Panel Orientation: Platform News Products

Last updated: August 2021 (2020 edition)

The purpose of this document is to provide participants of our News Ranking Review Panels with information on each platform news product being reviewed by the project.

NewsQ selected eight news products to examine and from which to collect data:

This review has focused mainly on documentation available from news product pages. As we aim to update this orientation as more information becomes available, your suggestions are welcome.

How to Use This Document

The following document provides overviews for each news product, mostly from the perspective of the goals expressed by platform owners themselves, with background for each product (vis-a-vis news); its process; and, how it works.

Four aspects have been selected for our overviews to support conversations related to news ranking and recommendations systems online:

  • Technological Interface: Is the product oriented to desktop or mobile?
  • Content Recommendation: Do articles appearing within the news product appear due to algorithmic processing alone, or is there human curation?
  • Content Guidelines: Do the news products offer rationales related to the content recommendation, including mission statements for the products or a description of their content-related processes?
  • Customized COVID-19 Policy: Has the product developed a specific policy related to COVID-19 content?

Each product overview starts with an information box to allow for quick scanning, like the one below:

Interface Orientation: [✓] Desktop [✗] Not Mobile
Content Recommendation: [✓] Algorithmic [✓] Human
Content Guidelines: [✓]Exists
Customized COVID-19 Policy: [✓] Present

A check mark ✓ indicates that the news product incorporates the stated dimension. When there is an ✗, the product does not focus on this feature or have this feature in a way that we have been able to find related documentation.

At the bottom of each section, we include links to archived versions of the documents from which we summarized our overview.

Note: The information in the respective overviews relate to each news product only and, unless otherwise specified, does not refer to other products or services by each platform.

Alphabet: Google News

Interface Orientation: [✓]Desktop [✓]Mobile
Content Recommendation: [✓]Algorithmic [*]Human (Special Coverage)
Content Guidelines: [✓]Exists
Customized COVID-19 Policy:[✓]Present

Background. Google News primarily uses algorithms to select and rank news content. These algorithms choose what all users see in the Top Stories, Headlines, and Full Coverage sections, and they personalize content for each user in sections such as For You.

Members of the Google News staff are able to add temporary topics for special circumstances, like events or elections. They also choose news topics and publications to highlight in the Newsstand tab of the Google News App.

According to the platform, the essential purpose of the product is “to help everyone understand the world by connecting people with high quality news from a variety of perspectives.”

Google News states it aims to “help you make sense of the news” by:

  • “Using technology to connect you to information”
  • “Providing access to context and multiple perspectives”
  • “Elevating trustworthy information” 
  • “Fighting misrepresentative and deceptive practice”

Google News also says it aims to “help sustain a healthy news ecosystem” by:

  • “Building and strengthening audiences for high-quality news”;
  • “Collaborating with the news industry to drive innovation.”

Ranking Factors & Process

Screenshot of Google News categories on desktop (13 Aug 2021).

Google News offers a number of general news categories that are available for every user. The content available in Top Stories is chosen algorithmically and only varies depending on language and regional settings. 

Content is also personalized in the For You sections based on user-specified interest about topics, location, and publishers. Depending on account settings, Google News can suggest content based on user activity. 

Google News describes its ranking process as one in which its algorithms weigh a host of factors. It identifies its primary factors as:

  • Relevance
  • Interests
  • Location
  • Prominence
  • Authoritativeness
  • Freshness
  • Usability

Ranking in Google News is determined by the following factors

  • Relevance (Relevance to search terms)
  • Location (Google uses location to help find content relevant to a user’s area, such as Local stories)
  • Prominence (Noteworthy news events as signaled by trending articles or stories, as well as coverage being prominently featured by publishers)
  • Authoritativeness (Authoritativeness signals are designed to help surface pages that “demonstrate expertise, authoritativeness and trustworthiness on a given topic”)
  • Freshness (Freshness refers to when the article was published and when it is more useful to have up-to-date content over an older article)

In addition to the factors above, the For You tab is ranked based on: 

  • Usability (usability assesses page load times, how easy it is to view content on the site, if the site is formatted for different devices, etc.)
  • Interests (depending on account settings, individual interests may help determine results in sections such as Discover or For You in Google News)

Google News emphasizes that it “elevates news from authoritative sources” and that it “requires publishers to be transparent and accountable in order to be represented in news results” in accordance with its content policies. Google News also states that it “uses technology to sort massive amounts of content to connect you with important, relevant, and useful news.” [Emphasis added]

Content Labels. Google News uses labels to help classify and sort information. Publishers are advised to apply labels to their entire site as well as different parts of their site. Labels are also algorithmically applied to a publisher’s site.

The labels that publishers can apply themselves are: 

  • Opinion
  • Satire
  • User-generated
  • Press release
  • Blog

Information found in this section is adapted from the following documents: How Google News stories are selected, Building news experiences, Help you make sense of the news, Surfacing useful and relevant content, Presenting news in helpful ways, Ranking within Google News, Organizing news from around the web, What does each label mean?

External Audits. While Google News may continually be refining its approach and results, external audits of Google News and Google Search have taken place in recent years.

Apple News

Interface Orientation: [✓]Desktop [✓]Mobile
Content Recommendation: [✓]Algorithmic [✓]Human
Content Guidelines: [✓]Exists
Customized COVID-19 Policy: [✓]Present

Background. Apple News is an algorithmically and human-determined ranking and recommendation system for news content. It can be accessed via desktop app at or as the “Apple News” mobile app. The homepage presents Top Stories in the Today section. Scrolling through Apple’s Today section, past Top Stories, takes users past a number of other sections (e.g., Politics, Business) that either populate by default or that the user selected to follow. Each section displays previews for a certain number of stories as the user scrolls past.

At the bottom of the app, there are three main sections: Today, News+ (which allows users to dive deeper into certain publications), Audio, and Following (which allows users to follow certain topics or beats).

Content on the service is also curated by topic. A set number of sections show up by default; other sections allow users to find news in areas they have explicitly selected to follow in the app (See the Apple News+ description).

Screenshot from Apple News Top stories, Trending Stories and For You (13 Aug 2021).
Screenshot from Apple News Trending Stories (13 Aug 2021).

Ranking Factors & Process

Apple editorial staff chooses five stories to be featured in the Top Stories section of Apple News. The team reportedly selects from a pool of between 100 and 200 pitches per day. The Apple editorial team also curates a selection of featured stories. 

Algorithms are used to select content for the Trending Stories section. News content is also personalized using algorithms when users follow, unfollow, or block categories. 

Information found in this section is adapted from the following documents: Apple News, View news stories chosen just for you on iPhone, Auditing News Curation Systems: A Case Study Examining Algorithmic and Editorial Logic in Apple News, Apple News’s Radical Approach: Humans Over Machines.

Facebook News (News Tab)

Interface Orientation: [*]Limited Desktop [✓]Mobile
Content Recommendation: [✓]Algorithmic [✓]Human
Content Guidelines: [✓]Exists
Customized COVID-19 Policy: [✓]Present

Background. Facebook News is a news product that is available for both desktop and mobile users. A blend of human and algorithmic curation is implemented to rank and recommend content to users. The platform uses machine learning models to personalize a users’ news experience, choosing content based on diverse factors including previous engagement. In addition, Facebook’s human curation team chooses content based on publicly editorial guidelines. According to their public-facing materials, the platform news product aims to deliver content that is “informative, reliable and relevant to your community”.  This feature is different from Facebook’s News Feed which ranks and recommends activity from the pages, people and groups that a user follows.

News Sections currently include: 

  • Home
  • New For You
  • COVID 19
  • Your Local News
  • Science & Tech
  • Health 
  • Entertainment 
  • Business
  • Sports
Screenshot from Facebook News site on desktop (13 August 2021).

Selection of News Pages and Publishers. To be included as a news source on Facebook news, publishers must meet Facebook’s News Page Index Registration Guidelines which includes: 

  • Being active during the past 90 days
  • Status as a news provider with a multi-person editorial staff
  • Reporting on current events or timely information
  • Citations or links to factual sources
  • Date and time stamps on published content
  • Pages that primarily publish content that is neither aggregated nor user-generated
  • Provides transparent information about writers or editors

Publishers must also meet integrity standards which look at factors such as:

  • Misinformation
  • Community standards violations (e.g., hate speech)
  • Clickbait, engagement bait, and scraped content

Facebook divides publishers into four main categories

  • General News 
  • Topical News
  • Diverse News 
  • Local News

Ranking & Recommendation

Facebook News prioritizes original reporting, diverse perspectives, and relevant stories. The news platform product only includes publishers who register and meet the aforementioned news page index registration requirements. A machine learning model identifies news content using some of the same guidelines from the news page index. 

Algorithmically Curated Content. Facebook News uses machine learning algorithms to personalize the news experience for each user. The ML model evaluates articles based on thousands of “signals” (including publisher location, byline, topic, previous interaction etc.) and the chosen articles are given a score using a predictive algorithm similar to the one that ranks content in the news feed. The score is intended to measure the likelihood that a reader will care about the content, ultimately upranking or downranking content according to the score. Users can further personalize the content they receive by hiding articles and  blocking publishers.  

To personalize Facebook News to include local news, users can set a primary location in the settings function.

Human-Curated Content. A team of journalists curates content to give an overview of the day’s news and the biggest headlines of the day.

According to Facebook, topics are chosen based on: 

  • Prevalence
  • Interest
  • Impact
  • Diversity

They state that they prioritize stories based on: 

  • Facts
  • Diverse voices
  • Original reporting
  • On-the-record sourcing
  • Timeliness
  • Depth and context
  • Fairness
  • Local reporting

Information Centers. Human curation teams are also responsible for updating information on the COVID-19 Information Center and the Climate Science Information Center. 

Information found in this section is adapted from the following documents: How Facebook News WorksHow machine learning powers Facebook’s News Feed ranking algorithm, Facebook Business Help Center, Facebook registration guidelines, How News Feed Works.

Microsoft: Bing News

Interface Orientation: [✓]Desktop [✓]Mobile
Content Recommendation: [✓]Algorithmic [✓]Human
Content Guidelines:[✓]Exists
Customized COVID-19 Policy: [✗]Unable to find

Background. Bing News is a Microsoft product that uses an algorithmically-determined ranking and recommendation system for news content. It can be accessed via web at or in the news section of the “Microsoft Bing Search” mobile app. The homepage presents Top Stories. Content on the service is also curated by topic by choosing interests to follow such as news, sports, and weather. Bing news is divided into categories which can be seen in the sidebar of the site page, including: For you, Top Stories, Sports, U.S. Local, World, Science, Technology, Entertainment, Politics, and Business.

To be eligible as a news source in Bing News, publishers must meet certain requirements and adhere to best practices as outlined by the PubHub Guidelines

Non-news sites are automatically disqualified from inclusion as well as sites that do not publish with regular frequency and those that do not meet certain grammar standards. These are defined in the PubHub Guidelines as follows:

  • “Non-news sites designed primarily to market products or services”
  • “Sites with a primary purpose of unauthorized news or content aggregation”
  • “Sites that do not publish with some level of frequency”
  • “Sites publishing content that does not adhere to basic standards of grammar, punctuation, sentence structure, spelling, and word usage”

Bing’s PubHub Guidelines also identify the following journalistic best practices which sites must adhere to if they are to be included as a news source: 

A) Accountability and Transparency. Sites must provide easily identifiable and accessible ownership and contact information, including:

  • Publisher name
  • Physical address
  • Email address
  • Phone number

B) Content Rights and Responsibility. Sites are responsible for the content on their site and must have legal rights to publish.

C) Attribution and Representation. Sites must provide information about authorship, source attribution, and must clearly label content. These guidelines include:

  • “Clear, verifiable authorship”
  • “Bylines must primarily use the full names of writers”
  • “Sources must be provided for facts, quotes, and opinions”
  • “Headlines and link text must accurately represent the connected content”
  • “Site content consistently reflects the stated purpose and theme of the site”
  • “Commentary, opinion, and reviews must be clearly labeled”

Ranking Factors & Process

Content is algorithmically curated based on many factors including:

  • Source authority
  • Newsworthiness
  • Originality
  • Relevance

Bing News can be personalized for each user based on their settings which include:

  • Language
  • Country or region
  • Location
Snapshot of Desktop version of Bing News settings (7 July 2021).
Desktop version of Bing News settings (7 July 2021).

The desktop version of Bing News allows users to further personalize the news experience by choosing personal interests to follow.

News interests search bar on the desktop version of Bing News (13 Aug 2021).

Content Labels. Bing News categorizes news content to identify “traditional news reporting” from other content like analysis and opinion. Labels are both provided by publishers (according to standards set by The Trust Project) or by Bing which scans the article:

  • Analysis (“Based on factual reporting, though it may incorporate the expertise of the author and offer interpretations and conclusions”)
  • Backgrounder (“Provides context, definition, and detail on a news topic”)
  • Fact check (“Checks a specific statement or set of statements asserted as fact”)
  • In depth (“Provides a deep look at a news-related topic and takes 10 minutes or more to read”)
  • Live update (“Receives continuous updates while an event is developing”)
  • Local source (“Publisher is based at or near the location of the story”)
  • Most cited (“Article being linked to the most within a collection of news articles”)
  • Opinion (“Advocates for ideas and draws conclusions based on the author’s interpretation of facts and data”)
  • Review (“An assessment or critique of a service, product, or creative endeavor”)
  • Satire (“Humorous/satirical article not intended to be understood as factual”)

Information found in this section is adapted from the following documents: Bing News PubHub, Get the latest news (Bing Help), About interests on Bing.

Microsoft: Microsoft News

Interface Orientation: [✓]Desktop [✗]Not Mobile
Content Recommendation: [✓]Algorithmic [✓]Human
Content Guidelines: []No longer exists*
Customized COVID-19 Policy: [✗]Not found

Background. Microsoft News is a human and machine-determined ranking and recommendation system which curates content for, The Edge browser start page, the Microsoft News app, and more. It can be accessed via web at or as the “Microsoft News” mobile app.

The Edge start page presents Headlines and content on the service is curated by topic. A set number of sections show up by default; other sections allow users to find news in areas they have explicitly selected to follow in the app; because it allows for individual sign-in, the products may reflect personal interest given their statement that “user choice and personalization are essential to the experience.”  

Rather than a mission statement, one can find an updated Microsoft News belief statement that includes: 

  • “A free, well-funded press plays a critical role in society”
  • “In delivering unparalleled breadth and depth of high-quality journalism”
  • “That trustworthy and diverse perspectives matter”
  • “User choice and personalization are essential to the experience”

Microsoft News no longer has a set of defined Editorial Standards to which it refers (2020 version). Instead, its principles can be discovered in a FAQ for Microsoft News.

Ranking Factors & Process

According to its FAQ, “Microsoft News believes in the power of combining human and machine curation.” Microsoft News content is curated by hundreds of editors in combination with algorithms that personalize based on user preferences. Microsoft News publishes content from over 1200 publishers that send “more than 100,000 unique pieces of content” everyday. Then:

“Our AI scans the content as it arrives, processes to understand dimensions like freshness, category, topic type, opinion content and potential popularity and then presents it for our editors. Our algorithms suggest appropriate photos to pair with content to help bring stories to life. Editors then curate the top stories throughout the day, across a variety of topics, so our readers get the latest news from the best sources.”

(from About us)

Microsoft News states that it labels content in an effort to clearly flag to readers when a news article contains advertising, such as sponsored studies or native advertising. According to Microsoft’s FAQ, this content is marked with an Ad label.

Factual Content. If Microsoft discovers there are “factual or any other significant errors impacting the quality of the content, we immediately notify the publisher and request corrections.”

Bias and Diversity. Stating the challenge of balancing conflicting viewpoints, Microsoft News states that they attempt to provide a range of perspectives in their coverage: “we believe that trustworthy and diverse perspectives matter, and we are constantly working to develop content experiences that will allow us to feature all sides of a story.”

Further Automation. In 2020, Microsoft announced that AI would replace the work of Microsoft externally contracted news producers. According to the Seattle Times, the following are examples of the work that the human contractors performed:

  • Identifying trending news stories from dozens of publishing partners
  • Helping to optimize the content by rewriting headlines
  • Adding better accompanying photographs or slide show to stories
  • Planning content
  • Maintaining the editorial calendars of partner news websites and assigning content to them

Information found in this section is adapted from the following documents: Microsoft News: Trusted News from the World’s Best Journalists, Microsoft News – About us, Microsoft News feedback – frequently asked questions.

Twitter Explore — News

Interface Orientation: [✓]Desktop [✓]Mobile
Content Recommendation: [✓]Algorithmic [*]Limited Human (Twitter Moments, COVID-19)
Content Guidelines: [*]Limited documentation
Customized COVID-19 Policy: [✓]Present

Screenshot of Twitter Explore News Feed (2 July 2021)

Background. Twitter’s Explore Tab and News Tab is an algorithmically determined ranking and recommendation system for news content. It can be accessed via web at Explore ( or on the Twitter mobile app. Twitter provides little information about how the Explore tab is driven in general including its News section: “Explore tabs may vary based on your location and settings.”

To reach the news section, the user has to navigate to the Explore section on desktop or the search icon on the Twitter app. The main section that then appears is For You. Then the user can navigate to five other sections: COVID-19, Trending, News, Sports, or Entertainment.  

According to a Twitter help desk technician, News in the What’s Happening section or explore page is driven by an algorithm not only based upon “who you follow, your interests, and your location,” but are also based on trending topics and Twitter Moments. The difference between news and a trending topic however was not clarified (2 July 2021). 

Twitter has a number of policies (“The Twitter Rules”) that sometimes involve human curation and can affect what content appears on its platform.  Some policies of interest include:

We highlight a few elements of these policies further below. In 2020, some safety principles on Twitter highlighted the tension with freedom of expression. The page at this URL no longer exists, with the earlier content absorbed into the above policies. An updated version of an ongoing help desk “Safety and security” page continues to address issues such as hacking, privacy, and abuse.  

Ranking Factors & Process 

Algorithmic Recommendation for Trends. News recommendation is driven by an algorithm on Twitter, and is linked to the way they approach trends. By default, trends are oriented to who a user follows, what interests they have expressed, and where the user is based. It is also possible to see what trends exist outside of personalization; instructions are on the FAQ page.  Rules exist for Trends, as governed by the platform policies. Twitter notes that for trends, “in some cases, we may also consider the newsworthiness of the content, or if it is in the public interest when evaluating potential violations. In these cases, the content might continue to trend on our platform.”

Human Curation with Twitter Moments. Twitter Moments are intended to surface “the best of what’s happening on Twitter.”  Moments can be algorithmically generated or human curated by a team. The team’s goal is to provide “insight and context” on conversations happening on the platform in 5 languages across 16 markets.  

Curators are trained according to a policy that focuses on standards of impartiality, accuracy, corrections, and other content-related standards regarding adult, sensitive, and illegal material:

  • Impartiality (“On topics of public debate, we seek to represent a variety of viewpoints whenever feasible.”)
  • Accuracy (“Our goal is to highlight quality Tweets that represent accurate information.”)
  • Corrections (“If we become aware that we have highlighted inaccurate information, we will update the Moment with a visible correction and issue an updated Tweet. In rare cases, we may delete the Moment and post a retraction using the relevant country Twitter account.”)
  • Standards (“Profanity, violence, nudity and other types of potentially sensitive content are avoided except when it’s necessary to highlight a newsworthy conversation”)

Twitter Moment curators are also expected to avoid conflicts of interest. Moments may also be curated by individuals or Twitter partners who must also meet curatorial standards. 

Policies: Misleading Information. According to the platform, “You should be able to find reliable information on Twitter.”  Decisions about adding labels and warnings for “misleading information” such as synthetic tweets and manipulated media — as well as potential removal of those tweets — are assessed using the following questions

  • “Is the media synthetic or manipulated?” 
  • “Is the media shared in a deceptive manner?”
  • “Is the content likely to impact public safety or cause serious harm?”

Twitter takes varying actions when tweets fall into these categories: 

In order to make some of these determinations, Twitter may use their own technology or work with third parties. There is little additional information about the process that Twitter uses to identify tweets that fall into these categories.

Policies: COVID-19. According to Twitter’s COVID-19 misinformation policy, users “may not use Twitter’s services to share false or misleading information about COVID-19 which may lead to harm.” Twitter still uses a blend of automated and human processes to address the spread of harmful messages related to COVID-19. Automated processes surface content that is likely to cause harm, and human teams manually review reports of content that need additional context. Twitter has updated their COVID-19 tabwith “credible” information, including “Why vaccines are safe,” and “What COVID-19 vaccine efficacy means.”

External Audits. Because Twitter states that it relies heavily on personalized algorithms for recommendation of Topic and News content, with little guidance on what qualifies as News, it can be helpful to understand how Twitter algorithms perform. 

A recent 2021 study created archetypal sock puppets to understand how Twitter handled news recommendations generally. Among its discoveries: over time, algorithmic recommendation in Twitter increased the overall diversity of sources, but it also tended to increase partisan messaging while decreasing messages with direct links to news articles in feed results.

Information found in this section is adapted from the following documents: Twitter ExploreVisit Explore to see what’s happening The Twitter Rules Safety on Twitter Twitter Moments guidelines and principlesUpdating our approach to misleading informationBuilding rules in public: Our approach to synthetic & manipulated mediaCOVID-19 Misleading Information Policy,Coronavirus: Staying safe and informed on TwitterTwitter Trends FAQ. It also contains reference to an email from Twitter Support (ref:_00DA0K0A8._5004w2B8X7A:ref).

Yahoo News

Interface Orientation: [✓]Desktop [✗]No Mobile
Content Recommendation: [✓]Algorithmic [✓]Human
Content Guidelines: [✗]Unable to find
Customized COVID-19 Policy: [✗]Unable to find

Background. Content on Yahoo News is both human curated and algorithmically-determined. It can be accessed at The site has a number of default sections including: 

  • News Home
  • US
  • World
  • Politics
  • Health
  • Science
  • Originals

The Originals section includes a dropdown menu with subsections:

  • 360
  • Skullduggery
  • Conspiracyland 
Screenshot of Originals dropdown menu (13 Aug 2021).

Researchers were unable to find any information related to Yahoo’s ranking and recommendation processes. 

Information found in this section is adapted from the homepage of Yahoo News: NewsQ researchers were unable to find public-facing information about ranking factors and process for the platform to date. We will update this section when possible.

Thanks to members of Google News and Facebook for providing feedback on aspects of this orientation.

As stated above, this version of the review has focused mainly on documentation available from news product pages. We aim to update this orientation as more information becomes available; suggestions are welcome at hello [at] newsq [dot] net.