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"  Regardless of what you think about Newt Gingrich, he does have one thing going for him: more than 1.3 million Twitter followers (a fact he likes to bring up). But this may not be as impressive as it sounds. On Monday, an anonymous source who claimed to be a Gingrich ex-staffer told Gawker that most of those followers are fake, or &amp;quot;dummy&amp;quot; accounts set up by an agency hired to boost follower numbers. The next day the search company PeekYou released a report calculating that only 8 percent of Gingrich&amp;#039;s followers were real human beings.  While there&amp;#039;s no concrete proof that Gingrich bought followers, the former Speaker of the House is certainly not alone in having a set of Twitter followers that is substantially fake. Those of us who tweet regularly are all too familiar with receiving emails notifying us that some mysterious-sounding entity of potentially dubious origin is following us. But just how many of a person&amp;#039;s Twitter followers are phony? I ran a quick experiment to find out.  First, I analyzed 500 accounts that follow me at @Douglas_Main. The results: Real people: 58 percent (290) Legitimate companies or organizations: 22 percent (110) Fake or spam: 19 percent (95) Unclear: 1 percent (5) Not bad. For comparison, I then analyzed the most recent 500 of the 2000 or so accounts that follow Popular Mechanics assistant editor John Herrman at @jwherrman. Here&amp;#039;s his tally: Real people: 24.6 percent (123) Legitimate companies or organizations: 14 percent (70) Fake or spam: 48.6 percent (243) Unclear: 12.8 percent (64) Herrman&amp;#039;s total of real humans is actually closer to the average, PeekYou founder and CEO Michael Hussey says. The company&amp;#039;s program, PeekAnalytics (which will be released within the month) examines public records and other digital accounts linked to Twitter to determine if users are indeed real humans. According to his data, only 35 percent of the average Twitter user&amp;#039;s followers are actual people. Part of the reason Herrman has so many more bot followers than I is simply that he has a higher overall number of followers, and he is more active on Twitter. Greg Finn, an editor at Search Engine Land and an Internet marketer, tells PM that generally people with more followers and more tweets will have higher percentage of spam or bots, automated accounts controlled by a computer program. Bots also search out and follow people who tweet certain key words, or automatically follow every account that other users follow. Often, however, bots will un-follow those who don&amp;#039;t follow back, allowing them to stay undetected by Twitter&amp;#039;s spam sleuths, who look for unusual spikes in follow numbers, Finn says. (Twitter itself is not keen to talk about this issue; requests to speak with the company were not answered.) One of the biggest obstacles to finding spammers and fake accounts, whether it be by Twitter&amp;#039;s spam police or third parties, is the wide variety of ways real humans use the service, according Sheldon Levine, a manager at analytical software firm Sysomos. For example, some people use Twitter solely for news, following hundreds or thousands of accounts but rarely if ever tweeting themselves. But such an account is exactly what many spam accounts look like.  An obvious trait that can give away spam accounts is the lack of a bio or any personal information beyond the name (or random collection of characters) in a Twitter handle. An analysis of Gingrich&amp;#039;s million-plus horde of Twitter followers by a group from Indiana University found that 76 percent of Gingrich&amp;#039;s followers lacked a profile biography. But again, that trait by itself is not a certain indicator of a fake account\u201A many real people don&amp;#039;t fill in those fields, either. &amp;quot;There&amp;#039;s no real discernible way to tell a real account from a spam without looking at what they&amp;#039;re doing, what their bio is, what they&amp;#039;re tweeting,&amp;quot; Levine says. That may be why there are no reliable free services capable of telling you which accounts are spam, although companies such as Sysomos, Radian6 and Alterian sell products that claim to accomplish just that.  Indeed, my own quest to categorize followers showed just how difficult it is to tell, even with a human eye analyzing each account. It took nearly 3 hours to sift through 500 of Herrman&amp;#039;s followers, and even then I had to label 13 percent of the accounts as &amp;quot;unclear&amp;quot; because many of these users tweet seemingly random sentences or links that could be automatically generated, or could be written by real people who use Twitter for inscrutable reasons (or simply write in a way that is not easily identifiable as human).  All this time spent sorting real from fake left me wondering: What do spammers get out of fake Twitter handles to make it worth all the trouble? Jason Jones, an antispam activist who goes by his Internet moniker Salty Droid, says fake accounts serve several purposes. Most importantly, they allow users who gain a large following to appear legitimate or popular. &amp;quot;It&amp;#039;s about providing convincing evidence that you are somebody when you&amp;#039;re not,&amp;quot; Jones says. Users can then leverage this fake celebrity to help them promote a product or infect others with viruses via links to shady websites. Accounts with many followers can also be sold via eBay or other sites. Hussey says his team paid $100 on eBay for a fake account with 12,000 followers, which they then used to improve their spam filter and to help them figure out which users were real.  Fake accounts that follow many people can also gather information on real users to inform product pitches or even to steal people&amp;#039;s identities. Twitter notifies its users when they get new followers, forwarding profile information that could contain spam links (in their bio or one of their tweets) to a malicious site. These emails, because they originate from Twitter, pass through spam filters unnoticed. However, Hussey says, there is one surefire way to find the frauds in your follower list: Look for accounts with profile pictures of scantily clad women. &amp;quot;One of the things I joke about is that Twitter should have a filter for users whose profile picture is of a woman in a bikini,&amp;quot; he says. &amp;quot;Ninety-nine percent of the time it&amp;#039;s spam.&amp;quot; (Follow PM at @popmech. If you&amp;#039;re a real carbon-based life-form, that is.) "^^<http://www.w3.org/2001/XMLSchema#string>
<http://www.popularmechanics.com/technology/a6941/how-much-of-twitter-is-spam/?click=main_sr>