The Decision-Making Logic of Big Data Algorithmic Analytics
The Decision-Making Logic of Big Data Algorithmic Analytics

Summary/Abstract: We inspect the relevant literature on the decision-making logic of big data algorithmic analytics, providing both quantitative evidence on trends and numerous in-depth empirical examples. Building our argument by drawing on data collected from Pew Research Center, we performed analyses and made estimates regarding % of users who say they frequently/sometimes see on social media posts that are overly dramatic or exaggerated/people making accusations or starting arguments without having all the facts/posts that teach you something useful you had not known before/posts that appear to be about one thing but turn out to be about something else and % of users who say, after being directed to view their Facebook “ad preferences” page, that they did not know Facebook maintained this list of their interests and traits/they are not comfortable with Facebook compiling this information/the listings do not very or at all accurately represent them. Data collected from 4,200 respondents are tested against the research model by using structural equation modeling.

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