Central Perk

joi, 23 iunie 2011

Damn Cool Pics

Chinese College Student's "Washing Machine"
The 50 Most Googled Women on the Web
Courtney Stodden, The 16-Year-Old Bride
The World's Scariest Job
Should you invest in the Grouponzi IPO?
Balding Celebrities

Chinese College Student's "Washing Machine"

Posted: 23 Jun 2011 04:25 PM PDT

A short video that recently spread on the Chinese internet featuring one Chinese college student's "creative" method for "automatically" washing his clothes using two water faucets. In China, many people still handwash their laundry.

The 50 Most Googled Women on the Web

Posted: 23 Jun 2011 03:12 PM PDT

According to Coed Magazine, which compiled a list for the 50 Most Popular Women on the Web, Lady Gaga is the most popular woman online based on Google searches and statistics.

Who would have thought that Justin Bieber will be included in the list of 50 most popular women on the Internet. Among the 50 most talked about women in Internet Justin Bieber is on the list and is making the number 2 on the list. Well, nobody can deny its popularity, and I think there's something to say about his fame, if it can really add to the list of best looking women.

#50 Blake Lively - 47,800,000 Results

#49 Marilyn Monroe - 47,900,000 Results

#48 Cheryl Cole - 49,700,000 Results

#47 Carrie Underwood - 50,500,000 Results

#46 Kelly Clarkson - 51,400,000 Results

#45 Hillary Clinton - 51,400,000 Results

#44 Scarlett Johansson - 52,700,000 Results

#43 Michelle Obama - 52,900,000 Results

#42 Natalie Portman - 53,100,000 Results

#41 Nicole Scherzinger - 56,400,000 Results

#40 Penélope Cruz - 57,200,000 Results

#39 Chelsea Handler - 57,800,000 Results

#38 Hilary Duff - 58,500,000 Results

#37 Ciara - 58,800,000 Results

#36 Ke$ha - 61,600,000 Results

#35 Kylie Minogue - 62,700,000 Results

#34 Vanessa Hudgens - 62,400,000 Results

#33 Emma Watson - 67,500,000 Results

#32 Jessica Simpson - 69,100,000 Results

#31 Kristen Stewart - 71,300,000 Results

#30 Jennifer Aniston - 71,400,000 Results

#29 Ashley Tisdale - 71,600,000 Results

#28 Fergie - 73,700,000 Results

#27 Jessica Alba - 79,500,000 Results

#26 Kate Middleton - 81,300,000 Results

#25 Sarah Palin - 90,100,000 Results

#24 Mariah Carey - 107,000,000 Results

#23 Christina Aguilera - 111,000,000 Results

#22 Megan Fox - 118,000,000 Results

#21 Oprah Winfrey - 124,000,000 Results

#20 Angelina Jolie - 134,000,000 Results

#19 Paris Hilton - 145,000,000 Results

#18 Taylor Swift - 159,000,000 Results

#17 Lindsay Lohan - 173,000,000 Results

#16 Avril Lavigne - 175,000,000 Results

#15 Adele - 177,000,000 Results

#14 Selena Gomez - 179,000,000 Results

#13 Beyonce - 195,000,000 Results

#12 Miley Cyrus - 207,000,000 Results

#11 Jennifer Lopez - 214,000,000 Results

#10 Madonna - 230,000,000 Results

#9 Kim Kardashian - 232,000,000 Results

#8 Shakira - 239,000,000 Results

#7 Katy Perry - 263,000,000 Results

#6 Britney Spears - 277,000,000 Results

#5 Nicki Minaj - 296,000,000 Results

#4 Cher - 340,000,000 Results

#3 Rihanna - 384,000,000 Results

#2 Justin Bieber - 496,000,000 Results

#1 Lady Gaga - 578,000,000 Results

Courtney Stodden, The 16-Year-Old Bride

Posted: 23 Jun 2011 12:43 PM PDT

Love is a weird thing: You never quite know when and where cupid's arrow might strike. Take, for example, the recent nuptials of Doug Hutchison, a 51-year-old actor best known for a recurring role on Lost, to (allegedly) 16-year-old Courtney Stodden. The mother of 16-year old Courtney did consent which is the only reason the wedding is legal.

A model at age 12, Courtney signed with the John Casablanca modeling agency, and from there entered the world of Donald Trump's Miss Universe pageant at age 15. She was Miss Ocean Shore WA, USA and represented her city in the Miss Washington pageant.

Courtney is also a pop singer with three original songs called We Are America, Crazy, and Car Candy.

Doug Is An Actor Who You Might Recognize As That Creepy Guy From "Lost"

Or That Creepy Guy From "The Green Mile"

Or That Creepy Guy From "The X-Files"

The World's Scariest Job

Posted: 23 Jun 2011 11:13 AM PDT

While some people would find it unbearable to go anywhere near the edge of a cliff, these Chinese workers are building a 3ft-wide road made of wooden planks on the face of a mountain that's thousands of feet high. Once finished, it is hoped sightseers will flock to here to edge along and admire the views.

The 'road' - the width of a dinner table - they're assembling is on Shifou Mountain in Hunan Province and stands vertical at 90 degrees without any slopes or alcoves. What's more, these workers from China's eastern Jiangxi Province toil away on it with what appear to be few if any safety measures.

Source: telegraph.co.uk

Should you invest in the Grouponzi IPO?

Posted: 23 Jun 2011 11:07 AM PDT

On the heels of filing its $750 million initial public offering, online coupon startup Groupon is under heavy scrutiny from critics.

Until recently, most people praised Groupon for its simplistic business model and its incredible growth, which some have called the fastest of any company to date.

Groupon lets users purchase steeply discounted deals from local merchants. Discounts range anywhere from 30 to 80 percent off the regular sale price on food, trips, drinks at a local bar, etc. Groupon takes half of the money from every deal sold, which is a pretty easy way to bring in a lot of money without having to get creative.

But the Chicago-headquartered company is still running at a loss despite the astonishing revenue growth, which went from $94,000 in 2008 to $713 million in 2010, according to the filing. Groupon has consistently lost money every quarter since launching except for one — the first quarter of 2010, when it brought in an $8 million profit. Comparatively, it lost $146.5 million in the first quarter of 2011.

Click to Enlarge.

Source: onlinemba

Balding Celebrities

Posted: 22 Jun 2011 07:50 PM PDT

These celebrities went from a full head of hair to being bald. Some of them probably had such a extreme haircut because they were going bald anyway, some because it was required for a movie roll, and some just to make a statement. Regardless of the reason they sure look different.

Eddie Murphy

Jake Gyllenhaal

Amber Rose

Laurence Fishburne

Eric Bana

Britney Spears

Bruce Willis

Howie Mandel

Patrick Stewart

Kevin Spacey

John Malkovich

Brad Pitt

Demi Moore

Jack Nicholson

Timothy Olyphant

Michael Stipe

Hugh Jackman

Ving Rhames

Vin Diesel

Woody Harrelson

John Travolta

Joey Lawrence

Andre Agassi

Marlon Brando

Cate Blanchett

Colin Farrell

Billy Corgan

Lady GaGa

Samuel L. Jackson

Cameron Diaz

SEOmoz Daily SEO Blog

The Wikipedia Model

Posted: 22 Jun 2011 02:01 PM PDT

Posted by russvirante

This post was originally in YOUmoz, and was promoted to the main blog because it provides great value and interest to our community. The author's views are entirely his or her own and may not reflect the views of SEOmoz, Inc.

As an SEO agency, Virante has always prided itself in having research-based answers to the questions presented by our clients. A year or so ago, I caught myself referring to the a site as having "a great looking natural link profile" without really having an numbers or analysis to describe exactly what that profile should look like. Sure, I could point out a spam link or two, or what looked like a paid link, but could we computationally analyze a backlink profile to determine how "natural" it was?

We dove into this question several months ago while trying to identify automated methods to identify link spam and link graph manipulation. This served dual purposes - we wanted to make sure our clients were conforming to an ideal link model to prevent penalties and, at the same time, wanted to be able to determine the extent to which competitors were scamming their way to SEO success.

Building the Ideal Link Model

The solution was quite simple, actually. We used Wikipedia's natural link profile to create an expected, ideal link data set and then created tools to compare the Wikipedia data to individual websites...

Select 500+ random Wikipedia articles
Request the top 10,000 links from Open Site Explorer for each Wikipedia article
Spider and Index each of those backlink pages
Build tools to analyze each backlink on individual metrics

Once the data was acquired, we merely had to identify the different metrics we would like to compare against our client's and their competitors' sites and then analyze the data set accordingly. What follows are three example metrics we have used and the tools for you to analyze them yourself.

Link Proximity Analysis

Your site will be judged by the company it keeps. One of the first and most obvious characteristics to look at is what we call Link Proximity. Most paid and spam links tend to be lumped together on a page such as 20 backlinks stuffed into a blog comment or a sponsored link list in the sidebar. Thus, if we can create an expected ideal link proximity from Wikipedia's link profile, we can compare it with any site to identify likely link manipulation.

The first step in this process was to create the ideal link proximity graph. Using the Wikipedia backlink dataset, we determined how many OTHER links occurred within 300 characters before or after that Wikipedia link on the page. If no other links were found, we recorded a 1. If one other link was found, we recorded a 2. So on and so forth. We determined that about 40% of the time, the Wikipedia link was by itself in the content. About 28% of the time there was one more link near it. The numbers continued to descend from there.

Finally, we plotted these numbers out and created a tool to compare individual websites to Wikipedia's model. Below is a graph of a known paid-link user's link proximity compared to Wikipedia's. As you will see, nearly the same percentage of their links are standalone. However, there is a spike at five proximal links for the paid link user that is substantially higher than that of Wikipedia's average.

Even though paid links only represent a ~25% proportion of their link profile, we were able to detect this anomaly quite easily. Here is the Link Proximity Analysis tool so that you can analyze your own site.

White Hat Takeaway: If you are relying on link methods that place your link in a list of others (paid, spam, blog-rolls, etc.), your links can be easily identified. While I can't speak for Google, if I were writing the algorithm, I would stop passing value from any 5+ proximal links more than one standard deviation above the mean. Go ahead and use the tool to determine if your site looks suspicious. Run the tool on your site and make sure that you are within about 18% of Wikipedia's pages for 4+ proximal links.

Source Link Depth Analysis

The goal of Paid Links is to boost link juice. The almighty PageRank continues to be the primary metric which link buyers use to determine the cost of a link. Who buys a PR0 link these days? It just so happens that PageRank tends to be highest on the homepage of sites, so most Paid Links also tend to come from the homepage. This is another straightforward method for finding link graph manipulation - just determine what percentage of the links come from homepages vs. internal pages.

Once again, we began by looking at the top 10,000 backlinks for each 500 random Wikipedia pages. We then tallied the number of folders deep for each link acquired. For example, a link from http://www.cnn.com would score a 1. From http://www.cnn.com/politics would score a 2. We created a graph of the percentage at which each of these occurred and then created a tool to compare this ideal model to that of individual websites.

Below is an example of a known paid-link user's site.

As you can see, 79% of their top links come from the homepages of websites, compared to Wikipedia's articles with average around 30%. SEOmoz, on the other hand, receives only 40% of its links from homepages, well within the standard deviation, and Virante receives 29%. Here is the Source Link Depth Analysis tool so that you can compare your site to Wikipedia's.

White Hat Takeaway: If your link strategy involves getting links primarily from the homepages of websites, the pattern will be easily discernible. Run the tool and determine whether you are safely within 15% of Wikipedia's pages in terms of homepage links.

Domain Links per Page Analysis

Yet another characteristic we wanted to look at was the number of links per page pointing to the same domain. Certain types of link manipulation like regular press releases, article syndication, or blog reviews tend to build links two and three at a time, all pointing to the same domain. A syndicated article might link to the homepage and two product pages, for example. Our goal was to compare the expected number of links to Wikipedia pages from a linking page to the actual number of links to a particular website, looking for patterns and outliers along the way.

We began again with the same Wikipedia dataset, this time counting the number of links to Wikipedia from each linking page. We tallied up these occurrences and created an expected curve. Finally, we created a tool to compare this curve against that of individual sites.

The example below is a site that heavily relied on paid blog reviews. As you will see, there is a sharp spike in links from pages with three inbound links to the domain.

Caveat: Chances are when you run this tool you will see a spike at position #1. It is worth pointing out that the majority of website homepages tend to fall in this category. When you run this tool, as with the others, you should probably take a second to look at your competitors as well. Is your site closer to Wikipedia's model than your competitors? That is the question you should be asking first.

White Hat Takeaway: Is your link strategy creating patterns in domain links per page? A natural link graph will have great variation in this. Moreover, it is not uncommon for authoritative sites to have 10+ links to pages from sites. This should be expected - if your site is the authority, it would make sense for it to be cited several times on a thorough page about your subject matter. Here is the Multiple Links Analysis tool to compare your site to Wikipedia's.

What to Do?

First things first, take every result you get with a grain of salt. We have no reason to believe that Google is using Wikipedia's backlink profile to model what is and is not acceptable, nor do we pretend to believe that Google is using these metrics. More importantly, just because your site diverges in one way or another from these models does not mean that you are actually trying to manipulate the link graph. If anything, it demonstrates the following...

If you are manipulating the link graph, it is pretty easy to see it. If Virante can see it, so can Google.
If you are still ranking despite this manipulation, it is probably because Google hasn't caught up with you yet, or you have enough natural links to rank despite those that have been devalued.

So, what should you do with these results? If you are using a third party SEO company to acquire links, take a hard look at what they have done and whether it appears to differ greatly from what a natural link profile might look like. Better yet, run the tool on your competitors as well to see how far off you are compared to them. You don't have to be the best on the Internet, just the best on your Keyword.

Tool Links One More Time:

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VIDEO: Following-up on last night

Good morning,

In December 2009, President Obama promised the American people that we would begin the drawdown of troops in Afghanistan in July 2011, and last night he announced his plan to make good on that promise. By the end of this year 10,000 troops will return home and that number will reach 33,000 troops by next summer.

To put this important decision in a larger context, Vice President Joe Biden took a few minutes to share his thoughts about the promises this Administration has made – and kept – when it comes to the war in Afghanistan, the war in Iraq, and our commitment to defeat al Qaeda:

Sincerely,

David Plouffe
Senior Advisor to the President

P.S. In case you missed the President's remarks, you can watch the video here:
WhiteHouse.gov/AfghanSpeech

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How to Get Reviews For Your Website Graywolf's SEO Blog

How to Get Reviews For Your Website

Posted: 22 Jun 2011 10:42 AM PDT

Reviews are an extremely powerful asset for many websites. They can provide a continual stream of fresh, new, and unique content that is good for the users, which is ultimately what everyone wants. However, there are some upsides and downsides to reviews, and there is the big hurdle of figuring out how to get reviews and integrate them. In this post, we’ll take a look at these different aspects.

the hardest part of reviews isn't the technical aspects; it’s getting reviews in the first place…

The biggest and best reason for wanting to add reviews to your website is that you will have new content added to your website regularly that has useful information searchers are looking for. That said, reviews do have some issues. Anytime you deal with UGC (user generated content), you expose yourself to a new set of problems (see the Joys and Woes of User Generated Content by Vanessa Fox). First off, you should have a review policy that stipulates what languages you will accept, acceptable language and terminology, minimum lengths, maximum number of reviews, and so on. I wouldn’t try to make them iron clad laws, but I would set some general best practices that allow you some editorial wiggle room. I know a lot of sites that have little to no moderation and only delete for explicit language or slander/defamation; personally, I like to use a bit more editorial control and give editors the ability to clean up grammar and spelling. That said, there is a difference between changing “goood” to “good” and “goood” to “great.” Changing the intent of someone’s review is bad mojo and may have legal consequences, so tread lightly. That said, I think moderation is important. No matter how tight you make your review policy, someone will find a loophole and submit something that should never be published. You ultimately want editorial control to filter out the trolls and shills.

One thing that I don’t think is a good practice is filtering out reviews that don’t work to your benefit. Let’s say you sell two competing products, and one makes you considerably more affiliate income per unit sold. There will be the temptation to moderate reviews so that the one that makes you more money has none or very few bad reviews. This, my friend, is the path to the dark side. Don’t go there. Once people stop trusting your site, it’s over. Additionally, you should know Google recently filed a patent about detecting fake reviews (see How Google Might Choose High Quality Reviews to Display for Products and Businesses). It’s worth being aware of.

Whatever CMS you are using, chances are good that there are one or more review plugins or modules available. I recently reviewed WP Review Site Plugin and MyReview Plugin for WordPress and ultimately chose MyReviewPlugin. You can read the reviews but, in the end, it was admin features that were the deciding issue. You want to make sure that, whatever solution you choose, the output is compatible with Google’s rich snippet program. Once you have reviews for all your products or nearly all your products, submit your website for inclusion.

IMHO, the hardest part of reviews isn’t the technical aspects. It’s getting reviews in the first place. It’s a huge catch 22 situation: no one submits reviews until you have reviews. So here are some ideas about getting the process started.

Self Reviews

The best way to get honest reviews is to use the products or services yourself and write the reviews. Unless you have a connection who gets you review units or you get comped services, this can be very expensive. An example of this is GoVisitHawaii.com, which is run by Sheila Beal. She drags Andy Beal along, and they actually stay in different hotels in Hawaii and write up reviews (see
Review: Westin Princeville Resort, Review of Kauai Marriott Resort and Review: Waikiki Beach Marriott Resort and Spa). Yeah, visiting Hawaii on a regular basis is a tough gig, but somebody has to do it . One big advantage of this approach is that you can build a huge database of images (see how to build links with images). Look at the pictures and reviews on Travelocity and then look at those on Oyster; there simply is no comparison between the two.

Review Contests

Looking to get the ball rolling with user submitted reviews? Try a contest. To be clear here, the one thing you want to avoid is the appearance of incentivizing false positive or negative reviews. What you want to do is enter everyone who submits a review, whether positive or negative, that meets your editorial standards, into a contest. If you go this route, you will probably need to run the contest for a few months, so plan on a sustainable prize distribution, like an American Express gift card. If don’t have an established audience or social media presence you will need to “push” the contest on services like Twitter or even take out Facebook ads. Try to convert people who submit reviews to Facebook fans, Twitter followers, or add them to your mailing list.

Rewritten Reviews

This tactic can be summed up as “fake it till ya make it.” Basically, you are going to use reviews from other services and have people rewrite them and submit them to your website. If you keep the tone of the review the same but just rewrite them, it’s wrong but just a little wrong. If you write the reviews to achieve your own goals (I’ll let you work out why you would want to do that yourself), it’s a whole lot of wrong going on. Ideally, though, this is a short term strategy. Once you get enough real reviews, you should go back and delete the ones you influenced. I’m not going to be naive and tell you this doesn’t happen or that I’ve never done it, but use it sparingly and for as short a time period as possible.

So what are the takeaways from this post on How to Get Reviews For Your Website

Look for ways to ad reviews to your website.
Add your own editor reviews.
Encourage users to submit new reviews on a regular basis through contests or other means.
As a last resort, have reviews created for you to get critical mass.
Make sure your reviews are formatted to meet Google’s rich snippet specifications.
Apply for inclusion into the rich snippet program.
Make sure you are getting new reviews on a regular basis.

photo credit: Photospin

How To Get Customer Reviews on Your Website While UGC and Reviews can often be a mixed blessing,...
SEO for Product Reviews, Part I If you do any SEO work on branded or named...
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Let’s Talk About Reviews All right since I’ve gotten some feedback on reviews I’d...
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This post originally came from Michael Gray who is an SEO Consultant. Be sure not to miss the Thesis Wordpress Theme review.

How to Get Reviews For Your Website

Photo: First Lady and Nelson Mandela in South Africa

Your Daily Snapshot for
Thursday, June 23, 2011

First Lady and Nelson Mandela in South Africa

First Lady Michelle Obama continues her visit to South Africa and Botswana this week during an official visit focused on youth leadership, education, health and wellness.

Learn more at http://www.whitehouse.gov/youngafrica.

First Lady Michelle Obama talks with former South African President Nelson Mandela about his book during a visit at Mandela's home in Houghton, South Africa, June 21, 2011. (Official White House Photo by Samantha Appleton)