Tag Archives: Journalism & News

Who works in America’s newsrooms?

Over the course of two decades, the American Society of News Editors (ASNE) has compiled a national view of gender and race breakdowns of U.S. journalists. The newly released 2017 data helps us understand who is working in America’s newsrooms, and provides a unique insight into how the industry reflects—or struggles to reflect—the population it serves.

The Google News Lab supports inclusive reporting, and for the first time, has partnered with ASNE on their annual Newsroom Employment Diversity Survey. Working with design studio Polygraph, we helped ASNE create a data visualization to show how hundreds of newsrooms across the U.S. have changed since 2001.

Here's a glimpse at how it works:

  • xx
    Here’s an overview of the tool, with data from hundreds of newsrooms across the U.S.
  • pasted image 0 (2).png
    By comparing newsroom diversity counts to census data, this visual shows how each newsroom compares to its local area in terms of race and gender—or for national publications, the country as a whole.
  • pasted image 0 (3).png
    It also illustrates the relationship between diversity in a newsrooms’ leadership and diversity in its staff.
  • pasted image 0 (4).png
    And shows how newsrooms have changed in the last 16 years.

Check out our graphics, or download the data from our GitHub page to explore for yourself. We want to see what you can do with the data—by visualizing it yourself or adding further context to the numbers—so contact us at [email protected].

We hope this year’s reimagined data will advance the conversation on newsroom diversity and tell a story that’s broader than just the numbers.

Who works in America’s newsrooms?

Over the course of two decades, the American Society of News Editors (ASNE) has compiled a national view of gender and race breakdowns of U.S. journalists. The newly released 2017 data helps us understand who is working in America’s newsrooms, and provides a unique insight into how the industry reflects—or struggles to reflect—the population it serves.

The Google News Lab supports inclusive reporting, and for the first time, has partnered with ASNE on their annual Newsroom Employment Diversity Survey. Working with design studio Polygraph, we helped ASNE create a data visualization to show how hundreds of newsrooms across the U.S. have changed since 2001.

Here's a glimpse at how it works:

  • xx
    Here’s an overview of the tool, with data from hundreds of newsrooms across the U.S.
  • pasted image 0 (2).png
    By comparing newsroom diversity counts to census data, this visual shows how each newsroom compares to its local area in terms of race and gender—or for national publications, the country as a whole.
  • pasted image 0 (3).png
    It also illustrates the relationship between diversity in a newsrooms’ leadership and diversity in its staff.
  • pasted image 0 (4).png
    And shows how newsrooms have changed in the last 16 years.

Check out our graphics, or download the data from our GitHub page to explore for yourself. We want to see what you can do with the data—by visualizing it yourself or adding further context to the numbers—so contact us at [email protected].

We hope this year’s reimagined data will advance the conversation on newsroom diversity and tell a story that’s broader than just the numbers.

Driving the future of digital subscriptions

Journalism provides accurate and timely information when it matters most, shaping our understanding of important issues and pushing us to learn more in search of the truth. People come to Google looking for high-quality content, and our job is to help them find it. However, sometimes that content is behind a paywall.

While research has shown that people are becoming more accustomed to paying for news, the sometimes painful process of signing up for a subscription can be a turn off. That’s not great for users or for news publishers who see subscriptions as an increasingly important source of revenue.

To address these problems we’ve been talking to news publishers about how to support their subscription businesses with a focus on the following:

  • First, Flexible Sampling will replace First Click Free. Publishers are in the best position to determine what level of free sampling works best for them. So as of this week, we are ending the First Click Free policy, which required publishers to provide a minimum of three free articles per day via Google Search and Google News before people were shown a paywall.
  • Longer term, we are building a suite of products and services to help news publishers reach new audiences, drive subscriptions and grow revenue.
  • We are also looking at how we can simplify the purchase process and make it easy for Google users to get the full value of their subscriptions across Google’s platforms.

Our goal is to make subscriptions work seamlessly everywhere, for everyone.

First Click Free

We will end our First Click Free policy in favor of a Flexible Sampling model where publishers will decide how many, if any, free articles they want to provide to potential subscribers based on their own business strategies. This move is informed by our own research, publisher feedback, and months-long experiments with the New York Times and the Financial Times, both of which operate successful subscription services.  

"Google's decision to let publishers determine how much content readers can sample from search is a positive development,” said Kinsey Wilson, an adviser to New York Times CEO Mark Thompson. "We're encouraged as well by Google's willingness to consider other ways of supporting subscription business models and we are looking forward to continuing to work with them to craft smart solutions."

Publishers generally recognize that giving people access to some free content is the way to persuade people to buy their product. The typical approach to sampling is a model called metering, which lets people see a pre-determined number of free stories before a paywall kicks in. We recommend the following approach:

  • Monthly, rather than daily, metering allows publishers more flexibility to experiment with the number of free stories to offer people and to target those more likely to subscribe.
  • For most publishers, 10 articles per month is a good starting point.
  • Please see our Webmaster blog and our guide on Flexible Sampling for more detail on these approaches.

“Try before you buy” underlines what many publishers already know—they need to provide some form of free sampling to be successful on the internet. If it’s too little, then fewer users will click on links to that content or share it, which could have an effect on brand discovery and subsequently may affect traffic over time.

Subscription support

Subscribing to great content should not be as hard as it is today. Registering on a site, creating and remembering multiple passwords, and entering credit card information—these are all hassles we hope to solve.

As a first step we’re taking advantage of our existing identity and payment technologies to help people subscribe on a publication’s website with a single click, and then seamlessly access that content anywhere— whether it’s on that publisher site or mobile app, or on Google Newsstand, Google Search or Google News.

And since news products and subscription models vary widely, we’re collaborating with publishers around the world on how to build a subscription mechanism that can meet the needs of a diverse array of approaches—to the benefit of the news industry and consumers alike.  

We’re also exploring how Google’s machine learning capabilities can help publishers recognize potential subscribers and present the right offer to the right audience at the right time.

“It's extremely clear that advertising alone can no longer pay for the production and distribution of high quality journalism—and at the same time the societal need for sustainable independent journalism has never been greater.  Reader-based revenue, aka paid-content, or subscription services, are therefore not just a nice-to-have, but an essential component of a publisher's revenue composition,” said Jon Slade, FT Chief Commercial Officer.

“The Financial Times is welcoming of Google's input and actions to help this critical sector of the media industry, and we've worked very closely with Google to aid understanding of the needs that publishers have and how Google can help. That mutual understanding includes the ability to set controls over the amount of free content given to readers, a level playing field for content discovery, optimised promotion and payment processes. It is important that we now build and accelerate on the discussions and actions to date.”  

We are just getting started and want to get as much input from publishers—large, small, national, local, international—to make sure we build solutions together that work for everyone.  

Driving the future of digital subscriptions

Journalism provides accurate and timely information when it matters most, shaping our understanding of important issues and pushing us to learn more in search of the truth. People come to Google looking for high-quality content, and our job is to help them find it. However, sometimes that content is behind a paywall.

While research has shown that people are becoming more accustomed to paying for news, the sometimes painful process of signing up for a subscription can be a turn off. That’s not great for users or for news publishers who see subscriptions as an increasingly important source of revenue.

To address these problems we’ve been talking to news publishers about how to support their subscription businesses with a focus on the following:

  • First, Flexible Sampling will replace First Click Free. Publishers are in the best position to determine what level of free sampling works best for them. So as of this week, we are ending the First Click Free policy, which required publishers to provide a minimum of three free articles per day via Google Search and Google News before people were shown a paywall.
  • Longer term, we are building a suite of products and services to help news publishers reach new audiences, drive subscriptions and grow revenue.
  • We are also looking at how we can simplify the purchase process and make it easy for Google users to get the full value of their subscriptions across Google’s platforms.

Our goal is to make subscriptions work seamlessly everywhere, for everyone.

First Click Free

We will end our First Click Free policy in favor of a Flexible Sampling model where publishers will decide how many, if any, free articles they want to provide to potential subscribers based on their own business strategies. This move is informed by our own research, publisher feedback, and months-long experiments with the New York Times and the Financial Times, both of which operate successful subscription services.  

"Google's decision to let publishers determine how much content readers can sample from search is a positive development,” said Kinsey Wilson, an adviser to New York Times CEO Mark Thompson. "We're encouraged as well by Google's willingness to consider other ways of supporting subscription business models and we are looking forward to continuing to work with them to craft smart solutions."

Publishers generally recognize that giving people access to some free content is the way to persuade people to buy their product. The typical approach to sampling is a model called metering, which lets people see a pre-determined number of free stories before a paywall kicks in. We recommend the following approach:

  • Monthly, rather than daily, metering allows publishers more flexibility to experiment with the number of free stories to offer people and to target those more likely to subscribe.
  • For most publishers, 10 articles per month is a good starting point.
  • Please see our Webmaster blog and our guide on Flexible Sampling for more detail on these approaches.

“Try before you buy” underlines what many publishers already know—they need to provide some form of free sampling to be successful on the internet. If it’s too little, then fewer users will click on links to that content or share it, which could have an effect on brand discovery and subsequently may affect traffic over time.

Subscription support

Subscribing to great content should not be as hard as it is today. Registering on a site, creating and remembering multiple passwords, and entering credit card information—these are all hassles we hope to solve.

As a first step we’re taking advantage of our existing identity and payment technologies to help people subscribe on a publication’s website with a single click, and then seamlessly access that content anywhere— whether it’s on that publisher site or mobile app, or on Google Newsstand, Google Search or Google News.

And since news products and subscription models vary widely, we’re collaborating with publishers around the world on how to build a subscription mechanism that can meet the needs of a diverse array of approaches—to the benefit of the news industry and consumers alike.  

We’re also exploring how Google’s machine learning capabilities can help publishers recognize potential subscribers and present the right offer to the right audience at the right time.

“It's extremely clear that advertising alone can no longer pay for the production and distribution of high quality journalism—and at the same time the societal need for sustainable independent journalism has never been greater.  Reader-based revenue, aka paid-content, or subscription services, are therefore not just a nice-to-have, but an essential component of a publisher's revenue composition,” said Jon Slade, FT Chief Commercial Officer.

“The Financial Times is welcoming of Google's input and actions to help this critical sector of the media industry, and we've worked very closely with Google to aid understanding of the needs that publishers have and how Google can help. That mutual understanding includes the ability to set controls over the amount of free content given to readers, a level playing field for content discovery, optimised promotion and payment processes. It is important that we now build and accelerate on the discussions and actions to date.”  

We are just getting started and want to get as much input from publishers—large, small, national, local, international—to make sure we build solutions together that work for everyone.  

Source: Search


Driving the future of digital subscriptions

Journalism provides accurate and timely information when it matters most, shaping our understanding of important issues and pushing us to learn more in search of the truth. People come to Google looking for high-quality content, and our job is to help them find it. However, sometimes that content is behind a paywall.

While research has shown that people are becoming more accustomed to paying for news, the sometimes painful process of signing up for a subscription can be a turn off. That’s not great for users or for news publishers who see subscriptions as an increasingly important source of revenue.

To address these problems we’ve been talking to news publishers about how to support their subscription businesses with a focus on the following:

  • First, Flexible Sampling will replace First Click Free. Publishers are in the best position to determine what level of free sampling works best for them. So as of this week, we are ending the First Click Free policy, which required publishers to provide a minimum of three free articles per day via Google Search and Google News before people were shown a paywall.
  • Longer term, we are building a suite of products and services to help news publishers reach new audiences, drive subscriptions and grow revenue.
  • We are also looking at how we can simplify the purchase process and make it easy for Google users to get the full value of their subscriptions across Google’s platforms.

Our goal is to make subscriptions work seamlessly everywhere, for everyone.

First Click Free

We will end our First Click Free policy in favor of a Flexible Sampling model where publishers will decide how many, if any, free articles they want to provide to potential subscribers based on their own business strategies. This move is informed by our own research, publisher feedback, and months-long experiments with the New York Times and the Financial Times, both of which operate successful subscription services.  

"Google's decision to let publishers determine how much content readers can sample from search is a positive development,” said Kinsey Wilson, an adviser to New York Times CEO Mark Thompson. "We're encouraged as well by Google's willingness to consider other ways of supporting subscription business models and we are looking forward to continuing to work with them to craft smart solutions."

Publishers generally recognize that giving people access to some free content is the way to persuade people to buy their product. The typical approach to sampling is a model called metering, which lets people see a pre-determined number of free stories before a paywall kicks in. We recommend the following approach:

  • Monthly, rather than daily, metering allows publishers more flexibility to experiment with the number of free stories to offer people and to target those more likely to subscribe.
  • For most publishers, 10 articles per month is a good starting point.
  • Please see our Webmaster blog and our guide on Flexible Sampling for more detail on these approaches.

“Try before you buy” underlines what many publishers already know—they need to provide some form of free sampling to be successful on the internet. If it’s too little, then fewer users will click on links to that content or share it, which could have an effect on brand discovery and subsequently may affect traffic over time.

Subscription support

Subscribing to great content should not be as hard as it is today. Registering on a site, creating and remembering multiple passwords, and entering credit card information—these are all hassles we hope to solve.

As a first step we’re taking advantage of our existing identity and payment technologies to help people subscribe on a publication’s website with a single click, and then seamlessly access that content anywhere— whether it’s on that publisher site or mobile app, or on Google Newsstand, Google Search or Google News.

And since news products and subscription models vary widely, we’re collaborating with publishers around the world on how to build a subscription mechanism that can meet the needs of a diverse array of approaches—to the benefit of the news industry and consumers alike.  

We’re also exploring how Google’s machine learning capabilities can help publishers recognize potential subscribers and present the right offer to the right audience at the right time.

“It's extremely clear that advertising alone can no longer pay for the production and distribution of high quality journalism—and at the same time the societal need for sustainable independent journalism has never been greater.  Reader-based revenue, aka paid-content, or subscription services, are therefore not just a nice-to-have, but an essential component of a publisher's revenue composition,” said Jon Slade, FT Chief Commercial Officer.

“The Financial Times is welcoming of Google's input and actions to help this critical sector of the media industry, and we've worked very closely with Google to aid understanding of the needs that publishers have and how Google can help. That mutual understanding includes the ability to set controls over the amount of free content given to readers, a level playing field for content discovery, optimised promotion and payment processes. It is important that we now build and accelerate on the discussions and actions to date.”  

We are just getting started and want to get as much input from publishers—large, small, national, local, international—to make sure we build solutions together that work for everyone.  

How publishers can take advantage of machine learning

As the publishing world continues to face new challenges amidst the shift to digital, news media and publishers are tasked with unlocking new opportunities. With online news consumption continuing to grow, it’s crucial that publishers take advantage of new technologies to sustain and grow their business. Machine learning yields tremendous value for media and can help them tackle the hardest problems: engaging readers, increasing profits, and making newsrooms more efficient. Google has a suite of machine learning tools and services that are easy to use—here are a few ways they can help newsrooms and reporters do their jobs

1. Improve your newsroom's efficiency 

Editors want to make their stories appealing and to stand out so that people will read them. So finding just the right photograph or video can be key in bringing a story to life. But with ever-pressing deadlines, there’s often not enough time to find that perfect image. This is where Google Cloud Vision and Video Intelligence can simplify the process by tagging images and videos based on the content inside the actual image. This metadata can then be used to make it easier and quicker to find the right visual.

2.  Better understand your audience

News publishers use analytics tools to grow their audiences, and understand what that audience is reading and how they’re discovering content. Google Cloud Natural Language uses machine learning to understand what your content is about, independent of a website’s section and subsection structure (i.e. Sports, Local, etc.) Today, Cloud Natural Language announced a new content classifier and entity sentiment that digs into the detail of what a story is actually about. For example, an article about a high-tech stadium for the Golden State Warriors may be classified under the “technology” section of a paper, when its content should fall under “technology” and “sports.” This section-independent tagging can increase readership by driving smarter article recommendations and provides better data around trending topics. Naveed Ahmad, Senior Director of Data at Hearst has emphasized that precision and speed are critical to engaging readers: “Google Cloud Natural Language is unmatched in its accuracy for content classification. At Hearst, we publish several thousand articles a day across 30+ properties and, with natural language processing, we're able to quickly gain insight into what content is being published and how it resonates with our audiences."

3. Engage with new audiences

As publications expand their reach into more countries, they have to write for multiple audiences in different languages and many cannot afford multi-language desks. Google Cloud Translation makes translating for different audiences easier by providing a simple interface to translate content into more than 100 languages. Vice launched GoogleFish earlier this year to help editors quickly translate existing Vice articles into the language of their market. Once text was auto-translated, an editor could then push the translation to a local editor to ensure tone and local slang were accurate. Early translation results are very positive and Vice is also uncovering new insights around global content sharing they could not previously identify.

DB Corp, India’s largest newspaper group, publishes 62 editions in four languages and sells about 6 million newspaper copies per day. To address its growing customers and its diverse readership, reporters use Google Cloud Translation to capture and document interviews and source material for articles, with accuracy rates of 95 percent for Hindi alone.

4. Monetize your audience

So far we’ve primarily outlined ways to improve content creation and engagement with readers, however monetization is a critical piece for all publishers. Using Cloud Datalab, publishers can identify new subscription opportunities and offerings. The metadata collected from image, video, and content tagging creates an invaluable dataset to advertisers, such as audiences interested in local events or personal finance, or those who watch videos about cars or travel. The Washington Post has seen success with their in-house solution through the ability to target native ads to likely interested readers. Lastly, improved content recommendation drives consumption, ultimately improving the bottom line.

5. Experiment with new formats

The ability to share news quickly and efficiently is a major concern for newsrooms across the world. However today more than ever, readers are reading the news in different ways across different platforms and the “one format fits all” method is not always best. TensorFlow’s “summary.text” feature can help publishers quickly experiment with creating short form content from longer stories. This helps them quickly test the best way to share their content across different platforms. Reddit recently launched a similar “tl;dr bot” that summarizes long posts into digestible snippets.

6. Keep your content safe for everyone

The comments section can be a place of both fruitful discussion as well as toxicity. Users who comment are frequently the most highly engaged on the site overall, and while publishers want to keep sharing open, it can frequently spiral out of control into offensive speech and bad language. Jigsaw’s Perspective is an API that uses machine learning to spot harmful comments which can be flagged for moderators. Publishers like the New York Times have leveraged Perspective's technology to improve the way all readers engage with comments. By making the task of moderating conversations at scale easier, this frees up valuable time for editors and improves online discussion.

8
Example of New York Time’s moderator dashboard. Each dot represents a negative comment

From the printing press to machine learning, technology continues to spur new opportunities for publishers to reach more people, create engaging content and operate efficiently. We're only beginning to scratch the surface of what machine learning can do for publishers. Keep tabs on The Keyword for the latest developments.

How publishers can take advantage of machine learning

As the publishing world continues to face new challenges amidst the shift to digital, news media and publishers are tasked with unlocking new opportunities. With online news consumption continuing to grow, it’s crucial that publishers take advantage of new technologies to sustain and grow their business. Machine learning yields tremendous value for media and can help them tackle the hardest problems: engaging readers, increasing profits, and making newsrooms more efficient. Google has a suite of machine learning tools and services that are easy to use—here are a few ways they can help newsrooms and reporters do their jobs

1. Improve your newsroom's efficiency 

Editors want to make their stories appealing and to stand out so that people will read them. So finding just the right photograph or video can be key in bringing a story to life. But with ever-pressing deadlines, there’s often not enough time to find that perfect image. This is where Google Cloud Vision and Video Intelligence can simplify the process by tagging images and videos based on the content inside the actual image. This metadata can then be used to make it easier and quicker to find the right visual.

2.  Better understand your audience

News publishers use analytics tools to grow their audiences, and understand what that audience is reading and how they’re discovering content. Google Cloud Natural Language uses machine learning to understand what your content is about, independent of a website’s section and subsection structure (i.e. Sports, Local, etc.) Today, Cloud Natural Language announced a new content classifier and entity sentiment that digs into the detail of what a story is actually about. For example, an article about a high-tech stadium for the Golden State Warriors may be classified under the “technology” section of a paper, when its content should fall under “technology” and “sports.” This section-independent tagging can increase readership by driving smarter article recommendations and provides better data around trending topics. Naveed Ahmad, Senior Director of Data at Hearst has emphasized that precision and speed are critical to engaging readers: “Google Cloud Natural Language is unmatched in its accuracy for content classification. At Hearst, we publish several thousand articles a day across 30+ properties and, with natural language processing, we're able to quickly gain insight into what content is being published and how it resonates with our audiences."

3. Engage with new audiences

As publications expand their reach into more countries, they have to write for multiple audiences in different languages and many cannot afford multi-language desks. Google Cloud Translation makes translating for different audiences easier by providing a simple interface to translate content into more than 100 languages. Vice launched GoogleFish earlier this year to help editors quickly translate existing Vice articles into the language of their market. Once text was auto-translated, an editor could then push the translation to a local editor to ensure tone and local slang were accurate. Early translation results are very positive and Vice is also uncovering new insights around global content sharing they could not previously identify.

DB Corp, India’s largest newspaper group, publishes 62 editions in four languages and sells about 6 million newspaper copies per day. To address its growing customers and its diverse readership, reporters use Google Cloud Translation to capture and document interviews and source material for articles, with accuracy rates of 95 percent for Hindi alone.

4. Monetize your audience

So far we’ve primarily outlined ways to improve content creation and engagement with readers, however monetization is a critical piece for all publishers. Using Cloud Datalab, publishers can identify new subscription opportunities and offerings. The metadata collected from image, video, and content tagging creates an invaluable dataset to advertisers, such as audiences interested in local events or personal finance, or those who watch videos about cars or travel. The Washington Post has seen success with their in-house solution through the ability to target native ads to likely interested readers. Lastly, improved content recommendation drives consumption, ultimately improving the bottom line.

5. Experiment with new formats

The ability to share news quickly and efficiently is a major concern for newsrooms across the world. However today more than ever, readers are reading the news in different ways across different platforms and the “one format fits all” method is not always best. TensorFlow’s “summary.text” feature can help publishers quickly experiment with creating short form content from longer stories. This helps them quickly test the best way to share their content across different platforms. Reddit recently launched a similar “tl;dr bot” that summarizes long posts into digestible snippets.

6. Keep your content safe for everyone

The comments section can be a place of both fruitful discussion as well as toxicity. Users who comment are frequently the most highly engaged on the site overall, and while publishers want to keep sharing open, it can frequently spiral out of control into offensive speech and bad language. Jigsaw’s Perspective is an API that uses machine learning to spot harmful comments which can be flagged for moderators. Publishers like the New York Times have leveraged Perspective's technology to improve the way all readers engage with comments. By making the task of moderating conversations at scale easier, this frees up valuable time for editors and improves online discussion.

8
Example of New York Time’s moderator dashboard. Each dot represents a negative comment

From the printing press to machine learning, technology continues to spur new opportunities for publishers to reach more people, create engaging content and operate efficiently. We're only beginning to scratch the surface of what machine learning can do for publishers. Keep tabs on The Keyword for the latest developments.

How publishers can take advantage of machine learning

As the publishing world continues to face new challenges amidst the shift to digital, news media and publishers are tasked with unlocking new opportunities. With online news consumption continuing to grow, it’s crucial that publishers take advantage of new technologies to sustain and grow their business. Machine learning yields tremendous value for media and can help them tackle the hardest problems: engaging readers, increasing profits, and making newsrooms more efficient. Google has a suite of machine learning tools and services that are easy to use—here are a few ways they can help newsrooms and reporters do their jobs

1. Improve your newsroom's efficiency 

Editors want to make their stories appealing and to stand out so that people will read them. So finding just the right photograph or video can be key in bringing a story to life. But with ever-pressing deadlines, there’s often not enough time to find that perfect image. This is where Google Cloud Vision and Video Intelligence can simplify the process by tagging images and videos based on the content inside the actual image. This metadata can then be used to make it easier and quicker to find the right visual.

2.  Better understand your audience

News publishers use analytics tools to grow their audiences, and understand what that audience is reading and how they’re discovering content. Google Cloud Natural Language uses machine learning to understand what your content is about, independent of a website’s section and subsection structure (i.e. Sports, Local, etc.) Today, Cloud Natural Language announced a new content classifier and entity sentiment that digs into the detail of what a story is actually about. For example, an article about a high-tech stadium for the Golden State Warriors may be classified under the “technology” section of a paper, when its content should fall under “technology” and “sports.” This section-independent tagging can increase readership by driving smarter article recommendations and provides better data around trending topics. Naveed Ahmad, Senior Director of Data at Hearst has emphasized that precision and speed are critical to engaging readers: “Google Cloud Natural Language is unmatched in its accuracy for content classification. At Hearst, we publish several thousand articles a day across 30+ properties and, with natural language processing, we're able to quickly gain insight into what content is being published and how it resonates with our audiences."

3. Engage with new audiences

As publications expand their reach into more countries, they have to write for multiple audiences in different languages and many cannot afford multi-language desks. Google Cloud Translation makes translating for different audiences easier by providing a simple interface to translate content into more than 100 languages. Vice launched GoogleFish earlier this year to help editors quickly translate existing Vice articles into the language of their market. Once text was auto-translated, an editor could then push the translation to a local editor to ensure tone and local slang were accurate. Early translation results are very positive and Vice is also uncovering new insights around global content sharing they could not previously identify.

DB Corp, India’s largest newspaper group, publishes 62 editions in four languages and sells about 6 million newspaper copies per day. To address its growing customers and its diverse readership, reporters use Google Cloud Translation to capture and document interviews and source material for articles, with accuracy rates of 95 percent for Hindi alone.

4. Monetize your audience

So far we’ve primarily outlined ways to improve content creation and engagement with readers, however monetization is a critical piece for all publishers. Using Cloud Datalab, publishers can identify new subscription opportunities and offerings. The metadata collected from image, video, and content tagging creates an invaluable dataset to advertisers, such as audiences interested in local events or personal finance, or those who watch videos about cars or travel. The Washington Post has seen success with their in-house solution through the ability to target native ads to likely interested readers. Lastly, improved content recommendation drives consumption, ultimately improving the bottom line.

5. Experiment with new formats

The ability to share news quickly and efficiently is a major concern for newsrooms across the world. However today more than ever, readers are reading the news in different ways across different platforms and the “one format fits all” method is not always best. TensorFlow’s “summary.text” feature can help publishers quickly experiment with creating short form content from longer stories. This helps them quickly test the best way to share their content across different platforms. Reddit recently launched a similar “tl;dr bot” that summarizes long posts into digestible snippets.

6. Keep your content safe for everyone

The comments section can be a place of both fruitful discussion as well as toxicity. Users who comment are frequently the most highly engaged on the site overall, and while publishers want to keep sharing open, it can frequently spiral out of control into offensive speech and bad language. Jigsaw’s Perspective is an API that uses machine learning to spot harmful comments which can be flagged for moderators. Publishers like the New York Times have leveraged Perspective's technology to improve the way all readers engage with comments. By making the task of moderating conversations at scale easier, this frees up valuable time for editors and improves online discussion.

8
Example of New York Time’s moderator dashboard. Each dot represents a negative comment

From the printing press to machine learning, technology continues to spur new opportunities for publishers to reach more people, create engaging content and operate efficiently. We're only beginning to scratch the surface of what machine learning can do for publishers. Keep tabs on The Keyword for the latest developments.

Source: Google Cloud


Supporting local journalism with Report for America

I cut my teeth in journalism as a local reporter for my hometown paper, the Northfield News, and saw firsthand how local journalism impacts a community. Local reporters go to city council meetings to hold city governments accountable. They’re the first to show up when disaster strikes, getting critical information to their readers. And they provide the first draft of history for cities and towns, providing reporting that keeps their communities safe, informed and connected.


But not all communities in the U.S. are fortunate enough to have a strong local media presence—declining sales and revenues have led to local papers closing and local newsrooms shrinking. Despite this gloomy picture, there are lots of ideas about how to strengthen the local news ecosystem, and today we’re announcing our support of one new approach: Report for America.


An initiative of The GroundTruth Project, Report for America is taking its inspiration from Teach for America and applying it to local journalism. Its goal is to attract service-minded candidates and place them in local newsrooms for a year as reporters.


The first pilot, which will start early next year, aims to fill 12 reporting positions in newsrooms across the country, in areas underserved by local media. There will also be a community element to the work—a reporter might also help a local high school start or improve their student-run news site or newspaper.


As a founding member of this exciting initiative, the Google News Lab will provide in-depth training to the Report for America Corps members focusing on digital and data journalism, and equip them with the proper technology—Chromebooks, 360-degree cameras, and mobile phones.


Joining us in supporting Report for America are the Knight Foundation, The Lenfest Institute for Journalism, Galloway Family Foundation, Solutions Journalism Network and the Center for Investigative Reporting.


Report for America is just one part of our efforts to strengthen local news here at Google. Here are a few others:

  • To provide the proper exposure for local news outlets covering national stories, Google News labels those stories so readers can easily find on-the-ground reporting. Additionally we’ve made it easier for people to follow local news sources with a dedicated local tab on the Google News home page. And just last week, in the U.S., Google News went hyperlocal by adding clearly labeled Community Updates that provide information about news and events happening in your area so you’ll always know what’s going on.
  • We want to help publishers succeed financially by monetizing their content online. We have a key partnership with the Local Media Consortium—which represents more than 1,600 local media outlets—to tap into the power of our ad technology to fund and support local journalism. At their annual summit the LMC announced combined savings and revenue of more than $110 million for partners, based on that collaboration with Google.
  • At the Google News Lab, journalism training is an important component of the work we do to help journalists and newsrooms develop new skills and access the latest digital tools. Through  a partnership with the Society for Professional Journalists we’ve trained more than 9,500 local reporters across America in the last year alone. And a collaboration with the Center for Investigative Reporting’s Reveal Labs has helped build the capacity of investigative teams in Mississippi and New Jersey, a model we’re looking to scale in 2018.

We hope Report for America will bring fresh thinking and a new approach to strengthening local news.

Supporting local journalism with Report for America

I cut my teeth in journalism as a local reporter for my hometown paper, the Northfield News, and saw firsthand how local journalism impacts a community. Local reporters go to city council meetings to hold city governments accountable. They’re the first to show up when disaster strikes, getting critical information to their readers. And they provide the first draft of history for cities and towns, providing reporting that keeps their communities safe, informed and connected.


But not all communities in the U.S. are fortunate enough to have a strong local media presence—declining sales and revenues have led to local papers closing and local newsrooms shrinking. Despite this gloomy picture, there are lots of ideas about how to strengthen the local news ecosystem, and today we’re announcing our support of one new approach: Report for America.


An initiative of The GroundTruth Project, Report for America is taking its inspiration from Teach for America and applying it to local journalism. Its goal is to attract service-minded candidates and place them in local newsrooms for a year as reporters.


The first pilot, which will start early next year, aims to fill 12 reporting positions in newsrooms across the country, in areas underserved by local media. There will also be a community element to the work—a reporter might also help a local high school start or improve their student-run news site or newspaper.


As a founding member of this exciting initiative, the Google News Lab will provide in-depth training to the Report for America Corps members focusing on digital and data journalism, and equip them with the proper technology—Chromebooks, 360-degree cameras, and mobile phones.


Joining us in supporting Report for America are the Knight Foundation, The Lenfest Institute for Journalism, Galloway Family Foundation, Solutions Journalism Network and the Center for Investigative Reporting.


Report for America is just one part of our efforts to strengthen local news here at Google. Here are a few others:

  • To provide the proper exposure for local news outlets covering national stories, Google News labels those stories so readers can easily find on-the-ground reporting. Additionally we’ve made it easier for people to follow local news sources with a dedicated local tab on the Google News home page. And just last week, in the U.S., Google News went hyperlocal by adding clearly labeled Community Updates that provide information about news and events happening in your area so you’ll always know what’s going on.
  • We want to help publishers succeed financially by monetizing their content online. We have a key partnership with the Local Media Consortium—which represents more than 1,600 local media outlets—to tap into the power of our ad technology to fund and support local journalism. At their annual summit the LMC announced combined savings and revenue of more than $110 million for partners, based on that collaboration with Google.
  • At the Google News Lab, journalism training is an important component of the work we do to help journalists and newsrooms develop new skills and access the latest digital tools. Through  a partnership with the Society for Professional Journalists we’ve trained more than 9,500 local reporters across America in the last year alone. And a collaboration with the Center for Investigative Reporting’s Reveal Labs has helped build the capacity of investigative teams in Mississippi and New Jersey, a model we’re looking to scale in 2018.

We hope Report for America will bring fresh thinking and a new approach to strengthening local news.