Animation: The Rise and Fall of Popular Web Browsers Since 1994
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Animation: The Rise and Fall of Popular Web Browsers Since 1994

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Animation: The Rise and Fall of Popular Web Browsers Since 1994

In its early stages, the internet was a highly technical interface that most people had difficulty navigating. But that all changed when the Mosaic web browser entered the scene in 1993.

Mosaic was one of the first “user-friendly” internet portals—although by today’s standards, the browser was actually quite difficult to access. Comparatively, modern browsers in high use today have changed exponentially.

This animated graphic by James Eagle chronicles the evolution of the web browser market, showing the rise and fall of various internet portals from January 1994 to March 2022.

The 1990s: From Mosaic to Netscape

In the early 90s, Mosaic was by far the most dominant web browser. At the time, about 97% of all internet searches were done through this popular web portal.

Web browser% Share (January 1994)
Mosaic97.0%
Other3.0%

Mosaic was the first web browser to display images directly on a page in line with text. Earlier browsers loaded pictures as separate files, which meant users have to click, download, and open a new file in order to view them.

The pioneering portal was created by a team of university undergrads at the University of Illinois, led by 21-year-old Marc Andreessen. When Andreessen graduated, he went on to be the co-founder of Mosaic Communications Corporation, which evolved into Netscape Communications Corporation, the company that created Netscape Navigator.

Netscape was essentially a new and improved version of Mosaic, but since the University of Illinois owned the rights to Mosaic, Andreessen’s new company couldn’t actually use any of the original code.

Netscape became a nearly instant success, and as a result, Mosaic’s market share began to fall. By the late 90s, Netscape had captured 89% of the web browser market.

Web browser% Share (April 1996)
Netscape88.9%
Mosaic7.2%
Internet Explorer3.9%

Netscape dominated the market for a few more years. However, in the new millennium, a new tech giant started to take over—Internet Explorer.

The 2000s: Internet Explorer Enters the Chat, Followed by Firefox

In 1995, Microsoft launched Internet Explorer as part of an add-on package for its operating system, Microsoft Windows 95.

Given the popularity of the Windows franchise at the time, Internet Explorer was quickly adopted. By the early 2000s, it had captured over 90% of the market, reflecting Microsoft’s hold on the personal computing market.

Web browser% Share (January 2000)
Internet Explorer76.6%
Netscape18.4%
Opera0.7%
Other4.3%

Netscape was mostly phased out of the market by then, which meant Internet Explorer didn’t have much competition until Mozilla entered the arena.

Founded by members of Netscape, Mozilla began in 1998 as a project for fostering innovation in the web browser market. They shared Netscape’s source code with the public, and over time built a community of programmers around the world that helped make the product even better.

By 2004, Mozilla launched Firefox, and by 2006, the free, open-source browser had captured nearly 30% of the market. Firefox and Internet Explorer battled it out for a few more years, but by the mid-2010s, both browsers started to get leapfrogged by Google Chrome.

Present Day: Google Chrome is King of the Web Browsers

When Google’s co-founders Larry Page and Sergey Brin pitched the idea of starting a Google web browser to CEO Larry Schmidt in 2003, he was worried that they couldn’t keep up with the fierce competition. Eventually, the co-founders convinced Schmidt, and in 2008, Google Chrome was released to the public.

One of Chrome’s distinguishing features was (and still is) the fact that each tab operated separately. This meant that if one tab froze, it wouldn’t stall or crash the others, at the cost of higher memory and CPU usage.

By 2013, Chrome had swallowed up half the market. And with Android emerging as the most popular mobile OS on the global market, there were even more Chrome installations (and of course, searches on Google) as a result.

Notes on Data and Methodology

It’s important to note that the dataset in this animation uses visitor log files from web development site and resource W3Schools from 1999 onwards. Despite getting more than 60 million monthly visits, its userbase is likely slanted towards PC over mobile users.

Further, though Google’s Android platform has a sizable lead over Apple’s iOS in the global mobile sector, this likely slant also impacts the representation of iOS and therefore Safari browsers in the animation and dataset.

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This article was published as a part of Visual Capitalist's Creator Program, which features data-driven visuals from some of our favorite Creators around the world.

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The Evolution of Media: Visualizing a Data-Driven Future

Media and information delivery is transforming at an increasing pace. Here’s why the future will be more data-driven, transparent, and verifiable.

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In today’s highly-connected and instantaneous world, we have access to a massive amount of information at our fingertips.

Historically, however, this hasn’t always been the case.

Time travel back just 20 years ago to 2002, and you’d notice the vast majority of people were still waiting on the daily paper or the evening news to help fill the information void.

In fact, for most of 2002, Google was trailing in search engine market share behind Yahoo! and MSN. Meanwhile, early social media incarnations (MySpace, Friendster, etc.) were just starting to come online, and all of Facebook, YouTube, Twitter, and the iPhone did not yet exist.

The Waves of Media So Far

Every so often, the dominant form of communication is upended by new technological developments and changing societal preferences.

These transitions seem to be happening faster over time, aligning with the accelerated progress of technology.

  • Proto-Media (50,000+ years)
    Humans could only spread their message through human activity. Speech, oral tradition, and manually written text were most common mediums to pass on a message.
  • Analog and Early Digital Media (1430-2004)
    The invention of the printing press, and later the radio, television, and computer unlock powerful forms of one-way and cheap communication to the masses.
  • Connected Media (2004-current)
    The birth of Web 2.0 and social media enables participation and content creation for everyone. One tweet, blog post, or TikTok video by anyone can go viral, reaching the whole world.

Each new wave of media comes with its own pros and cons.

For example, Connected Media was a huge step forward in that it enabled everyone to be a part of the conversation. On the other hand, algorithms and the sheer amount of content to sift through has created a lot of downsides as well. To name just a few problems with media today: filter bubbles, sensationalism, clickbait, and so on.

Before we dive into what we think is the next wave of media, let’s first break down the common attributes and problems with prior waves.

Wave Zero: Proto-Media

Before the first wave of media, amplifying a message took devotion and a lifetime.

Add in the fact that even by the year 1500, only 4% of global citizens lived in cities, and you can see how hard it would be to communicate effectively with the masses during this era.

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

Wave 1: Analog and Early Digital Media

In this first wave, new technological advancements enabled widescale communication for the first time in history.

Newspapers, books, magazines, radios, televisions, movies, and early websites all fit within this framework, enabling the owners of these assets to broadcast their message at scale.

With large amounts of infrastructure required to print books or broadcast television news programs, it took capital or connections to gain access. For this reason, large corporations and governments were usually the gatekeepers, and ordinary citizens had limited influence.

AttributeDescription
📡 Information FlowOne-way
💰 Barriers to EntryVery high
📰 DistributionControlled by mass media companies and government
🏆 IncentiveTo cast a wide net, and to not alienate viewers or advertisers

Importantly, these mediums only allowed one-way communication—meaning that they could broadcast a message, but the general public was restricted in how they could respond (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 changed the game.

Starting in the mid-2000s, barriers to entry began to drop, and it eventually became free and easy for anyone to broadcast their opinion online. As the internet exploded with content, sorting through it became the number one problem to solve.

For better or worse, algorithms began to feed people what they loved, so they could consume even more. The ripple effect of this was that everyone competing for eyeballs suddenly found themselves optimizing content to try and “win” the algorithm game to get virality.

AttributeDescription
📡 Information FlowTwo-way
💰 Barriers to EntryVery low
📰 DistributionControlled by technology companies and algorithms
🏆 IncentiveTo cast a narrow net, to engage and mobilize a specific audience

Viral content is often engaging and interesting, but it comes with tradeoffs. Content can be made artificially engaging by sensationalizing, using clickbait, or playing loose with the facts. It can be ultra-targeted to resonate emotionally within one particular filter bubble. It can be designed to enrage a certain group, and mobilize them towards action—even if it is extreme.

Despite the many benefits of Connected Media, we are seeing more polarization than ever before in society. Groups of people can’t relate to each other or discuss issues, because they can’t even agree on basic facts.

Perhaps most frustrating of all? Many people don’t know they are deep within their own bubble in which they are only fed information they agree with. They are unaware that other legitimate points of view exist. Everything is black and white, and grey thinking is rarer and rarer.

Wave 3: Data Media

Between 2015 and 2025, the amount of data captured, created, and replicated globally will increase by 1,600%.

For the first time ever, a significant quantity of data is becoming “open source” and available to anyone. There have been massive advancements in how to store and verify data, and even the ownership of information can now be tracked on the blockchain. Both media and the population are becoming more data literate, and they are also becoming aware of the societal drawbacks stemming from Connected Media.

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

  • Transparency:
    Data literate users will begin to demand that data is transparent and originating from trustworthy, factual sources. Or if a source is not rock solid, users will demand that limitations of methodology or possible biases are openly revealed and discussed.
  • Verifiability and Trust:
    How do we know data shown is legitimate and bonafide? Platforms and media will increasingly want to prove to users that data has been verified, going all the way back to the original source.
  • Decentralization and Web3:
    Anyone can tap into large amounts of public data available today, which means that reporting, analysis, ideas, and insights can come from an increasingly growing set of actors. Web3 and decentralized ledgers will allow us to provide trust, attribution, accountability, and even ownership of content when necessary. This can remove the middleman, which is often large tech companies, and can allow users to monetize their content more directly.
  • Data Storytelling
    Growing data literacy, and the explosion of data storytelling is a key approach to making sense of vast amounts of data, by combining data visualization, narrative, and powerful insights.
  • Data Creator Economy:
    Democratized data and the rise of storytelling are intersecting to create a potential new ecosystem for data storytellers. This is increasingly what we are focused on at Visual Capitalist, and we encourage you to support our Kickstarter project on this (just 6 days left, as of publishing time)
  • Open-Ended Ecosystem:
    Just like open source has revolutionized the software industry, we will begin to see more and more data available broadly. Incentives may shift in some cases from keeping data proprietary, to getting it out in the open so that others can use, remix, and publish it, and attributing it back to the original source.
  • Data > Opinion:
    Data Media will have a bias towards facts over opinion. It’s less about punditry, bias, spin, and telling others what they should think, and more about allowing an increasingly data literate population to have access to the facts themselves, and to develop their own nuanced opinion on them.
  • Global Data Standards:
    As data continues to proliferate, it will be important to codify and unify it when possible. This will lead to global standards that will make communicating it even easier.

Early Pioneers of Data Media

The Data Media ecosystem is just beginning to emerge, but here are some early pioneers we like:

  • Our World in Data:
    Led by economist Max Roser, OWiD is doing an excellent job amalgamating global economic data in one place, and making it easy for others to remix and communicate those insights effectively.
  • USAFacts:
    Founded by Steve Ballmer of Microsoft fame to be a non-partisan source of U.S. government data.
  • FRED:
    This tool by the Federal Reserve Bank of St. Louis is just one example of many tools that have cropped up over the years to democratize data that were previously proprietary or hard to access. Other similar tools have been created by the IMF, World Bank, and so on.
  • FiveThirtyEight:
    FiveThirtyEight uses statistical analysis, data journalism, and predictions to cover politics, sports, and other topics in a unique way.
  • FlowingData:
    At FlowingData, data viz expert Nathan Yau explores a wide variety of data and visualization themes.
  • Data Journalists:
    There are incredible data journalists at publications like The Economist, The Washington Post, The New York Times, and Reuters that are tapping into 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.

Growth in data journalism and the emergence of these pioneers helps give you a sense of the beginnings of Data Media, but we believe they are only scratching the surface of what is possible.

What Data Media is Not

In a sense, it’s easier to define what Data Media isn’t.

Data Media is not partisan pundits arguing over each other on a newscast, and it’s not fake news, misinformation, or clickbait that is engineered to drive easy clicks. Data media is not an echo chamber that only reinforces existing biases. Because data is also less subjective, it’s less likely to be censored in the way we see today.

Data is not perfect, but it can help change the conversations we are having as a society to be more constructive and inclusive. We hope you agree!

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33 Problems With Media in One Chart

In this infographic, we catalog 33 problems with the social and mass media ecosystem.

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problems with media

33 Problems With Media in One Chart

One of the hallmarks of democratic society is a healthy, free-flowing media ecosystem.

In times past, that media ecosystem would include various mass media outlets, from newspapers to cable TV networks. Today, the internet and social media platforms have greatly expanded the scope and reach of communication within society.

Of course, journalism plays a key role within that ecosystem. High quality journalism and the unprecedented transparency of social media keeps power structures in check—and sometimes, these forces can drive genuine societal change. Reporters bring us news from the front lines of conflict, and uncover hard truths through investigative journalism.

That said, these positive impacts are sometimes overshadowed by harmful practices and negative externalities occurring in the media ecosystem.

The graphic above is an attempt to catalog problems within the media ecosystem as a basis for discussion. Many of the problems are easy to understand once they’re identified. However, in some cases, there is an interplay between these issues that is worth digging into. Below are a few of those instances.

Editor’s note: For a full list of sources, please go to the end of this article. If we missed a problem, let us know!

Explicit Bias vs. Implicit Bias

Broadly speaking, bias in media breaks down into two types: explicit and implicit.

Publishers with explicit biases will overtly dictate the types of stories that are covered in their publications and control the framing of those stories. They usually have a political or ideological leaning, and these outlets will use narrative fallacies or false balance in an effort to push their own agenda.

Unintentional filtering or skewing of information is referred to as implicit bias, and this can manifest in a few different ways. For example, a publication may turn a blind eye to a topic or issue because it would paint an advertiser in a bad light. These are called no fly zones, and given the financial struggles of the news industry, these no fly zones are becoming increasingly treacherous territory.

Misinformation vs. Disinformation

Both of these terms imply that information being shared is not factually sound. The key difference is that misinformation is unintentional, and disinformation is deliberately created to deceive people.

Fake news stories, and concepts like deepfakes, fall into the latter category. We broke down the entire spectrum of fake news and how to spot it, in a previous infographic.

Simplify, Simplify

Mass media and social feeds are the ultimate Darwinistic scenario for ideas.

Through social media, stories are shared widely by many participants, and the most compelling framing usually wins out. More often than not, it’s the pithy, provocative posts that spread the furthest. This process strips context away from an idea, potentially warping its meaning.

Video clips shared on social platforms are a prime example of context stripping in action. An (often shocking) event occurs, and it generates a massive amount of discussion despite the complete lack of context.

This unintentionally encourages viewers to stereotype the persons in the video and bring our own preconceived ideas to the table to help fill in the gaps.

Members of the media are also looking for punchy story angles to capture attention and prove the point they’re making in an article. This can lead to cherrypicking facts and ideas. Cherrypicking is especially problematic because the facts are often correct, so they make sense at face value, however, they lack important context.

Simplified models of the world make for compelling narratives, like good-vs-evil, but situations are often far more complex than what meets the eye.

The News Media Squeeze

It’s no secret that journalism is facing lean times. Newsrooms are operating with much smaller teams and budgets, and one result is ‘churnalism’. This term refers to the practice of publishing articles directly from wire services and public relations releases.

Churnalism not only replaces more rigorous forms of reporting—but also acts as an avenue for advertising and propaganda that is harder to distinguish from the news.

The increased sense of urgency to drive revenue is causing other problems as well. High-quality content is increasingly being hidden behind paywalls.

The end result is a two-tiered system, with subscribers receiving thoughtful, high-quality news, and everyone else accessing shallow or sensationalized content. That everyone else isn’t just people with lower incomes, it also largely includes younger people. The average age of today’s paid news subscriber is 50 years old, raising questions about the future of the subscription business model.

For outlets that rely on advertising, desperate times have called for desperate measures. User experience has taken a backseat to ad impressions, with ad clutter (e.g. auto-play videos, pop-ups, and prompts) interrupting content at every turn. Meanwhile, in the background, third-party trackers are still watching your every digital move, despite all the privacy opt-in prompts.

How Can We Fix the Problems with Media?

With great influence comes great responsibility. There is no easy fix to the issues that plague news and social media. But the first step is identifying these issues, and talking about them.

The more media literate we collectively become, the better equipped we will be to reform these broken systems, and push for accuracy and transparency in the communication channels that bind society together.

Sources and further reading:

Veils of Distortion: How the News Media Warps our Minds by John Zada
Hate Inc. by Matt Taibbi
Manufacturing Consent by Edward S. Herman and Noam Chomsky
The Truth Matters: A Citizen’s Guide to Separating Facts from Lies and Stopping Fake News in its Tracks by Bruce Bartlett
Active Measures: The Secret History of Disinformation and Political Warfare by Thomas Rid
The Twittering Machine by Richard Seymour
After the Fact by Nathan Bomey
Ten Arguments for Deleting Your Social Media Accounts Right Now by Jaron Lanier
Zucked by Roger McNamee
Antisocial: Online Extremists, Techno-Utopians, and the Highjacking of the American Conversation by Andrew Marantz
Social media is broken by Sara Brown
The U.S. Media’s Problems Are Much Bigger than Fake News and Filter Bubbles by Bharat N. Anand
What’s Wrong With the News? by FAIR
Is the Media Doomed? by Politico
The Implied Truth Effect by Gordon Pennycook, Adam Bear, Evan T. Collins, David G. Rand

 

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