Political analysts may once have depended entirely on subjective attributes, such as ethics, charisma, and non-scientific impressions of the electorate to forecast elections, but with the rise of data generated from human daily interaction with software systems, it is possible to add meaningful data-driven attributes to political forecasting alongside all of the demographic information available to today’s political consultant. Big Data collected using internet-of-things devices, online social networks, large-scale surveys, search engine queries, and others can be very useful for forecasting or guiding winning candidates. This applies to fomenting and forecasting political unrest as well as predicting democratic election outcome, as recent work on empirically determining tipping points in influencing public opinion has shown.

Marketing companies and election consultants have long used sophisticated polling techniques in order to determine and shape public opinion so that candidates can use their findings to their advantage. In the last decade, however, we have seen well-known applications of large-scale data analysis in politics. For example, in 2008, President Obama’s campaign very effectively monitored and leveraged social media as an important part of his campaign strategy.