Monday, December 17, 2012

Understanding the U.S. Media Coverage of the 2012 U.S. Presidential Election


The timeline chart (from the FDA's 2012 U.S. Election Media Study) captures the total media coverage of Obama and Romney, and in comparison to five major events in the last 32 days of the 2012 U.S. presidential election. In terms of overall coverage, Obama received an increase in coverage from four of the five key political events identified in the chart. As illustrated in the timeline chart, the FDA researchers observed declines in campaign coverage for each of the four weekend periods included in the study. These declines are the result of talk radio broadcasts not being aired on the weekends, and declines in campaign coverage during weekend periods for the press and television.

Obama received a more sustained increase in coverage and higher coverage from the 4th debate (or final 3rd presidential debate) than he received from Hurricane Sandy. In addition, Obama received the second highest daily coverage from the 3rd debate (or 2nd presidential debate). Obama had 192 data points compared to Romney's 162. During this period, the media attention was on Obama after his poor 1st debate performance and the Benghazi hearing. (The highest daily media coverage was on November 6th, Election Day.)

Only one day in this 32 day timeline of total media coverage did Romney eclipse the media coverage of Obama: October 10th—day of the Benghazi hearing. Romney had 138 data points compared to Obama's 126.

Data points refer to the media biases in the form of stories and information from the daily tracking by the FDA.

The correlation coefficient between Romney and Obama (based on total media exposure) is 0.97, meaning that the two move together in ALMOST a perfect, positive relationship.

A correlation coefficient can be in the range from minus 1, to positive 1. (A coefficient of zero means that there is no correlation, or no relationship at all).

A coefficient of minus one means that two sets of data (or two variables) are perfectly negatively correlated. This means that as one variable goes up, the other goes down in a precise and predictable relationship.

A coefficient of positive one means that two sets of data (or two variables) are perfectly positively correlated. This means that as one variable goes up, the other also goes up in a precise and predictable relationship.

FDA's 2012 U.S. Presidential Election Media Study







Mr. Stephen Garvey, Foundation for Democratic Advancement, Executive Director

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