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How Facebook’s Psychological Parsing Practices Will Reshape Targeted Ads

https://www.wired.com/story/facebooks-targeted-ads-are-more-complex-than-it-lets-on/

The rise of big data and the sheer amount of information social media platforms are able to collect on its users have significantly changed the nature of advertisements and more specifically, targeted ads. One of the new advertising techniques made possible by overt data collection is the over-segmentation of user data. This leads to very unfortunate practices, such as the documented case of cigarette companies marketing tobacco ads to low-income people, based on a confluence of related categories of “user interest” data. These may or may not even be subject areas you directly navigated to, however just by belonging to additional groups may prompt advertisers to market to you based on the characteristics of your group.

Facebook continues to emphasize the transparency in this data collection process and the user’s ability to adjust their ad preferences. In the Wired piece linked above, the author encourages readers to see the information Facebook has collected about you by navigating to the bottom of the screen and clicking through Your Information > Your categories. However, this still doesn’t change the nature of data collection online and even less is known about how these categories are generated in the first place.

In addition, Facebook’s new practice of psychological parsing turns the existing advertisement system on its head yet again. Repeated reports by Bloomberg and The Intercept have shown that Facebook is able to leverage additional information to help refine and adjust targeted ads for advertisers through looking at user emotion. Based on the range of posts and online engagement, Facebook is able to make fairly correct assessments on consumers’ future behavior, which could have very large implications for advertisement industry.

In this manner, Facebook can create a much more efficient matching market that can create more effective valuations for their advertisement slot not only based on the market research that advertiser’s produce in their valuation. Facebook is able to provide additional information that can suggest a more precise pairing. For example, similar to other digital platforms and search engines like Google, Facebook runs an instant digital auction for each ad placement. However, while bid prices are a factor of consideration, Facebook also assess the relevance of the ad in that situation and this could potentially reduce the bid price necessary to win.

This type of data aggregation becomes problematic when the behavioral prediction exploits vulnerabilities in user’s emotions based on information collected from network engagement and displays ads specifically targeting when users are about to make critical choices such as changing product brand or subscriptions.

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