There are two @Davekarpf’s on Twitter. The first one is me, @davekarpf. The second is a spambot, named @davekarpf_. The spambot seems pretty benign. It has taken my name and my avatar photo, but otherwise neither impersonates me nor spreads noxious links through the web.
I learned about my spambot last month, while I was in London for the International Communication Association Annual Meeting. I had just finished reading Finn Brunton’s excellent book, Spam: A Shadow History of the Internet, so I found the experience particularly intriguing. Someone mentioned “hey Dave, did you know that you have a fake account?” I tried contacting Twitter to have the account shut down, but couldn’t jump through all of the required hoops while I was out of the country. I tried again two weeks ago, but no luck.
The interesting thing about this spam account is that it does so little actual spamming. It has 34 tweets, 6 followers, and follows only 90 people. Only one tweet includes a shortlink, and that one is a retweet. The poster sounds like a high school or college kid, and isn’t going out of their way to either impersonate me or damage my reputation. They’ve simply appropriated my likeness.
What’s more interesting about the spambot is that its 6 followers are ALSO probably spambots. 4 of those followers are @Bradleywi_, @Joshuadav_, @BETV_Rockitweb_, and JustinJMarcus_. Notice the underscores at the end of each name. Each of these appropriate a real person’s avatar, name, and account details, then add an underscore at the end. Each includes similar, benign tweets.
So what’s the big deal? What’s going on here?
I’ve actually written about this phenomenon before, in my 2012 article, “Social Science Research Methods in Internet Time“:
When financial value or public attention is determined by an online metric, an incentive is created for two industries of code-writers: spammers/distorters, who falsely inflate the measure, and analytics professions, who algorithmicaly spearate out the spam/noise to provide a proprietary value-added. …Any metric of digital influence that becomes financially valuable, or is used to determine newsworthiness, will become increasingly unreliable over time.
Twitter has a well-known spambot problem. Analytics professionals have gotten good at identifying the obvious spambots. Gibberish names, zero tweets, no picture, following-thousands-with-zero-followers… All of these serve as flags for spam-detecting code-writers. So the spammers have to get more sophisticated. They appropriate profiles, seed them with harmless tweets, and keep the follow counts manageable. That can all be accomplished through a pretty simple script. Then, voila, you’ve got yourself a botnet, which you can use to goose metrics like Klout rankings, follower counts, and trending topics. Tweetspam is evolving.
My spambot doesn’t appear to mean me any harm, so I won’t try all that hard to get it deleted. I’ll devote another half hour of effort next week. But if Twitter Central makes it too difficult, then I’ll have little reason to bother. The bot is aimed at the broader Twitter ecology, not at me personally.
…And that, ladies and gentlemen, is how tweetspam got a little bit trickier.