Tag Archives: Journalism & News

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.

The state of data journalism in 2017

Data journalism has been a big focus for us at the Google News Lab over the past three years—in building tools, creating content and sharing data with the data journalism community. We wanted to see if we’re taking the right approach: how big is data journalism, what challenges do data journalists face and how is it going to change?

Up until today, we really haven’t had clear answers to those questions. So, in collaboration with PolicyViz, we conducted a series of in-depth qualitative interviews and an online survey to better understand how journalists use data to tell stories. We conducted 56 detailed in-person interviews with journalists in the U.S., UK, Germany and France and an online survey of more than 900 journalists. Our analysis offers a glimpse into the state of data journalism in 2017 and highlights key challenges for the field moving forward. 

The result is one of the first comprehensive studies of the field and its activity. A decade ago, data journalists there was only handful of data journalists. 

Today, this research shows that:

  • 42% of reporters use data to tell stories regularly (twice or more per week).
  • 51% of all news organizations in the U.S. and Europe now have a dedicated data journalist—and this rises to 60% for digital-only platforms.
  • 33% of journalists use data for political stories, followed by 28% for finance and 25% for investigative stories.

There is a big international variation, even within our study. In France, 56% of newsrooms have  a data journalist, followed by Germany with 52%, the UK with 52%, and the U.S. with 46%. Despite its huge growth, data journalism still faces challenges as we head towards 2018.

  • 53% of the sample saw data journalism as a speciality skill that requires extensive training, and is not easy to pick up.

  • Survey respondents also discussed the time pressures they face and the limited bandwidth from dedicated data journalists who can clean, process, and analyze data. We found that 49% of data stories are created in a day or less.

  • Our research also found that data visualization tools are not keeping up with the pace of innovation. As a result, reporters are building their own solutions: a fifth of data journalists use in-house tools and software, whether it’s data visualization tools or even data cleaning solutions.

9

More than half of respondents want their organizations to use more data to tell stories. But, some felt the return on investment was unclear as the production of data journalism can take significant time and resources.


The future of data journalism, though, has never been as important as it is today, nor as much a part of the way journalists work every day, as this study shows. As one of our interviewees put it:


We heard from one data journalist in the U.S. that “data is a good way of getting to the truth of things ... in this post-truth era, this work is increasingly important. We are all desperately searching for facts.”

The state of data journalism in 2017

Data journalism has been a big focus for us at the Google News Lab over the past three years—in building tools, creating content and sharing data with the data journalism community. We wanted to see if we’re taking the right approach: how big is data journalism, what challenges do data journalists face and how is it going to change?

Up until today, we really haven’t had clear answers to those questions. So, in collaboration with PolicyViz, we conducted a series of in-depth qualitative interviews and an online survey to better understand how journalists use data to tell stories. We conducted 56 detailed in-person interviews with journalists in the U.S., UK, Germany and France and an online survey of more than 900 journalists. Our analysis offers a glimpse into the state of data journalism in 2017 and highlights key challenges for the field moving forward. 

The result is one of the first comprehensive studies of the field and its activity. A decade ago, data journalists there was only handful of data journalists. 

Today, this research shows that:

  • 42% of reporters use data to tell stories regularly (twice or more per week).
  • 51% of all news organizations in the U.S. and Europe now have a dedicated data journalist—and this rises to 60% for digital-only platforms.
  • 33% of journalists use data for political stories, followed by 28% for finance and 25% for investigative stories.

There is a big international variation, even within our study. In France, 56% of newsrooms have  a data journalist, followed by Germany with 52%, the UK with 52%, and the U.S. with 46%. Despite its huge growth, data journalism still faces challenges as we head towards 2018.

  • 53% of the sample saw data journalism as a speciality skill that requires extensive training, and is not easy to pick up.

  • Survey respondents also discussed the time pressures they face and the limited bandwidth from dedicated data journalists who can clean, process, and analyze data. We found that 49% of data stories are created in a day or less.

  • Our research also found that data visualization tools are not keeping up with the pace of innovation. As a result, reporters are building their own solutions: a fifth of data journalists use in-house tools and software, whether it’s data visualization tools or even data cleaning solutions.

9

More than half of respondents want their organizations to use more data to tell stories. But, some felt the return on investment was unclear as the production of data journalism can take significant time and resources.


The future of data journalism, though, has never been as important as it is today, nor as much a part of the way journalists work every day, as this study shows. As one of our interviewees put it:


We heard from one data journalist in the U.S. that “data is a good way of getting to the truth of things ... in this post-truth era, this work is increasingly important. We are all desperately searching for facts.”

Ending FOMO with Community Updates

FOMO: that feeling you get when you fear you're missing out on something super awesome, interesting or important to you: like a fun gig in the local park, an important school board meeting, or a community clean up down the road from your house.

Well, Community Updates could be your solution. It will bring you information about news and events happening right in your own backyard so you’ll always know what’s going on.

Even though Google News helps you understand what’s happening around the world, we realized that it wasn’t easy for people to get information about their own communities.

So we used machine learning techniques to find additional sources publishing local content— like hyperlocal bloggers and high school newspapers—and we realized these and other local sources deserved their own unique space. The redesign of the Google News earlier this year provided a place for this type of news to live—a tab at the top of the page called Local. That means everything from this outdoor donut and craft beer pairing event in Rochester, or students organizing a hackathon next door to the Googleplex at Mountain View High School, to this list of open restaurants and grocery stores in Houston during Hurricane Harvey will be easier than ever to find and keep tabs on.

1
Community Updates are found under the "Local" tab on Google News.

Community Updates builds on the work we’ve been doing for the last decade in highlighting local information and publications (we first launched local sections in 2008). Last year we expanded to all 81 Google News editions and put a spotlight on local sources of national news.

We hope Community Updates will make Google News even more useful, so that you’re not worried about missing out on cool events and opportunities around you. At the moment this feature is only available in the U.S. in English on news.google.com and will be available in the Google News & Weather App later this fall. More information on Community Updates is available here. See our Publisher Center for more on Getting Into Google News.

Ending FOMO with Community Updates

FOMO: that feeling you get when you fear you're missing out on something super awesome, interesting or important to you: like a fun gig in the local park, an important school board meeting, or a community clean up down the road from your house.

Well, Community Updates could be your solution. It will bring you information about news and events happening right in your own backyard so you’ll always know what’s going on.

Even though Google News helps you understand what’s happening around the world, we realized that it wasn’t easy for people to get information about their own communities.

So we used machine learning techniques to find additional sources publishing local content— like hyperlocal bloggers and high school newspapers—and we realized these and other local sources deserved their own unique space. The redesign of the Google News earlier this year provided a place for this type of news to live—a tab at the top of the page called Local. That means everything from this outdoor donut and craft beer pairing event in Rochester, or students organizing a hackathon next door to the Googleplex at Mountain View High School, to this list of open restaurants and grocery stores in Houston during Hurricane Harvey will be easier than ever to find and keep tabs on.

1
Community Updates are found under the "Local" tab on Google News.

Community Updates builds on the work we’ve been doing for the last decade in highlighting local information and publications (we first launched local sections in 2008). Last year we expanded to all 81 Google News editions and put a spotlight on local sources of national news.

We hope Community Updates will make Google News even more useful, so that you’re not worried about missing out on cool events and opportunities around you. At the moment this feature is only available in the U.S. in English on news.google.com and will be available in the Google News & Weather App later this fall. More information on Community Updates is available here. See our Publisher Center for more on Getting Into Google News.

Ending FOMO with Community Updates

FOMO: that feeling you get when you fear you're missing out on something super awesome, interesting or important to you: like a fun gig in the local park, an important school board meeting, or a community clean up down the road from your house.

Well, Community Updates could be your solution. It will bring you information about news and events happening right in your own backyard so you’ll always know what’s going on.

Even though Google News helps you understand what’s happening around the world, we realized that it wasn’t easy for people to get information about their own communities.

So we used machine learning techniques to find additional sources publishing local content— like hyperlocal bloggers and high school newspapers—and we realized these and other local sources deserved their own unique space. The redesign of the Google News earlier this year provided a place for this type of news to live—a tab at the top of the page called Local. That means everything from this outdoor donut and craft beer pairing event in Rochester, or students organizing a hackathon next door to the Googleplex at Mountain View High School, to this list of open restaurants and grocery stores in Houston during Hurricane Harvey will be easier than ever to find and keep tabs on.

1
Community Updates are found under the "Local" tab on Google News.

Community Updates builds on the work we’ve been doing for the last decade in highlighting local information and publications (we first launched local sections in 2008). Last year we expanded to all 81 Google News editions and put a spotlight on local sources of national news.

We hope Community Updates will make Google News even more useful, so that you’re not worried about missing out on cool events and opportunities around you. At the moment this feature is only available in the U.S. in English on news.google.com and will be available in the Google News & Weather App later this fall. More information on Community Updates is available here. See our Publisher Center for more on Getting Into Google News.