Surfacing forum posts in search results

Today, we introduced a new search feature that makes it easier for you to find forum posts or discussions related to what you're searching for. This new addition to Google search results applies to sites that tend to have a large number of posts on a specific topic. When several different discussions on a site are relevant to your query, we indent them under the primary result and include the date of each post.

So for instance, if you search for [getting from rome to florence] you will see, below the third result, a list of relevant discussions on various ways to get between these cities.


It's always nice to know what others are saying about the best ways to get around (by boat or train) and how recent those comments are — especially if it's your first time traveling to Italy.

We hope this feature gives you a deeper view into the relevant content available on sites throughout the web — even when that content spans multiple pages or discussions.
At the same time, the main search results are diverse as always — so if you can't pinpoint a useful comment there's a list of relevant sites there to help.

Posted by Johanna Wright, Director of Product Management and Devin Mullins, Software Engineer

Jump to the information you want right from the search snippets

For most search results, Google shows you a few lines of text to give you an idea of what the page is about — we call this a "search snippet." Recently, we've enhanced the search snippet with two new features that make it easier to find information buried deep within a page.

Normally, a search snippet shows how a page, as a whole, relates to a your query by excerpting content that appears near and around where your query terms show on the page. But what if only one section of the page is relevant to your search?

That's where these new features can help, by providing links within the snippet to relevant sections of the page, making it faster and easier to find what you're looking for. Imagine, for example, that we're researching trans fats and cholesterol, and their effects on the body. If we start with a generic query like [trans fats], Google returns several results with lots of information about trans fats in general, including this result from Wikipedia:

Now, included with the snippet are links to specific sections within the page, covering different subtopics of trans fats. Since we're particularly interested in what's healthy and what's not, "Nutritional guidelines" is probably where the most relevant information is. Clicking this link will take you directly to that section, midway down the page.

Now imagine we're particularly interested in learning about good cholesterol and what levels of it are healthy, so we try a more specific query, [good cholesterol level]. The top result is from the American Heart Association and has tons of information about cholesterol levels. The specific information about good (HDL) cholesterol, however, is contained in one section titled "Your HDL (good) cholesterol level"‎. Since the query was more specific, the snippet for this result now provides the option to "jump to" just this section of the website.


Clicking on "Jump to Your HDL (good) cholesterol level‎" takes you directly to the most relevant information on the page:


Clicking on the title of the snippet ("What Your Cholesterol Levels Mean") still takes you to the top of the page, as always.

If you're a webmaster and would like to have these links appear for your webpages, take a look at the Google Webmaster Central Blog for info on some of the things you can do. And in the meantime, we hope these enhancements help you find the information you're looking for faster.

Posted by Chris Kern, Snippets Team

Two new improvements to Google results pages

Today we're rolling out two new improvements to Google search. The first offers an expanded list of useful related searches and the second is the addition of longer search result descriptions -- both of which help guide users more effectively to the information they need.

More and better search refinements

Starting today, we're deploying a new technology that can better understand associations and concepts related to your search, and one of its first applications lets us offer you even more useful related searches (the terms found at the bottom, and sometimes at the top, of the search results page).

For example, if you search for [principles of physics], our algorithms understand that "angular momentum," "special relativity," "big bang" and "quantum mechanic" are related terms that could help you find what you need. Here's an example (click on the images in the post to view them larger):

Let's look at a couple of examples in other languages. In Russian, for the query [гадание на картах] (fortune-telling with cards), the algorithms find the related terms "таро" (tarot), "ленорман" (lenormand) and "тибетское гадание мо" (tibetan divination mo). In Italian, if you search for [surf alle canarie] (surf at the canary islands), we now offer suggestions based on the three most famous Canary Islands: "lanzarote," "gran canaria," and "fuerteventura":

We are now able to target more queries, more languages, and make our suggestions more relevant to what you actually need to know. Additionally, we're now offering refinements for longer queries — something that's usually a challenging task. You'll be able to see our new related searches starting today in 37 languages all around the world.

And speaking of long queries, that leads us to our next improvement...

Longer snippets

When you do a search on Google, each result we give you starts with a dark blue title and is followed by a few lines of text (what we call a "snippet"), which together give you an idea of what each page is about. To give more context, the snippet shows how the words of your query appear on the page by highlighting them in bold.

When you enter a longer query, with more than three words, regular-length snippets may not give you enough information and context. In these situations, we now increase the number of lines in the snippet to provide more information and show more of the words you typed in the context of the page. Below are a couple of examples.

Suppose you were looking for information about Earth's rotation around the sun, and specifically wanted to know about its tilt and distance from the sun. So you type all of that into Google: [earth's rotation axis tilt and distance from sun]. A normal-length snippet wouldn't be able to show you the context for all of those words, but with longer snippets you can be sure that the first result covers all those topics. In addition, the extra line of snippets for the third result shows the word "sun" in context, suggesting that the page doesn't talk about Earth's distance from the sun:

Similarly, if you're looking for a restaurant review that covers all the parts of the meal, longer snippets can help:

But don't just take our word for it — try it out yourself with your favorite long, detailed query.

These are just two recent examples of improvements we've made. We are constantly looking for ways to get you to the web page you want as quickly as possible. Even if you don't notice all of our changes, rest assured we're hard at work making sure you have the highest quality search experience possible.

Posted by Ori Allon, Technical Lead, Search Quality Team, and Ken Wilder, Snippets Team Engineer

Eye-tracking studies: more than meets the eye

Imagine that you need a refresher on how to tie a tie. So, you decide to type [how to tie a tie] into the Google search box. Which of these results would you choose?


Where did your eyes go first when you saw the results page? Did they go directly to the title of the first result? Did you first check the terms in boldface to see if the results really talk about tying a tie? Or maybe the images captured your attention and drew your eyes to them?

You might find it difficult to answer these questions. You probably did not pay attention to where you were looking on the page and you most likely only used a few seconds to visually scan the results. Our User Experience Research team has found that people evaluate the search results page so quickly that they make most of their decisions unconsciously. To help us get some insight into this split-second decision-making process, we use eye-tracking equipment in our usability labs. This lets us see how our study participants scan the search results page, and is the next best thing to actually being able to read their minds. Of course, eye-tracking does not really tell us what they are thinking, but it gives us a good idea of which parts of the page they are thinking about.

To see what the eye-tracking data we collect looks like, let's go back to the results page we got for the query [how to tie a tie]. The following video clip shows in real time how a participant in our study scanned the page. And yes, seriously — the video is in real time! That's how fast the eyes move when scanning a page. The larger the dot gets, the longer the users' eye pauses looking at that specific location.



Based on eye-tracking studies, we know that people tend to scan the search results in order. They start from the first result and continue down the list until they find a result they consider helpful and click it — or until they decide to refine their query. The heatmap below shows the activity of 34 usability study participants scanning a typical Google results page. The darker the pattern, the more time they spent looking at that part of the page. This pattern suggests that the order in which Google returned the results was successful; most users found what they were looking for among the first two results and they never needed to go further down the page.


When designing the user interface for Universal Search, the team wanted to incorporate thumbnail images to better represent certain kinds of results. For example, in the [how to tie a tie] example above, we have added thumbnails for Image and Video results. However, we were concerned that the thumbnail images might be distracting and disrupt the well-established order of result evaluation.

We ran a series of eye-tracking studies where we compared how users scan the search results pages with and without thumbnail images. Our studies showed that the thumbnails did not strongly affect the order of scanning the results and seemed to make it easier for the participants to find the result they wanted.

The thumbnail image seemed to make results with thumbnails easy to notice when the users wanted them (see screenshots below — page with the thumbnail image on the right)...

Click the images to  view them larger.

...and the thumbnails also seemed to make it easy for people to skip over the results with thumbnails when those results were not relevant to their search (page with the thumbnail on the right).

For the Universal Search team, this was a successful outcome. It showed that we had managed to design a subtle user interface that gives people helpful information without getting in the way of their primary task: finding relevant information.

In addition to search research, we also use eye-tracking to study the usability of other products, such as Google News and Image Search. For these products, eye-tracking helps us answer questions, such as "Is the 'Top Stories' link discoverable on the left of the Google News page?" or "How do the users typically scan the image results — in rows, in columns or in some other way?"

Eye-tracking gives us valuable information about our users' focus of attention — information that would be very hard to come by any other way and that we can use to improve the design of our products. However, in our ongoing quest to make our products more useful, usable, and enjoyable, we always complement our eye-tracking studies with other methods, such as interviews, field studies and live experiments.

Posted by Anne Aula and Kerry Rodden, User Experience Researchers

Our international approach to search

In previous posts in this series, you have read about the challenges of building a world-class search engine. Our goal is to make Google’s search be relevant to all people, regardless of their language or country. As my colleague Amit Singhal described, we use statistical data as the basis for making sweeping algorithmic changes. Many of these changes can be rolled out across all languages we support, but in some cases the unique characteristics of each language require some algorithmic considerations and tuning. And to make things really interesting, there are cases where the same language is different across countries. Obvious examples are "color" in the U.S. vs. "colour" in the U.K., or "camião" in Portugal vs. "caminhão" in Brazil.

My name is Daphne Dembo, and my focus is improving Google's international search. This is a tough challenge, since Google search is used in many countries and languages where our engineers have little personal knowledge. Initially, the international search improvements were done by Search Quality engineers who were passionate about their languages and countries: Lina from Sweden improved our parsing of compound words in German and Swedish; Dimitra from Greece introduced diacritical support; Ishai from Israel worked on transliteration corrections for Hebrew and Arabic; Trystan from Australia created methods for identifying local search results and ranking them together with foreign ones from the same language; Alex, a bilingual Ukrainian and Russian, introduced morphological understanding of these languages. As the importance of our international search grew, we solicited help from Googlers in all our offices. Finally, we are leveraging an international network of search specialists who help us understand search within the unique combination of their language and country.

Our first step in providing search support for a language is to train our language model on a large collection of documents in that language. This ensures that our language model is more precise and comprehensive — for example, it incorporates names, idioms, colloquial usage, and newly coined words not often found in static dictionaries. For instance, we recently started identifying Swahili, and used pages such as this one for the Parliament of Tanzania to train our system with the language's nuances. Having a trained language model helps to categorize documents during crawling and indexing of the web and to parse the user's query. Once this stage was complete, we launched Swahili search in countries such as Tanzania and Kenya, enabling local searches for the "Dar es Salaam stock exchange" [Soko la hisa dar es salaam], and "cure for Malaria" [Tiba ya malaria]. (As always, we are using square brackets to denote a search query. For example, you can search for "soccer" in Hamburg, Germany by clicking on [fußball in hamburg]).

We learn some things from our users, so as people start using our search engine, we can improve the way we rank in that language. Here are few examples:

• Spell corrections: We recently launched spell corrections in Estonian. If your Estonian is rusty, and you don't remember how to spell "smoke detector," we can suggest a spell correction for [suitsuantur], leading to better search results.
• Diacritical marks: Many languages have diacritical marks, which alter pronunciation. Our algorithms are built to support them, and even help users who mis-type or completely ignore them. For example, if you're a resident of Quebec, Canada and would like to know the weather forecast in Quebec City, we'll serve good results whether you type with diacritical signs [Météo à Québec] or without [meteo quebec]. Czech users can read the same excellent results for a popular kids' cartoon by searching for [krtecek] and [krteček]. On the other hand, sometimes diacriticals change the meaning of the word and we have to use them correctly. For example, in Thai, [ข้าว] is "rice," with completely different results than [ข่าว], which is "news"; or in Slovakia, results for "child" [dieťa] are different than results for "diet" [diéta].
• Synonyms: A general case of diacritical support is the handling of synonyms in different languages. Korean searches showed that "samsung" can be viewed as a synonym of "삼성", so that when users search for [samsung], they find results which have the company's name in Korean.
• Compounding: Some languages allow compounding, which is the formation of new words by combining together existing words. You can see a nice example in Swedish, where we return documents about a Swedish credit card for both compounded [Visakort] and non-compounded [visa kort] queries.
• Stemming: Google has developed morphological models that can receive compound words as queries, and return pages which contain their stem, possibly as part of a different compound. For example, when searching for cars in Saudi Arabia, you can search for [سيارة] and [سيارات] because both are variants of the same stem, and both return many common results. A Polish user can search for "movie" [film], and get back results that contain other variants of the stem, such as "filmów," "filmu," "filmie," "filmy." A user from Belarus will find results for all word forms of the capital, Minsk [Мінск]: "Мінску," "Мінска," "Мінскага."

In addition to these semantic factors, Google does even more to parse documents and queries. Understanding the details of language usage in a country is important. Notation of acronyms is different across languages: In Hebrew it is double quotes before the last (left-most) character, as in "prime minister" [רה"מ]; in Thai — a dot at the end of the word, as in police station [สน. ]; while in the U.S. — dots after each character, as in [I.B.M.]. Chinese users quote works of art with a "《", as in: [《手机》剧情], and denote dates with a "日", as in: [2006年1月13日].

Beyond the linguistic elements of a language, we consider how people enter a query. For example, some languages that do not have Latin scripts require keyboards with dual alphanumeric keys. The user can switch between language input modes by typing special keystrokes. In case the user forgets to type this sequence, the queries end up being gibberish. You can see correct handling of these mistakes in Arabic ([hgsuv] corrected to [السعر]) and ([حقثسهيثىفهشم ثممثؤفهخىس ] corrected to [presidential elections]), Hebrew ([vdrk, kuyu] corrected to [הגרלת לוטו]), and Cyrillic ([rehc ljkffhf] corrected to [курс доллара]).

Another way of avoiding the inconvenience of switching keyboard modes is by typing the phonetic sounds of the query in Latin characters. Recreating the correct query in the target language isn't trivial, since there might be many possibilities. We can see several such examples in which we suggest the same query in the intended language for Russian ([biskvitnyi rulet] to [бисквитный рулет]), "movies" in Chinese ([dianying] to [电影]), and "Bank of Attica" in Greek [trapeza attikhs] returns good results for "Τράπεζα Αττικής". Users of 8 Indic languages (such as Hindi, Gujarati, Telugu) can type the phonetic sound of the query, and choose the words in Hindi script:


Ease of typing and reading is also influenced by the language used. Since every Chinese word requires several keystrokes on a standard keyboard, we provide category browsing by Images and related searches so that people don't need to type as much. Similarly, we are now launching Google Suggest, or real-time completion of queries, in many languages.

So far I described how we improve the quality of search in a language. However, there is a strong effect of the location of the user, even if it is only approximated to the country, since in many cases local content is more relevant than global information. For example, searching for Spanish Yellow Pages [Páginas Amarillas] will result in several documents of global interest and several local results in Peru, Mexico, and Spain. Similar to that, searching for [Côte d'Or] in France will return results for that region, whereas searches in Belgium will return results about the chocolate maker.

Note that the display of information should conform to the standards in that country, so we display "," as a decimal notation for Croatian users who want to know how many millimeters are in an inch [inč u milimetrima], or for Italian users who are interested in currency exchange rates [50 euro in dollari]. Similarly, temperatures in Norway [Været i Oslo] will be displayed in Celsius, while in the U.S. — in Fahrenheit [weather Boston].

If everything else fails, we provide cross-language translations based upon Google's translation technology described in this blog post. We will translate your query to English, search English documents on the web, and translate the returned results from English back into the original query language. For example, Japanese users who are interested in viewing Halloween illustrations (Halloween is a holiday which originated in Ireland) can search for [ハロウィン イラスト]. You can then request a Japanese translation of the English pages (at the bottom of the page), which will bring up the translation page in the screenshot below. Similarly, Korean users can search for the latest on Harry Potter [해리 포터], and Arabic readers can search for the opening of the Sydney Opera house [افتتاح دار الاوبرا في سيدني]. (Click on the image to see a larger version.)



All in all, Google Search is being actively developed for more than 100 languages, in 150+ countries, with dozens of improvements launched each month. So far I've covered the basics of how international search works, but this is just the surface of all the international work we do. There are many other interesting topics that impact international markets like usability, homepage and results page layout, and connectivity. An understanding of real cultural and human factors is essential to creating a search engine that resonates with the people who use it. (Click on the image to see a larger version.)



(Update: Replaced example in the 4th bullet point.)

Posted by Daphne Dembo, Engineering Director

The art of the field study

I'm Dan Russell, a member of the Search Quality team doing user experience research. This post is part of our ongoing series to talk about the Search Quality team at Google, showing a bit of what we do in the day-to-day course of improving the quality of the user experience.

The role of "user experience" research is to try and get the inside story on what people do when they search. We're constantly asking: What's the user's experience of search? What works and doesn't work for them? What are they looking for? What DO they want?

To understand the full richness and variety of what people do when they are using Google, we spend many hours in the field, watching people search and listening to what they say as they do this. We hear it when they're happy, and when they're terribly frustrated. And perhaps most importantly, we also pay attention to the things they don't say -- the inexpressible "gotchas" that slow users down or get in the way of their search.

It turns out that people are masters of saying one thing and doing another, particularly when it comes to nearly automatic behavior. We find that searchers often turn so quickly to Google that they don't really think too much about what they're actually searching for. It's surprising, but often we'll see people trying to find out something about a topic, but then never actually mention the topic itself. That is, there's often a big discrepancy between what they'll tell me (the human observer) they're trying to do, and the search terms they enter into Google. One person I shadowed for the day spent ten minutes trying to find the schedule of the ferry that runs between San Francisco and Larkspur, but somehow only thought of adding the word "ferry" much later in their search.

We also study eye tracking. The eye makes a complex scan path over the search results, building up a composite picture of what is presented on the page. It's clear that what actually happens is a very rapid scan and assessment of each result as they are seen. In those milliseconds between the eye landing on the first fixation and seeing a few results, all kinds of decisions and choices are made--nearly all of them subconsciously.

In this short video, you can see three different searchers all looking for the same thing (in this case, a child's backpack). The red dot is the searcher's gaze moving around on the search results page. Notice how methodically the gaze moves from result title to title, occasionally inspecting the snippet text to gain more detail about the result.


(Video courtesy of Kerry Rodden)

So the job of figuring out what people actually do when they search isn't as simple as asking someone what they search for during the day. It's basically impossible to give an accurate telling of what you saw (or didn't see) on the results page while actively searching for a high quality results.

Memories of your own behavior are also notoriously unreliable. People's search behavior in the lab is often different than when they're at home or at work. This is a natural (and expected) side effect of lab studies: people will work especially hard to please a researcher. If we ask them to search for a pair of brown shoes they'd like to buy for themselves, in the lab they'll find the first pair that seems reasonable and then stop, satisfied. If it was real, they would go on and spend more time. We still do lab studies, but we know what to watch for, and what to ignore.

Data from field studies gives us insight into how people respond to the Google experience in ways that we can't otherwise measure.

For instance, in several field studies we discovered that many of the people who went to the previous version of the Advanced Search page had a strong, almost visceral negative reaction when the page appeared. The text of the original page had language that many people saw as intimidating--words like "Domain," "Usage Rights" and "Safe Search" can be a bit much if you're not sure what they mean.

The old Advanced Search page was a little off-putting (click on the image to see a larger version):


Based on our field studies, we dug more deeply into how people were actually using our Advanced Search page, and quickly discovered that, indeed, a large number of users were going to the page, and then leaving it without ever filling in any of the slots.

Armed with this insight from field studies, we redesigned the page, simplifying it by removing terms that were unclear to the average user (the word "occurrences," for example, just didn't mean anything to many of the Advanced Search page users), moving rarely used features (numeric range searches, date searches, etc.) into a part of the page that was expandable with a single click. That made them easy to get to for people who knew they wanted to search with those restrictions, but out of the way in a non-threatening way.

One of the other things we noted in the field study was that people often didn't understand how the Advanced Search page worked. So we added a "visible query builder" region at the top of the page. As you fill in the blanks, the box at the top of the page fills in with the query that you could type into Google. It was our way of making visible the effects of advanced search operators.

The Advanced Search page post-redesign (click on the image to see a larger version):


The good effect of these changes quickly became clear. The number of users that bounced out of the Advanced Search page dropped significantly. Interestingly, the total number of Advanced Search page users didn't increase significantly... at least not yet. By improving the UI on the page, we hope to attract even more searchers to the large range of search options available on Google.

In the end, this example shows the kind of insights that field studies can bring. As with the eye-tracking example, asking someone about their emotional response to a web page just isn't a useful way to get that data. But watching them in situ, as they actually use Google to go about their daily search lives can reveal all kinds of remarkable, otherwise undiscoverable, and actionable insights into searcher behavior.

Posted by Daniel Russell, Uber Tech Lead, Search Quality