Judgement Day for Spammers

In 2014, the infamous ‘Instagram Rapture’ took place and millions of inactive and spam accounts were deleted. In an effort to fight against accounts that hijack hashtags and exist only to bump up followers, Instagram deleted many of these accounts, and the results were visible when Instagram’s own followers went down 18.9 million users. The same happened to many celebrities and brands, shocking Instagram users (Goel). However, many users were probably as glad as I was because direct messages from bots and hackers can get irritating.

This issue of fake accounts has arisen in multiple social media apps and websites, causing many numbers and data sets to be inaccurate. For example, when Instagram analyzes specific tools based on all Instagram accounts, the fake accounts will throw the numbers off. While active accounts may use a specific function consistently, those fake accounts won’t and therefore the number of accounts that use this function will be skewed. So how reliable is Big Data actually?

The collecting of people’s online data is already controversial but to gather it just to get skewed results and wrong conclusions only stirs the pot. Although the problem seems almost too widespread for a quick fix, it should not be avoided. Boyd and Crawford also state, “Furthermore, the notion of an ‘active’ account is problematic…The very meanings of ‘user’ and ‘participation’ and ‘active’ need to be critically examined” (669). There needs to be a further examination by these bigger companies on how to make the data more accurate and credible. I have no quick answer on how to do this but others surely feel the same way, analyzing Big Data comes with its drawbacks. As Boyd and Crawford stated, “When researchers approach a data set, they need to understand — and publicly account for — not only the limits of the data set but also the limits of which questions they can ask of a data set and what interpretations are appropriate.” (669–670).

All in all, the issue of fake accounts has definitely caused many numbers and data sets to be inaccurate, which furthers the idea that Big Data is not reliable. So the next question to ask would be should we work on fixing Big Data or consider it unethical and abolish it completely? Even though this issue can only be resolved in time, the importance of it should not be hindered. Technology is being created and updated consistently and at a faster pace than ever before and the analysis on the ethics of technology is already farther behind than it should be. Not rushing to keep up the ethics with new and upcoming technology will only make the already extensive gap bigger.

Citations:

Goel, Vindu. (2014, Dec. 18). Millions of Fake Instagram Users Disappear in Purge. Retrieved February 12, from https://bits.blogs.nytimes.com/2014/12/18/millions-of-fake-instagram-users-disappear-in-purge/.

Danah Boyd & Kate Crawford. (2012) CRITICAL QUESTIONS FOR BIG DATA, Information, Communication & Society, 15:5, 662–679, DOI: 10.1080/1369118X.2012.678878.