SEARCH
| Sergey Brin On "To Tell The Truth" Feb 18, 2008 - 08:31 Sergey Brin, Googles Co-Founder, On "To Tell The Truth" TV Game Show. The year 2000 |
Couple of years back, around this same time when Twitter was launched, most of the major search engines have started to think about the idea of 'real-time' results and include a 'freshness' factor to the results returned for some of the queries that are performed on their search engines. Twitter is both more and less than a search engine, but there are lots of third parties doing search-like things around the Twitter data. Especially because Twitter search seems to be returning real time search results.
Real Time Search Engines:
Real-time searches are more valuable because it lets you know what's happening right now on any given topic. Companies use it to handle customer services. News junkies use it to follow political events. With this increase in demand for real time searches many new real time search engines like collecta, crowdeye have been launched over the last few months.
This new generation of emerging search engines are ready to compete with the big boys to tap into the torrent of tweets, blog postings and online photos that can be captured by cell phones. Below are some of the real-time search engines that allow you to take a deep look as what's going right now.
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Collecta - scours the net for the most recent blog posts, news stories, tweets and comments and displays them in a continuous waterfall. It's a torrent of information to keep track of.
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Crowdeye - currently a twitter only search engine, it gives you results from tweets and retweets including graphs, charts and relevant third party links.
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OneRiot - is a bookmarking site for twitter. Users share tweets that contain URLs to web pages and this site keeps track and returns search results based on topics. This is a really great way to discover some new sites related to subjects and you can interact with the twitter shares right from the site by replying to or retweeting good stuff you find.
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Topsy - lots of stats when you search including the a collection of authors by volume for each topic you are trending. Really like this to find people who are very active around a topic or who are your best retweeters.
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Scoopler - aggregates and organizes content shared on the Internet instantaneously, similar to eye-witness reports of breaking news, with photos and videos from the events, and links to the hottest memes of the day. Indexing live updates from Twitter, Flickr, Digg and Delicious, they are able to surface some of the most relevant results, updated in real-time.
Users needs Realtime Searches
As the current trend on the web is towards more and more real-time information, the race is on to collect, organize, and filter the data so that people can actually may sense of it. Real-time search is one of the hottest mini Web trend out there right now, promising new ways to help users tease out current information they want from the digital information glut. The ability to seek out what everyone is discussing or looking for in the moment captures the imagination.
Even Google made its counter-move to real time search, by coming out with a new set of feature called 'Search Options', which gives users the option to filter out certain results and only see content that is only a particular number of days old, ie. 1 day, 1 week, 1 year. This has been clearly reflected from the words of Google's co-founder Larry Page:
"I have always thought we needed to index the web every second to allow real time search. At first, my team laughed and did not believe me. Now they know they have to do it. Not everybody needs sub-second indexing but people are getting pretty excited about realtime."
And as you all know when the news broke that Michael Jackson had died Twitter was able to deliver better relevant results. On the other hand, Google thought MJ died at age 65 in 2007 and sometimes later it was able to show only the "We are Sorry Page"!
Google Results showing Michael Jackson died at age 65
So I conclude saying that unless Google take actions on this real time search issues(which was at one time a laughable concept), it will be hard for them to with stand their position, so I hope soon Google will overcome this issue. And I can also sense the launches of more real time search engines in the future with this growing demand for it.
Update:
Hmmm not to much of my surprise, now the Microsoft's new release Bing also have joined the race for real time searches. Sources from Bing said as follows:
"There has been much discussion of real-time search and the premium on immediacy of data that has been created primarily by Twitter. We've been watching this phenomenon with great interest, and listening carefully to what consumers really want in this space. Today we're unveiling an initial foray into integrating more real time data into our search results, starting with some of the more prominent and prolific Twitterers from a variety of spheres. This includes Tweets from folks from our own search technology and business sphere like Danny Sullivan or Kara Swisher as well as those from spheres of more general consumer appeal like Al Gore or Ryan Seacrest.
Starting later today, when you search for these folks names in association with Twitter, you'll see their latest Tweets come up in real time on Bing's search results. For example, if you type "Kara Swisher Twitter" or "Kara Swisher Tweets" or even "@karaswisher" as your search query, you'll see something like the below. (Note this feature will be rolling out gradually over the course of the next few hours so you may not see it right away.)"
Yesterday, our CEO sent me an article from Lifehacker that announced a new Google experiment, the Google Wonder Wheel. The experiment didn't actually work on my desktop but the video on YouTube demonstrated the capabilities. It's just like a mind map that allows you to drill down into deeper search results. The future is getting cooler, right?

I like how wonderwheel is starting to make search not only more 'fun but also more connected.'
Microsoft Decides It Has No Answer For The Answers Market
By Joseph Tartakoff - Mon 11 May 2009 01:59 PM PST
MSN QnA, Microsoft's rival to Yahoo Answers, is shutting down. A spokeswoman says MSN QnA is being closed "as part of our overall investment in updating and re-aligning our online services to provide customers with new ways to share their opinions and ideas." It's the latest MSN-branded service to be cut. Microsoft (NSDQ: MSFT) announced it was closing its MSN Encarta site in late March. But as recently as mid-February, Microsoft still seemed dedicated to the QnA service, rebranding it as MSN QnA from Live QnA and moving into the MSN organization.
The answers market has been tough for big companies to break into, with the notable exception of Yahoo (NSDQ: YHOO). Microsoft launched QnA in August 2006, four months before Google (NSDQ: GOOG) decided to shut down Google Answers, which charged users to have their questions answered. In its three years in existence, Microsoft's QnA appears to have attracted about 3 million questions. Yahoo Answers measures itself not by questions but by answers-it has attracted more than 750 million answers-but it's clear that Yahoo is far more popular. LiveSide first reported the news Monday.
What if the ads we saw when watching TV were always just what we wanted to see? Well, we believe it is possible to make TV ads more relevant to viewers and to deliver more value to advertisers. http://googleblog.blogspot.com/2009/05/tuning-in-to-tv-data.html
Television is becoming more like the web. Just as users click with their mouse to choose what's most relevant to them on the web, viewers send signals about what they want to see on television with clicks of the remote control.
Each week, Google analyzes data from millions of anonymized set-top boxes (STBs) to see which channels they were tuned to second by second. This data is provided by our partner, EchoStar. We're then able to use tuning metrics to provide our advertisers with next-day reports of how many televisions showed their ads nationwide and how the audience responded with their remotes.
We look at the various tuning metrics as signals from the audience about what they want to see and when. One of the metrics we've been exploring is the % Initial Audience Retained (%IAR). This is the percentage of the audience that was present at the beginning of the ad and then stayed tuned-in through the entire ad. If most viewers see an ad they like and decide to stay tuned-in, that ad would have a high %IAR.
Many factors affect audience behavior, including the nature of the programming, the time of day, the day of week, and, of course, the personality of each viewer. But ads themselves also have an impact. By identifying which factors affect tune-away, we can focus in on how the audience reacted to the ad itself.
Check out this video to learn what we found:
The chart below shows all TV commercials that aired on the Google TV Ads platform August through November 2008. Each dot represents an ad, and they are lined up from left to right in order of their %IAR as compared to what we'd expect given other factors (e.g., time of day, network, etc). The red dots on the left represent ads where more audience tuned away than expected. The green dots on the right represent ads where more of the audience stayed tuned than expected. The black dots in the middle are "normal," meaning there was no significant difference between the audience retention for those ads versus what you would expect based on historical data.

The next question we wanted to answer was how well this historical data could predict the future audience reaction. If we can use the past to predict the future, then we can get closer to putting relevant ads in front of TV viewers. So we selected one ad with relatively high audience tune-away (red dot) and one ad with relatively low tune-away (green dot) to run side-by-side on national television to test our findings. In the graph below, the diagonal line shows where audiences reacted the same to both ads. The points above that line represent airings when more of the audience stayed tuned to the ad that had previously retained audiences better. We learned audiences reacted predictably to the two ads.

Through our analysis of tuning data from millions of set-top boxes, we're getting closer to matching the right ads to the right television audience. It takes a lot of processing power to make sense of the enormous amount of data, but the insights to be gleaned are very powerful. Not only are we able to offer advertisers better measurement and more accountability for their TV campaigns, our goal is to also create a better viewing experience for TV audiences by showing viewers what they want to see.
Aardvark is a neat new service that lives in your IM client and which routes any question you might have to an Aardvark user who has the right expertise to answer your query. In return, Aardvark will also send you a few questions every day that fit your profile. You then decide to either answer the question or refer it to another friend. Of course, you can also always pass if you don't know the answer.
Aardvark will come out of its private beta during SXSW, but we have a few invites for you if you want to try it out now.
Aardvark was developed by The Mechanical Zoo, a San Francisco-based company that raised $5.25 million from August Capital and Baseline Ventures last October.
When you sign up with Aardvark, you simply add some basic information about your location, the topics you want to answer questions about, and your preferred IM client. Aaardvark supports Google Talk, AIM, and Microsoft's Live Messenger. After this, Aardvark will live in your IM client and you simply ask it whatever question you might have in plain English.

Aardvark analyzes your questions, determines what they are about, and then passes them on to the people in your Aardvark network - or, if nobody in your direct network fits the bill, it will pass it on to the rest of the Aardvark community.
Q&A
In our tests, this worked surprisingly well. We did, for example, ask Aardvark about what parties to go to at SXSW and received an answer within a few minutes. When we asked for local clothing stores in Portland, OR, a good answer came in even faster. We even got some good book recommendations through Aardvark.
Aaardvark features a number of simple commands that allow you to interact with the service and that are always explained in your conversations with Aardvark. When you get an answer, for example, you can simply type 'thanks' to send a thank-you note, or, whenever you feel like answering questions, just type in 'try' and Aardvark will look for a question that fits your expertise.
Better Than Twitter?
In our internal tests, we realized that a lot of the answers often rivaled those we received when asking our Twitter network. Thanks to the fact that Aardvark automatically routed our questions to people with the right expertise, all the answers we received so far were top-notch. In case you didn't like the answer (or if it was obscene), you can flag it and rate it on the service's website.
Overall, we think this is a great service and it is definitely one of the coolest products in this space that we have tested in the last couple of months.
Invites
Aardvark is scheduled to launch during SXSW, but we will send out an invite to the first 25 commenters on this post. Note: if you use your Facebook Connect or OpenID credentials to comment here, we won't see your email address!
(1) BeatMyPrice - Community powered price comparison site that helps you find the best price on products. You enter product details, price and the URL where you found the item. If someone finds the same item for less, you are offered the result, otherwise your link is saved as the cheapest one. Read more: BeatMyPrice - Find the Best Price Online.
- Find the best price you can online
- Visit beatmyprice.com
- Enter the details
- See if someone has found it cheaper elsewhere
- Save! (otherwise your price becomes the one to beat)
(2) Blist - Create comprehensive lists, be it a simple personal list or an advanced database. You could embed things like images, pdf files, word docs right beside a name in a spreadsheet etc. Read more: Blist - Create And Share Comprehensive Lists On The Web.
When reviews first started showing up in the local segment there was a debate about whether they would alienate advertisers and whether they were optional or mandatory from a consumer standpoint. Over the course of the past three years that question has been answered many times: yes they're mandatory and yes they're challenging from an advertiser POV (though most SMBs have a positive view of reviews).
Here's relevant online consumer data that Nielsen put out in December (n=1,000):
- 81% of online shoppers have read product or retailer reviews by other customers when doing their holiday shopping this year
- 71% agree that consumer reviews make them more comfortable that they are buying the right product
- 63% of online shoppers indicated that it was important to have multiple reviews for each product
- 14 % looked for reviews from an established source
- 3% sought out reviews by people they knew personally
Here are some of the charts (all Nielsen created):




Note in Table 3 that people are doing price comparisons and inventory checks to the extent they can before visiting the store. And 12% said they ordered online and picked up in store (see Krillion, NearbyNow).
Also, in Table 4 note the role of trust/brand in the decision of which sites to visit (direct navigation). Search followed probably after a generic product search (e.g., "All Clad 14 inch pan").
The most innovative, entrepreneurial minds in journalism have focused their efforts on collaboration
Will Algorithms Make Human Editors Obselete? Not If Journalists Collaborate
That's the brilliance of Google - it's actually driven by human judgment, by the judgment that someone producing a website makes every time they link to something. Rather than replacing human judgment, Google is actually co-opting it. But Google isn't co-opting the judgment of most journalists and news orgs - because so many of them still don't link to anything. (Notable exceptions notwithstanding.)
From ReadWriteWeb
Mahalo popularized the term "human powered search" when they launched just over a year ago. Many of the pitches we get still use that term as part of their positioning. Many of them are bootstrapped, so the price of entry is clearly low. But the upside has not yet been established. In this post we look at the pros and cons of human powered search engines in general, look at some differentiating strategies and ask "what is the future for Human Powered Search?"
Old Wine In New Bottles?
When Mahalo first launched, my instinctive reaction (which I recorded on my personal Blog) was that this was "old wine in new bottles". Traditional publishers have been doing "human powered search" even BI (Before Internet) but these went by boring names like Directory. Human editors work great in well defined niches, always have done and always will. Human editors produce the expert content that Google finds for you. This is long tail publishing. This is Business Media and Enthusiast Media, large but slow growth traditional publishing segments of the media industry.
But an Internet scale venture powered by humans rather than software? We look at three reasons why this might work and two reasons why it won't work.
Three Pros And Two Cons
Most ventures in this space highlight three things that a human editor can always do better than a software program. These are the three Pros:
1. Spam control. Humans can easily spot even the most ingenious spam .
2. Duplicate control. 10 articles that all say virtually the same thing are just a waste of time.
3. Disambiguation. Computers need an awful lot of expensive programming to always spot the difference between "apple" as a fruit, a consumer electronics company or a record label. Humans can do it in a flash.
The two Cons:
1. You cannot persuade people to break their Google habit until your searches are better than Google for most cases (not just the few cases where you specialize). This massive hurdle is true for all search engines.
2. You cannot win as a destination site if you are general purpose. You go to the sites that specialize in the areas that interest you. If you don't know what sites to go to, Google will find those sites for you.
So, do three Pros beat two Cons? Not in this case. The Pros are three relatively minor irritants that human powered search fixes. The Cons are total showstoppers.
Pay People To Write Content?
Mahalo pays people to create content. That means they can predict the quality of the results. Paying people requires lots of funding. Mahalo has plenty of funding and it is unlikely anybody else will get funded with the same model. So Mahalo has a fairly long and clear runway before take-off. Mahalo is private company so we don't know how long it will take them to get to profitability or even if the basic economics make profitability feasible at all. In today's climate, nobody will buy Mahalo without a clear path to profitability.
Are you Bullish or Bearish on Mahalo? Cast your vote in our Company Index (powered by TradeVibes). My vote was Bearish and I was in the majority at the time I cast my vote (80% Bullish vs 20% Bearish). The sample size on that vote was too low to be meaningful (40), so the more votes the better.
The Elephant In The Community Generated Content Room
Most other ventures get "the community" to create the content. The elephant in this room is of course Wikipedia. How on earth do you get general knowledge content that is better at scale than Wikipedia? How do you motivate people to create content if, unlike Mahalo, you are not paying their salaries? Google's answer with Knol was to pay them indirectly via Adsense revenue. The market jury on Knol is still out. If Google cannot win, how can any other start-up without their brand power? If the Knol competitor also monetizes through Adsense, their margin is even less.
About The Players
The other well funded venture that wears the human powered search label is Wikia. Founded by Jimmy Wales of Wikipedia fame, this looks like the largest pure Wiki style venture. Content is community generated, but it appears that they have editors/moderators/curators on payroll.
Squidoo looks like a bootstrapped venture. It is hard to tell if it has traction. Looking at Squidoo's page on TradeVibes will point to many other inexpensive Wiki style ventures. The basic technology of Wikis is now a total commodity.
One of the earliest ventures, About.com, is now owned by the New York Times. On my survey of one, About is the one site other than Wikipedia that surfaces a lot in general knowledge type searches. At the scale they operate, it may well be profitable. So Mahalo, Wiki and other human powered search engines may have a bright future.
What do you think? Can general purpose human powered search engines scale and make money? Or will they either fail or move into small niches? What new ventures have a fundamentally differentiated approach to this market?
Social software is proliferating online, but many of the most common Internet tools, such as search engines, are still used in isolation. "These tools are designed for a single person, working alone by him or herself, but that's not always the way that we work," says Meredith Morris, a researcher in the Adaptive Systems and Interaction group at Microsoft Research. People planning travel with their spouses, she says, or students working on research projects with classmates all too often find themselves repeating work others have done or fail to find sites that others have identified. Morris is designing a tool that could begin to help with this problem.
Called SearchTogether, the tool is meant to help groups whose members are working on different computers, whether they're all logged in simultaneously or one at a time. The tool is a plug-in for Internet Explorer 7 and requires a Windows Live ID to use. Once all the users have the tool installed, Morris explains, if one of them wants to initiate a Web search, she can invite the others to join her. The tool tracks the work done by the group, making it easier for the initiator to assign tasks and for group members to keep track of what they've done.
Before designing the tool, Morris conducted a survey to find out what problems plagued people trying to search as a group online. Among the problems she identified were redundant effort and inefficient communication about results.
SearchTogether is designed to reduce these problems by storing all the queries group members have entered, Morris says, and by tracking comments they make about the pages they find. The search initiator can also use the tool to divide work among group members. For example, the initiator could send half of the top 25 results of a query to one user and half to another. The users can then investigate the results without duplicating each other's efforts. If the search becomes relevant to someone else in the future--for example, if a family member wants to take the same trip that a group previously planned--new users can be invited to the project, where they see the stored queries and comments.
If users are searching simultaneously, they can use SearchTogether's "peek and follow" feature to view the pages others are looking at and to write each other instant messages as they explore the results of their queries.
Morris says that she's interested in adding features that could give users more-sophisticated sorting capabilities. For example, if a doctor and a layperson are searching together for information about a health problem, the tool might automatically send all highly technical results to the doctor.
Madhu Reddy, an assistant professor of information services and technology at Pennsylvania State University, says that in his studies of collaborative information seeking, he's observed that the search problems Morris has identified are very common. Many groups struggle to split up search tasks effectively, to keep all their members aware of what the others are doing, and to bring their results together at the end. A particular challenge, Reddy says, is that a lot of group interactions in the real world are gesture based. A good collaborative search tool, he says, would compensate for the loss of gesture--when, for example, a group member wanted to point out a single item on a Web page. Reddy also sees a need for tools that allow users to tap into others' expertise in navigating different pockets of online information.
Reddy says that one factor to take into consideration is "that we really don't know how people collaborate; we're still starting to develop the empirical research." He says that tools will need to be designed to support different types of searches. "You can envision anonymous users working together across continents," he says, "which is very different from teams working together in organizations to solve problems." Morris's tool, Reddy says, seems well-suited to general users working together over a distance. Reddy's own team is also developing a multiuser search engine.
Morris's interest in collaborative search extends beyond SearchTogether. She has also worked on designing a tool that helps multiple users of the same computer search as a team. An early version of SearchTogether will be released this spring.
Copyright Technology Review 2008.
I love the title of this post. This is where I got it:
http://www.scribemedia.org/2008/08/13/is-bigger-better-not-in-a-digital-...
Big companies talk the talk when it comes to adapting to the digital age. But do they walk the talk? It's difficult to reconcile their desire to be nimbler - and more responsive to their customers - with the fact that at big companies budgets are generally scheduled a year in advance.
What's more, when consumers are increasingly driving the dialogue online about products and services it may be problematic for big companies to be part of the conversation when they deploy a top-down strategy. Athur Ceria, founder and chief creative officer of CreativeFeed Network, says these sorts of business practices are fast becoming antiquated and may be deterring large enterprises from capitalizing on digital technologies.
Ceria has blogged about the need for big companies to think small if they want success in the digital world. He stresses that, for many large companies, process has started to infringe on creativity.
Big companies grappling with the Internet need to embrace a "sense of discovery," said Ceria, who has worked with Cisco, Intel and Yahoo, among other major brands. A sense of mission and a sense of awareness are also crucial if big companies want to take advantage of the Web. I recently spoke with Ceria about why bigger is not better in the digital age - and how large enterprises need to change if they want to stay in the game.
I also chatted with Ceria about trends in Web design. Ceria, who has an MFA from Yale University with a focus on graphic design, says far too many companies still treat their Web sites like a "brochure," rather than a living, breathing "organism" that is part of the company's DNA.
Enjoy.
I would speculate that there's so much information out there that no other organizational tool can manage the volumes of content that people online "consume." Search has become an essential utility for almost all internet users.
Pew: Daily Search Usage Approaching Email Levels
According to a new report from The Pew Internet & American Life Project, daily use of search engines is growing and starting to approach email usage levels. New research conducted by telephone among 2,251 US adults, age 18 and older, found that 49 percent of internet users use a search engine on a typical day, compared with 60 percent for email.
In 2002, Pew's data showed that about 30 percent of people online used search daily.
What about sites like www.chacha.com ? Interesting that he didn't include these in this article.
ToAnswer: Twitter Meets Yahoo Answers
Erick Schonfeld from Techchrunch
One of the ways people use Twitter is to ask a question to a large group of people at once: "Does anyone know a good recipe for Lobster Bisque?" "What are the best games for a four-year-old's pirate birthday party?" "What is the best tech conference to attend this year?"
Whether or not you get a good answer depends on how many people are following you and how smart they are. It's not like Yahoo Answers where there are millions of people coming to look for and answer each other's questions. But what if you could combine the two: ask questions via Twitter and find answers via a dedicated Website?
That's what ToAnswer
is. It's the project of Chuck Harmston, a lone Web designer in Mesa, Arizona. (So try not to pound on it too much). You ask questions by sending a Tweet to @toask, and then anyone can answer the questions on the site. Now, if only the service would Twitter you back every time somebody offers an answer, then I'd be impressed.
A post on TechCrunch yesterday suggested ChaCha was cutting the pay rate of its human guides to save costs as a prelude to "implosion." When I had last spoken to ChaCha the company had presented a very different picture so I decided to investigate and contacted co-founder Brad Bostic.
Some of the stats below are impressive... (CLICK HERE TO READ THE ENTIRE POST).
Here's a range of information that www.ChaCha.com provided to me:
* Millions of queries per month
* 90% month on month query growth from Jan-June
* Over 10,000 new users per day
* Over 25,000 guides in the system Advertising:
* Early advertising trials showed 5.2% conversion rates in mobile
* ChaCha also said that Nielsen Mobile found that Google SMS has approximately 37 million queries per month. This was achieved over a period of several years
* ChaCha's "mobile answers" service launched in January this year and the company said it expects to hit 30 million queries by December, this year User profile:
* 53% are repeat users
* 83% say they consider mobile ChaCha to be "very valuable"
* Average usage now more than 30 times per month. Compare average mobile search volume is nine times per month
* 88% hear about the service from a friend
* Users are 18-34; use it socially and for utilitarian purposes
Drilling deeper: Niche 'vertical sites' refine Web searching
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Two years after Merriam-Webster formally recognized "google" as a transitive verb, consumers are recognizing the limitations of Google, Yahoo, Microsoft or Ask.com, whose "horizontal" searches deliver vast breadth of information but not much depth. Increasingly, people are "drilling down" into highly detailed and structured sites like Retrevo for consumer electronics; Trulia and Zillow for real estate; SimplyHired and Indeed for jobs; Kayak, Farechase and Farecast for travel, and so on... more |
You Get What You Pay For With Online Q & A Sites, Study Shows
ScienceDaily (Apr. 11, 2008) - A new study by University of Minnesota computer science and engineering researchers revealed that the answer quality provided by online question-and-answer Web sites, such as Yahoo! Answers and Google Answers, depends on two factors--how much you pay and how many people contribute to your answer.
See also:
The University of Minnesota study posed 126 questions across a variety of Q&A sites and found that paying $10 or more to get your question answered at the now-closed Google Answers site yielded the highest-quality answers as judged by a panel of evaluators. These answers were long and detailed, with many links to source material.
Surprisingly the Web site Yahoo! Answers, which provides answers for free, performed as well as Google Answers when the fee was low ($3) and outperformed reference librarians and an "ask-an-expert" site. Researchers attributed this success to the large online community that contributes to that site's answers.
University of Minnesota researchers involved in the study include computer science and engineering professor Joseph Konstan and graduate student Max Harper. Their study examined a variety of questions eliciting facts, opinions and advice on topics spanning entertainment, technology and business. Examples of some of the questions posted are:
- Which actress has the first female line in a talking movie" I found on Wikipedia that Al Jolson had the male line, but I can't find any record of which female had the first line.
- What is the best technique for making BBQ spare ribs" I'll cook it if you can find me a recipe that's really worth the time and effort.
Of the findings, Konstan said, "Solutions that simply direct questions to a single individual don't achieve results as well as those that open the question and answers to a larger community."
The results of the study are reported in the academic research paper titled "Predictors of Answer Quality in Online Q&A Sites." The paper was published in the Association for Computing Machinery's 2008 Conference on Human Factors in Computing Systems (CHI 2008) proceedings, and presented at the conference in Florence, Italy, April 8.
Dec. 18, 2006 at 11:13pm Eastern by Bill Slawski
Why Do People Google Google? Understanding User Data to Measure Searcher Intent
What are people looking for when they type "Google" into Google? What do they want to see when they use "eBay" as a query? How does a Google or Yahoo learn from their log files, and other user information? What does it tell them about user intent?
In an interview posted earlier today with Luke Wroblewski, Yahoo's Principal Designer for Social Media, we're told that the amount of user data that Yahoo has to work with while designing may be almost overwhelming. A point we haven't seen made much by the search engines, it's the second time today I've heard it. The first was during a presentation from Google senior research scientist Dan Russell.
Last Tuesday, Keri Morgret went to the December BayCHI, where Dan Russell spoke about How People Use Search Engines. She reports on some of her thoughts as well as some interesting observations about eye-tracking studies at Google. In her post, she includes a link to a video of an earlier version of the speech, How do Google searchers behave? Improving search by divining intent. The questions I started this post with are ones he asks in his presentation. He's one of the guys who tries to find answers to questions like that.
Dan Russell joined Google from the IBM Almaden Research Center, and also worked for Xerox PARC and Apple's Advanced Technology Group, as well as teaching at both Stanford and Santa Clara Universities. His homepage includes three sets of slides used during different versions of this presentation. The video weighs in at almost an hour-and-a-half, so if you want the shortened version, or want to read along, you may want to download one of those big PDF files.
The presentation is long, but it provides some nice glimpses into how Google works. I tried to find out when Dan Russell started working at Google when he give the presentation at Stanford linked to above, but it wasn't easy to locate a date. It wasn't long enough for him to not discuss some of the insights he had when he first started looking at searcher intent while at Google. His thoughts:
1. Intuitions are terrible when trying to figure out what people are searching for.
2. In particular, your intuitions are terrible.
3. That's why Google does studies.
4. Fallacy 1: "I do it this way" so others do, too.
5. Fallacy 2 "My Mom does it this way" so others do, too.
6. Deep truth: You are statistically insignificant.
7. Deeper truth: (As a computer scientist/student/audience member) you are a couple of sigma from the norm
8. So are your friends
Understanding User Behavior and Types of Queries
While Google focuses upon search as its core mission, we're told that the effort is of little use if we "can't understand what the question is." What are users looking for? That's true not only for organic search, but also for things like images, Google Earth, print, and video, which don't have the benefit of pagerank and link structure to index. Most of these services are in beta, and they can get it wrong now. Applications can be changed on a very quick basis, or as Dan Russell calls it, rapid prototyping on a delivery model. Especially if they can look at the usage data of those services and somehow understand it.
An example is Google Video, which at first provided the most popular results, with snippets. But it wasn't getting the clickthroughs that they expected. So they quickly changed it to a richer display and the clickthroughs increased dramatically.
Another example was Google Maps - A couple of months after starting, the links were on the right side. After looking at log files, they decided to move them to the left, use a larger font, and add a tab for more details. They found that user behavior is influenced by small changes - and saw significantly differences in clickthrough rates for things like minor size changes in fonts. We're told that measuring millions of clickthroughs provides interesting results.
Another issue arises when making changes to something like Maps Local. Those changes need to be echoed in places like Maps Local for Mobile. Another challenge that they face is training a culture to use a new interface - smaller changes are easier to get people used to using them.
It's not unusual to see queries broken down into three different types, as described by Andrei Broder in his paper, A taxonomy of web search. We get to see some percentages, and a greater breakdown of query types in this presentation describing what people are searching for:
Navigational - 15 %
Transactional - 22%
- Obtain 8%
- Interact 6%
- Entertain 4%
- Download 4%
Informational - 63%
- List 3%
- Locate 24%
- Advice 2%
- Undirected 31%
- Directed 3%
Search Patterns
What patterns might emerge when people search?
We're told that it is usually a two step process:
1. Searchers find a good site, and;
2. Look for information there.
Another strategy is teleporting, or going directly to somewhere else.
The reasons for teleporting:
- Users don't realize they can search directly for the information
- Difficulties in formulating a query
- The user trusts the source that they are going to
Presumably, that two step process can be a good strategy if you know something about the resource, use its search engine if it has one, and understand the structure of that site. A video of a user session is shown at this point, illustrating someone exploring a site search, snippets, and the possibility of refining their query back at the search engine.
Information about Query Sessions
Instead of just looking at individual searches, considering user sessions are an important part of the analysis of searches.
How often do people do query reformation during a user session, and what do they do when they reform those queries?
1. Spell correct helps lots of people, and shortens their sessions.
2. People often make a minor change to a word, or add a word, which may not provide the best results (people often get stuck in inefficient queries, and don't change those much).
Some other things that they see:
1. The more words used in a query, the longer sessions tend to last. Their assumption here is that more sophisticated queries involve people spending more time searching.
2. People use longer sessions on weekends.
3. The longer the sessions, the more often they see multi-tasking (multiple search subjects in a session) and interruptions.
Advanced Searchers
Advanced searchers make up an extremely tiny fraction of the folks who search. Some of the characteristics of an advanced searcher are that they:
Have lots of meta-knowledge about content and sites
Take notes (on the machine, or paper, or bookmarks)
Try alternative word sequences
Use quotations correctly
While they may take advantage of these things, they don't do a lot of it.
The Challenges of Analysis of User Data
I started this post mentioning the problem of having an almost overwhelming amount of user data. Dan Russell shifts gears at this point of the presentation, and starts talking about how to analyze and reduce that data to manageable levels, so that instead of relying upon intuition, they are making meaningful use of the information.
There are two parts to meeting that challenge. The first is building a scalable data analysis system, where a portion of the data can be looked at, and parallel systems can be used to analyze the rest of the records. That type of analysis is described in a Google paper - Interpreting the Data: Parallel Analysis with Sawzall.
The second part of the analysis involves usability. The importance of field studies and lab-based usability tests of prototypes is covered in detail.
For instance, a user would perform a realistic task with a prototype, while thinking aloud. Researchers would watch to see:
- Where they have problems.
- Fail to complete a task, or take too long.
- Make an important mistake and don't realize it.
- Misunderstand an important part of the UI.
Efforts are made to avoid helping or influencing the user, and focusing upon their actions rather than their opinions. Eyetracking is often used in this type of testing.
Field Studies consisting of interviews at the places where people actually use their computers are conducted, as well as diary and ethnographic studies.
We're told that a large percentage of people who use search engines have very different mental images of how search engines work than people who work on search engines. An analogy used - someone opens the hood of your car, and points out a part, and asks you what it does. How likely are you to know?
The presentation describes a number of the issues they see when conducting field studies, and how they try to act upon them. The bigger issue here is how to take these types of studies and perform them in a manner which might be statistically significant. How useful might it be to get a greater sense of demographics involving different user segments and different cultures?
Some Questions and Conclusions
Some good questions that aren't necessarily answered from this presentation:
Is one click good? Better than two clicks?
Is no click better than one click - such as when the answer is provided in the snippet?
What's the best way to help searchers avoid distractions?
Should some diversity be mixed into results for breadth?
Why are SERPs so boring? Or are they?
How did a standard evolve across the major search engines in how search results pages look?
We're told that Google's focus in understanding how well they are doing in meeting searchers' intentions has transformed from a static IR-styled analysis of query results towards longer-run, session analysis of how users interact with the search engine. This approach involves incorporating data from many kinds of studies, and using many different approaches instead of looking at a single point of data.
They don't want to make decisions without lots of testing, they don't want to rely upon intuition, and upon a world view centered around Silicon Valley and Stanford.

text any question from your phone
and have it answered by real people (other Mosio members).
It's totally free and you can ask Mosio anything.
Mosio the mobile questions and answers service I wrote about last year has a really cool and useful new feature today called Twitter Answers. Mosio users simply need to befriend the Mosio Twitter bot, and ask it any questions using Twitter's direct messaging feature. Other users who have befriended the bot will get your question (syndicated from the bot), and up to four of them can directly reply to you.
While the entire thread is somewhat meaningless with Twitter's lack of message threading, hopping over to Mosio you can see the entire exchange in its correct order. Better yet, if any regular Mosio members are able to answer your question, those answers will be shared over to Twitter.
For Mosio users who want to avoid using their phone's keypad, there is some reprieve. Last month Mosio partnered with Jott to set up a voice-to-text system that lets people ask questions using a standard phone call. Jott will then convert their voice question over to text and post it to the service, while sending any replies back in the form of SMS messages. Other users are able to follow along on Mosio's main page, their phone, and now on Twitter.
I still think one of the best uses of Mosio is to help sort out bar bets or random questions while out and about. Mobile users with a data plan can turn to Google or some other search engine to find out what they're looking for, but services like Mosio, Fluther, and Yahoo Answers provide a human touch in many areas that search engines cannot.
On a side note, Mosio was at SF Beta last night showing this off, and they had by far the most inventive Web swag I've seen in a long time. Witness, the adhesive mustache. How can you not remember this?
Information Searches That Solve Problems http://www.pewinternet.org/PPF/r/231/report_display.asp
12/30/2007 | Leigh Estabrook Evans Witt Lee Rainie
There are several major findings in this report. One is this: For help with a variety of common problems, more people turn to the internet than consult experts or family members to provide information and resources.
Another key insight is that members of Gen Y are the leading users of libraries for help solving problems and in more general patronage.
In a national phone survey, respondents were asked whether they had encountered 10 possible problems in the previous two years, all of which had a potential connection to the government or government-provided information. Those who had dealt with the problems were asked where they went for help and the internet topped the list:
- 58% of those who had recently experienced one of those problems said they used the internet (at home, work, a public library or some other place) to get help.
- 53% said they turned to professionals such as doctors, lawyers or financial experts.
- 45% said they sought out friends and family members for advice and help.
- 36% said they consulted newspapers and magazines.
- 34% said they directly contacted a government office or agency.
- 16% said they consulted television and radio.
- 13% said they went to the public library.
The survey results challenge the assumption that libraries are losing relevance in the internet age. Libraries drew visits by more than half of Americans (53%) in the past year for all kinds of purposes, not just the problems mentioned in this survey. And it was the young adults in tech-loving Generation Y (age 18-30) who led the pack. Compared to their elders, Gen Y members were the most likely to use libraries for problem-solving information and in general patronage for any purpose.
Furthermore, it is young adults who are the most likely to say they will use libraries in the future when they encounter problems: 40% of Gen Y said they would do that, compared with 20% of those above age 30 who say they would go to a library.
This report is the fruit of a partnership of the University of Illinois -Urbana-Champaign and the Pew Internet & American Life Project. It was funded with a grant from the federal Institute of Museum and Library Services, an agency that is the primary source of federal support for the nation's 122,000 libraries and 17,500 museums.
The focus of the survey was how Americans address common problems that might be linked to government. The problems covered in the survey: 1) dealing with a serious illness or health concern; 2) making a decision about school enrollment, financing school, or upgrading work skills; 3) dealing with a tax matter; 4) changing a job or starting a business; 5) getting information about Medicare, Medicaid, or food stamps; 6) getting information about Social Security or military benefits; 7) getting information about voter registration or a government policy; 8) seeking helping on a local government matter such as a traffic problem or schools; 9) becoming involved in a legal matter; and 10) becoming a citizen or helping another person with an immigration matter.
There was some variance in the results, depending on the type of problem that people confronted. For instance, those who dealt with a health problem turned to experts more than any other source, followed by family and friends, and then the internet. And those who had issues related to big government programs such as Social Security or Medicare were most likely to go directly to government agencies for help, then the internet.
Most people were successful in getting information to help them address a problem no matter what channel they chose and no matter what problem they faced.
A major focus of this survey was on those with no access to the internet (23% of the population) and those with only dial-up access (13% of the population). This low-accessÃ'Â population is poorer, older, and less well-educated than the cohort with broadband access at home or at work. They are less likely to visit government offices or libraries under any circumstances. And they are more likely to rely on television and radio for help than are high-access users.
Moola Opens "Massively Multiplayer Rewards Game" to Public
Here's how it works: Moola fronts users a penny to start, which puts you at the bottom rung of a thirty step ladder. Every time you win a game, you double your money, every time you lose, you fall all the way to the bottom and start over with a penny. If you win 30 times in a row, you walk away with $10.7 million (though you can cash out at any time, so risking a few thousand in an online head-to-head game at the middle levels is probably not that smart).
Moola has grown to 175,000 users since it launched the invite-only beta in 2006. Moola CEO Arlen Ritchie told me that recently the site has been getting a lot more traffic to their home page than they have registered users, which indicated that there is interest from people who don't have invites. So, now seemed like the perfect time to open the doors to the site.
Ritchie acknowledged that it is unlikely anyone will ever win the $10 million prize because most people wouldn't be crazy enough to risk $5 million to try for it -- in fact, two people would have to be that crazy. Of course, you don't have to wager it all on each game. You can play in any bracket below your account balance, and Ritchie told me that most people keep a positive balance rather than wagering all their cash at once. And even if winning the big one may never happen, a lot of real money is being made on Moola. The top player right now has over $8,000 and the highest cash out was in the $5,500 range. Users on the site have exchanged over $4 million so far (though that figure may count the same money being traded back and forth between users multiple times and doesn't represent the amount paid out).
Because it is unlikely anyone will make big money from the games, most users will either stay in a low game bracket (a few cents), which the ads will cover for Moola, or they will make money via Moola's other options -- at which Moola always makes money.
Other Ways to Make Moola
In addition to games, Moola enables users to make money by searching on their Moola Search page. Powered by Google Custom Search, Moola employs an algorithm that measures how much people search, weeds out illegitimate searches and clicks, and then shares ad revenue with searchers. You might only make a few pennies per day, but that money can be used to play Moola games and bump you into a higher playing bracket.
Moola also lets people make cash via what they call "Boosters" -- or, a cash back program based on affiliate marketing. Shopping at any of Booster's affiliated online stores results in cash deposited in your account. Moola supports a lot of major online retailers including Hotels.com, Buy.com, Travelocity, Skype, Old Navy, and NewEgg.
The final way Moola enables users to make money, is via a 4-level referral program. Refer friends, and take a cut of anything they do on the site, whether that's search payouts, Booster Zone payouts, or game winnings.
BoosterBar
Along with opening the site to the public, Moola will be announcing a toolbar that is really centered around their shopping and search revenue streams. They've built the Moola search into the bar, which makes it more convenient for people. It is the slick shopping integration, however, that will garner more interest. Any site you visit on the Internet that is a Moola affiliate will register on the bar and allow you to log into your account so your shopping is eligible for cash back. That lets people shop on the web as normal, rather than have to first page through the site's directory of affiliates -- something Moola expects most people aren't keen on doing.
If an ecommerce site is not a Moola partner, the BoosterBar will suggest an alternative that is in their affiliate network. Ritchie tells me that initial feedback from partners on this feature is tremendous. They love being able to steal visitors away from competition right at the point of sale.
Eventually, the game playing side of Moola will be integrated into the toolbar, allowing users to set up games and then surf the web while waiting for an opponent -- which can take longer at the higher levels where competition is more thin. Ritchie told me that the plan down the line is to add social features, such as chat or messaging, to the toolbar to augment the community that has grown up around Moola. Apparently, some users have taken to organizing their own tournaments based around Moola's games (you can set up one-on-one matches with specific players on the site).
The Games
For the cornerstone of the site, the games are rather weak. Moola has created three proprietary games for the site, with a fourth currently in development. Moola's line up includes a rock, paper, scissors game (*yawn*), Hi-Lo (*yawn*), and a bidding game where you try to out smart your opponent (not the most thrilling experience, but it held my attention longer than the others). But, Moola is in the planning stages of an API that would allow third-party developers to add games to Moola. They're currently in talks with two unnamed developers to create additional content prior to the release of a public API. (And they are soliciting queries from other interested game developers at gamedev@moola.com.)
Moola developers would be able to make money from both the advertising on the games, as well as take a cut of the money that changes hands between players. Ritchie also told me that the plan is to allow developers to "Moola-ize" their games outside of the site. So, for example, Microsoft could add Moola functionality to Halo 3 on XBox Live and then Moola members could organize Halo matches and play each other for cash.
Conclusion
Nothing at Moola is very revolutionary. Cash back shopping? Seen it. Competitive gaming? Seen it. Revenue share on search? Seen it. Multilevel referral program? Seen it. But they appear to have packaged everything up in a tidy manner, and the coming API for games is exciting. Winning money playing online games without putting any of your own cash up makes it a lot more fun (I'm up to $0.22 -- time to retire!), and the prospect of less snooze-worthy games from third-party developers sounds great.
It took Moola members 10 months to play for the first $1 million. The last million took about 4 months. The next million is on track to cross through Moola in just 55 days. Once the site opens up, those millions will probably be flying about at a more rapid rate.
In a day and age where services like Mahalo and Wikipedia are succeeding because of the human component of question answering (and some or all of those human components are receiving some sort of compensation), for Google to flout that makes for somewhat of a head-scratcher. Mashable
Google Answers to Relaunch as Google Q&A
Google intends to relaunch the question-answering service Google Answers, which was closed last year. In Google Answers, "users could post a question (...) and specify how much they were willing to pay for an answer. A researcher then searched for the information they wanted and posted it to Google Answers." Some of the former Google Answers researchers built a similar service at Uclue.com.
Google Q&A, code-named Confucius, no longer has paid experts and works in a similar way with Yahoo Answers. Google Q&A was launched in Russia in June and in China, two months later.
Here's a message from Google's translation console:
"Q&A - This message is a name of successor for Google Answers. We will use it in OneGoogle toolbar, which you see on top of google.com page in the more.. section. Also, please use full name to translate it. That is, Questions and Answers. Abbreviation should be used only for English. URL showing this message: toolbar on top of http://www.google.com."

It's interesting to note that Google Q&A is also the name of a feature that displays answers to simple questions at the top of Google's search results page. Maybe Google will combine the facts automatically extracted from web pages with the explicit answers from the new service.
Google Seeks To Turn College Students Into Local SEMs
You've got to hand it to Google for creativity. It created the local business referral representative program to enlist stay-at-home moms, college students and others to get better data about local businesses and build AdWords awareness. (I was told by Google that the response to the program had been strong.) Now Google has developed the "Google Online Marketing Challenge." According to the site, "student groups will receive US$200 of free online advertising and then work with local businesses to devise effective online marketing campaigns."
As a practical matter it seeks to create a global pool of college students (or MBA students) and turn them temporarily into search engine marketers for local businesses. It will be interesting to see how big the response is and whether it helps build Google AdWords awareness among local businesses in those markets where the competition takes off. The competition begins in February.
The program will potentially also create a great group of local marketing case studies that Google can then use in myriad ways for education or sales or training.
Google also said that an even simpler version of AdWords is coming next year: SimpleAds. Aimed at local businesses and resellers, it will seek to radically simplify AdWords adoption.



