Alternatives for Google Search

The company is based in Paoli, Pennsylvania, in Greater Philadelphia, and has 21 employees. The company name originates from the children's game duck, duck, goose.[8][9]

...DuckDuckGo's results are a compilation of "over 400" sources,[42] including Yahoo! Search BOSS; Wikipedia; Wolfram Alpha; Bing; its own Web crawler (the DuckDuckBot); and others.[3][42][43] It also uses data from crowdsourced sites, including Wikipedia, to populate "Zero-click Info" boxes – grey boxes above the results that display topic summaries and related topics.[44]

DuckDuckGo positions itself as a search engine that puts privacy first and as such it does not store IP addresses, does not log user information and uses cookies only when needed. Weinberg states "By default, DuckDuckGo does not collect or share personal information. That is our privacy policy in a nutshell." However, they do maintain logs of all search terms used.[45]

Weinberg has refined the quality of his search engine results by deleting search results for companies he believes are content mills, like Demand Media's eHow, which publishes 4000 articles per day produced by paid freelance writers, which Weinberg says is, "...low-quality content designed specifically to rank highly in Google's search index." DuckDuckGo also filters pages with substantial advertising.[46]

Instant Answers

In addition to the indexed search results, DuckDuckGo displays relevant results, called Instant Answers,[47] on top of the search page. These Instant Answers are collected from either 3rd party APIs or static data sources like text files. The Instant Answers are called zeroclickinfo because the intention behind these is to provide what the user is searching for on the search result page itself so that the user doesn't have to click any results to find what they are looking for. As of August 20, 2016, there are 989 Instant Answers active.

The Instant Answers are open source.[48] They are maintained on Github and anyone can build or work on them.

Tor hidden service

In August 2010, DuckDuckGo introduced anonymous searching, including an exit enclave, for its search engine traffic using Tor network and enabling access through a Tor hidden service.[49][50] This allows anonymity by routing traffic through a series of encrypted relays. Weinberg stated: "I believe this fits right in line with our privacy policy. Using Tor and DDG, you can now be end to end anonymous with your searching. And if you use our encrypted homepage, you can be end to end encrypted as well."[51]
Voice search

In 2011, DuckDuckGo introduced voice search for users of the Google Chrome voice search extension.[52]

Bangs

DuckDuckGo includes "!Bang" commands, which give users the ability to conveniently search on specific websites – using the site's own search engine if applicable.[53] For example, searching for !w climate on DuckDuckgo will instantly return Wikipedia's Climate entry.
Business model

DuckDuckGo earns revenue in two ways:[54]

Serving ads from the Yahoo–Bing search alliance network, and
Affiliate relationships with Amazon and eBay.

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DuckDuckGo has advanced search syntax you can use to fine-tune your search queries.
Triggers:

Add, "news" to your searches to generate instant-answer news results. For example, LeBron James news
Add, "map" to your search to generate instant-answer map results. For example, Philadelphia map

Go directly to other sites:

Use \ to go to directly to the first search result. We call this I'm Feeling Ducky. For example, \futurama
Use ! to search other sites' search engines directly. We call these bangs. For example, !a blink182 searches Amazon.com for blink182. There are literally thousands of sites covered.

Group search terms:

Every search term should be used by default. That is, we try hard not to autocorrect your query. In other words, we treat your terms as if you typed AND in between them.
If you want to include one term or another, use the uppercase keyword OR in between terms. OR will only operate on adjacent words. Foo bar OR baz is equivalent to Foo ((bar)OR(baz)).
Use double quotes to include an entire phrase inside a syntax block. "foo bar" OR baz is equivalent to ((foo bar)OR(baz)).
In a chain of ORs, the middle groups are automatically quoted. steve jobs OR ballmer microsoft OR dedalus searches steve ((jobs)OR(ballmer microsoft)OR(dedalus)). If you don't want this to happen, you can use ANDs to group ORs together, as detailed below.
term1 OR term2 AND term3 OR term4 searches for ((term1)OR(term2)AND(term3)OR(term4)).
ORs are applied before ANDs. foo bar OR baz AND "term1 term2" OR term3 is equivalent to foo (((bar)OR(baz))AND((term1 term2)OR(term3))). This will return pages with the word foo, one of either bar or baz, and one of either "term1 term2" and term3.
You can use OR in conjunction with the site-search syntax. "The Incredible Hulk" site:rottentomatoes.com OR site:imdb.com will return results containing that phrase from both IMDb and Rotten Tomatoes.
If you're going to use parentheses, make sure you don't have any spaces between a parenthesis and a syntax keyword (OR/AND). Double up parens on the ends and don't include quotes. For instance, use ((foo)OR(bar)) rather than (foo) OR (bar). Likewise, use ((steve jobs)AND((iphone)OR(tablet))) rather than ("steve jobs") AND (iphone OR tablet). If you think you should use parentheses yourself, chances are there is a way to reformulate your query in a manner that makes them unnecessary.

Drop terms:

Use minus (-) before a word or phrase to have it not appear in results. Excluded words must be the last words in the search.

Safe search:

Add !safeoff to the end of your search to turn off safe search for that search.

Site search:

You can add site:domain to your search to restrict the results to a particular domain, e.g. contribute site:duck.co.
Click on the site icon at the bottom left of a result to do a site search for the domain related to that result. You can also do the same by clicking the More results link to the right of the URL line for a given result.
This feature also works with multiple domains, for example "The Incredible Hulk" site:rottentomatoes.com OR site:imdb.com.

Regional search:

Add region:cc (e.g. de) to boost a region.
Similarly you can do region:none to turn off a region if you have one set by default.
Use r: as a shorter abbreviation for region:.
Use site:.cc to restrict to a country level domain, e.g. site:.uk would only show results from domains ending in .uk.

Result filters:

Use inbody: (b: for short) to make sure something appears in the body of the page.
Use intitle: (t: for short) to make sure something appears in the title of the page.
Use filetype: (f: for short) to make sure the results are mostly files of that type, e.g. fdf.

Supported file types are: htm / html, pdf, txt, doc / docx, xls / xlsx and ppt / pptx.

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Bangs allow you to search on thousands of sites, directly.

A search for !amazon shoes will take you right to an Amazon search for shoes on Amazon.com. Try !a shoes or !ebay wallet. There are thousands of !bangs and you can even submit your own.

With our !bang autocomplete, it's even easier than ever to search directly on your favourite sites. Try it now!

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A new machine learning app for reporting on hate in America

Simon Rogers Data Editor Google News Lab

Aug 18, 2017

Hate crimes in America have historically been difficult to track since there is very little official data collected. What data does exist is incomplete and not very useful for reporters keen to learn more. This led ProPublica — with the support of the Google News Lab — to form Documenting Hate earlier this year, a collaborative reporting project that aims to create a national database for hate crimes by collecting and categorizing news stories related to hate crime attacks and abuses from across the country.

Now, with ProPublica, we are launching a new machine learning tool to help journalists covering hate news leverage this data in their reporting.

The Documenting Hate News Index — built by the Google News Lab, data visualization studio Pitch Interactive and ProPublica — takes a raw feed of Google News articles from the past six months and uses the Google Cloud Natural Language API to create a visual tool to help reporters find news happening across the country. It’s a constantly-updating snapshot of data from this year, one which is valuable as a starting point to reporting on this area of news.

The Documenting Hate project launched in response to the lack of national data on hate crimes. While the FBI is required by law to collect data about hate crimes, the data is incomplete because local jurisdictions aren't required to report incidents up to the federal government.

All of which underlines the value of the Documenting Hate Project, which is powered by a number of different news organisations and journalists who collect and verify reports of hate crimes and events. Documenting Hate is informed by both reports from members of the public and raw Google News data of stories from across the nation.

The new Index will help make this data easier to understand and visualize. It is one of the first visualisations to use machine learning to generate its content using the Google Natural Language API, which analyses text and extracts information about people, places, and events. In this case, it helps reporters by digging out locations, names and other useful data from the 3,000-plus news reports. The feed is updated every day, and goes back to February 2017.

The feed is generated from news articles that cover events suggestive of hate crime, bias or abuse — such as anti-semitic graffiti or local court reports about incidents. We’re also monitoring the feed to ensure that errant stories don’t slip in; i.e., searches for phrases that just include the word ‘hate’. (This hasn’t happened yet but we will continue to pay close attention.)

The Documenting Hate coalition of reporters has already covered a number of stories on this area, including an examination of white supremacy in Charlottesville, racist graffiti, aggression at a concert in Columbus, Ohio and the disturbing rise of hate incidents in schools.

Users of the app can filter the reports by searching for a keyword in the search box or by clicking on algorithmically-generated keywords. They can also see reports by date by clicking ‘calendar’.

The Hate News Index is available now and we will be developing it further over the next few months as we see how journalists use it day to day to unearth these stories of hate and help collate a national database to monitor.

The ProPublica-led coalition includes The Google News Lab, Univision News, the New York Times, WNYC, BuzzFeed News, First Draft, Meedan, New America Media, The Root, Latino USA, The Advocate, 100 Days in Appalachia and Ushahidi. The coalition is also working with civil-rights groups such as the Southern Poverty Law Center, and schools such as the University of Miami School of Communications.

As part of our mission to create new resources for the journalism community, we are also open-sourcing the data on our GitHub page — let us know what you do with it by emailing newslabtrends@google.com.

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