federal Reserve Bank of St. Louis tool is just one example of many tools that have emerged over the years to democratize data that was previously proprietary or difficult to access. Other similar tools have been developed by the IMF, World Bank, etc.
  • Thirty-five:
    FiveThirtyEight uses statistical analysis, data journalism and forecasting to uniquely cover politics, sports and other topics.
  • Flowing data:
    At FlowingData, data visualization expert Nathan Yau explores a variety of data and visualization topics.
  • Data Journalists:
    There are incredible data journalists at publications like The Economist, The Washington Post, The New York Times and Reuters who are unlocking the early beginnings of what is possible. Many of these publications also made their COVID-19 work freely available during the pandemic, which is certainly commendable.

The growth of data journalism and the emergence of these pioneers helps you get a feel for the beginnings of data media, but we believe they only scratch the surface of what’s possible.

What data carriers are not

In a way, it’s easier to define what disks are not.

Data media aren’t partisan experts arguing about each other on a news show, and it’s not fake news, misinformation, or clickbait designed to get easy clicks. Data carriers are not an echo chamber that only reinforces existing prejudices. Because data is also less subjective, it is less likely to be censored like we see it today.

Data isn’t perfect, but it can help make the conversations we have as a society more constructive and inclusive. We hope you agree!

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