What is it?
Well as Twitter puts it, “Twitter is a service for friends, family, and coworkers to communicate and stay connected through the exchange of quick, frequent messages” (Twitter, 2016).
Through Twitter, people are able to post and share ‘Tweets”, a message “… which may contain photos, videos, links and up to 140 characters of text” (Twitter, 2016).
What may seem to be a simple mode of communication has blown up to gargantuan proportions with 1.3 billion registered Twitter accounts and 310 million human users (Smith, 2016).
Why do I use the noun ‘humans’?
Interestingly, today these engineered Twitter bots account for 8.5% of all Twitter users (Weinberger, 2016).
What are bots you say?
Well bots are “… algorithms acting in social media networks [who] look like real users, coming in all shapes and sizes” (Finger, 2015).
But how are they sought?
They’re actually extremely easy to obtain. Or purchase.
While they can also be made, Social Media Marketing sites like Devumi, Fast Followerz and Twitter Boost to name a few.
The mind-blowing thing about all this is the fact that one thousand followers can run you as low as $19 (Buy Twitter Followers Reviews, 2014).
But while the Twitter bot as well as the rise in activity in Social Media bots in general are easy to obtain, the issue of whether they are a good idea in the first place is still up in the air.
With this in mind, it is important that you understand that Twitter holds a strong stance against the use of bots, or the automated use of twitter, confirmed that “creating and/or automating serial (or multiple) accounts for overlapping use cases is prohibited” (Twitter, 2016).
But while they restrict the use of bots, they’re position on the issue has SOME leeway, declaring that “Automating multiple accounts for what Twitter deems to be community benefit is permitted” (Twitter, 2016).
Whether for good or bad, the question rises, “How do I spot a Twitter bot?”
Characteristics to look out for include (Finger, How To Spot Social Media Bots – They Are Often Lonely, 2015):
- Time: Regular or Bursty
- Heavy Hashtag usage
- Blacklisted URL
- Spam Words
- Few Friends
Keeping this in mind, it is crucial to note that the act of identifying a Twitter bot, or any other social media bot can be tricky, and while these seem like simple identifiers, the process can be a lot more complicated.
I mean if it was that easy, the US military wouldn’t have “enlisted academics to fight a new enemy: Twitter Bots” through the Defense Advanced Research Projects Agency (DARPA) (Weinberger, 2016).
During the 4-week competition, DARPA placed “39 pro-vaccination influence bots onto a fake, Twitter-like social network”, without informing contestants exactly how many there were (Weinberger, 2016).
Over the duration of the competition, teams from the University of Southern California, Indiana University, Georgia Tech, Sentimetrix, IBM, and Boston Fusion lent their expertise for good. The competition allowed for the culmination of all participating team’s techniques into a complicated 3-step process (Weinberger, 2016).
- Initial bot detection – using language analysis, bots are detectable through “statistically unnatural and bot-generated words and phrases”
- Clustering, outliers, and network analysis – follow bots in order to utilize initial findings to “get a good statistical sense of robot social circles”
- Classification/Outlier analysis – effective indications sought through steps one and two, allow an “effective extrapolation of data to reveal additional bots”
It is with this that it was discovered (if it wasn’t already known already) that bots require human interaction to be effective.
So sleep well, knowing that computers can’t tell the difference between a human and a bot.
At least for now.
- Buy Twitter Followers Reviews. (2014). Retrieved from Buy Twitter Followers Reviews: http://buytwitterfollowersreview.org/top-10/
- Finger, L. (2015, February 17). Do Evil – The Business Of Social Media Bots. Retrieved from Forbes: http://www.forbes.com/sites/lutzfinger/2015/02/17/do-evil-the-business-of-social-media-bots/#11fdea941104
- Finger, L. (2015, February 24). How To Spot Social Media Bots – They Are Often Lonely. Retrieved from Forbes: http://www.forbes.com/sites/lutzfinger/2015/02/24/how-to-spot-social-media-bots-they-are-often-lonely/2/#1c27a95b5223
- Smith, C. (2016, April 30). By the Numbers: 170+ Amazing Twitter Statistics. Retrieved from Expanded Ramblings: http://expandedramblings.com/index.php/march-2013-by-the-numbers-a-few-amazing-twitter-stats/
- (2016, April 7). Automation rules and best practices. Retrieved from Twitter: https://support.twitter.com/articles/76915
- (2016, April). New user FAQs. Retrieved from Twitter: https://support.twitter.com/articles/13920
- Weinberger, M. (2016, January 22). The US government held a contest to identify evil propaganda robots on Facebook and Twitter. Retrieved from Business Insider: http://www.businessinsider.com.au/darpa-twitter-bot-challenge-2016-1