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TWITTER: THE DARK SIDE
Does Twitter’s Bit.ly Enable a Massive Click Fraud?


Statistics Bit.ly provides is egregiously inaccurate at best and fraudulent at worst. Bit.ly counts cyberspace’s ghosts and drones, bots and crawlers, presenting them all as humans.

Bit.ly’s statistics are inaccurate at best and fraudulent at worst and that they do not discriminate between real and robotically generated automatic clicks with no actual human behind the click.

Clicks or Click Fraud?

Bit.ly Clicks Animation

Check out animation about millions of bots clicks show at Bit.ly as "statistics"

Twitter: The Dark Side Study

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TWITTER: The Dark Side - EXECUTIVE SUMMARY

BACKGROUND

This Case Study provides a detailed analysis of numerous vulnerabilities of Bit.ly - the URL shortener chosen by Twitter, a Social Networking and microblogging service. Twitter is the buzz of the day despite or perhaps because of the fact that it has no revenue. Nevertheless with a recent investment of $100 million dollars received, Twitter has been valued as a billion-dollar venture.

Moreover, Twitter’s service limits how its users behave, how much they can say and how often they can say it. These limits, especially Twitter’s limitation of a post (“tweet”) to 140 characters has created a need for a URL shortener service i.e. a service that translate a long URL (Uniform Resource Locator) link into a short version of it that redirects a user to the original webpage. Therefore, the challenge of the Case Study was to analyze and measure the quantity, frequency and validity of clicks delivered by users to each other and by marketers and advertisers to clients on Twitter via Bit.ly.

METHODOLOGY

We set-up four Experiment Tasks that would invite, create, track and log clicks on Twitter / Bit.ly by:

using our own URL shortner Dac.im and

our Apache server logs while

measuring and comparing Bit.ly’s clicks statistic with our data and

with Google Analytics, Stat Counter & AdSense analytics data as

additional comparative analytics tools.

We also created and used various Twitter accounts and created and ran various robots to post on Twitter and Bit.ly. We compared and analysed all the data, looking at each and every IPA (Internet Protocol Address) recorded in logs for the purpose of determining a validity of each click i.e. is that click generated by a bot or by a human.

RESULTS

Many Twitter users, both corporate and individual, are uninformed regarding the true validity, value and measurement of clicks generated by Twitter activities directed at their target websites. The distorted mass media perceptions of the impact of Twitter when used as a marketing tool has mislead audiences on many levels. Our experiments have shown that:

Bit.ly under-reports raw numbers (total) of clicks for about 55%,

Bit.ly over-reports the number of human clicks for more than 95%,

Bit.ly does now show BOTS vs. HUMANS click ratio that goes up to 98% for automated, bots clicks and only 2% for human clicks,

Twitter’s number of followers on each account includes a huge number of robotic followers of no value for a human user whatsoever,

Twitter’s Direct Messaging as marketing tools is of no great value also; only 4.6% of users responded to a DM,

Bit.ly numerous vulnerabilities are best seen in our Experiment that produced 1,677,771 robotic clicks without a single human clicking on a short link created by Bit.ly and included in their “statistics”.


CONCLUSION

Quantitative results have shown that Bit.ly’s statistics are inaccurate at best and fraudulent at worst and that they do not discriminate between real and robotically generated automatic clicks with no actual human behind the click. Bit.ly statistics report only an aggregate number of clicks on any given link and therefore have almost no value for any Twitter user, be they an advertiser, a marketeer or individual selling products or services online.


RECOMMENDATIONS

Numerous Bit.ly’s security vulnerabilities and reporting inaccuracy point to an urgent need for the Standardization of the URL Shortener services that would include well defined and peer reviewed filtering of all shortened links and accurate reporting to prevent both click fraud and breaches of user’s privacy and security on-line.

PART II: INTRODUCTION to On-line Social Networking

 



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