joi, 23 iunie 2011

Damn Cool Pics

Damn Cool Pics

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
Publicat de 1 la 19:45 0 comentarii

SEOmoz Daily SEO Blog

SEOmoz Daily SEO Blog

The Wikipedia Model

Posted: 22 Jun 2011 02:01 PM PDT

Posted by russvirante

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...

  1. Select 500+ random Wikipedia articles
  2. Request the top 10,000 links from Open Site Explorer for each Wikipedia article
  3. Spider and Index each of those backlink pages
  4. 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...

  1. If you are manipulating the link graph, it is pretty easy to see it. If Virante can see it, so can Google.
  2. 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


The White House, Washington


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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