Do Smear Campaigns work?

Group members: Michelle Thomas, Reem Alfaiz, Andrew Mikofalvy

The data shows the effectiveness of negative ad campaigns as well as their tendency to be used as a last resort in gaining support and lowering support for competitors. We wanted to tell this story because of the over saturation of campaign ads and curiosity over the effectiveness of negativity.

We used data from the Politcal TV Ad Archive to look at which candidates negative ads were targeting as well as when they were being published. We compared those findings to voter results in each primary and caucus from data from the New York Times. We chose to tell this story through a line graph representing voter results overlayed with a bar graph depicting air count of negative ads per candidate. Both graphs are plotted over the time frame of February 1st- March 1st. This is the date of the first caucus until Super Tuesday, a day in which 12 states and 1 territory hold their primaries and caucuses. This layout allows people to see the race between candidates and relate it to when campaigns chose to start using negative ads, as well as if the candidates they target did worse or not. We felt that this is an effective time frame as Super Tuesday is a large sample of voting results and holds a perceived weight for campaign success. We chose to use delegates won as the measure for candidate success since it factors in issues such as relative importance of states, since negative ads were shown more in some states than others. We also included explanatory text so that the chart is understandable regardless of political system education.

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Data Log Michelle 2.8.16

  1. Android smartphone (calls and texts) | data logged by phone software/at&t
  2. checked gmail |  content specific info by google
  3.  took multiple busses |location and charlie card data logged by mbta
  4. tapped ID to get into massart building |student ID # recorded, time, location
  5. tapped ID to get into massart print shop | student ID # recorded, time, location
  6. sent in my taxes | tax info/ ID info recorded by federal, state goverments and turbotax
  7. checked voter registration | ID info recorded on gov website
  8. bought theater ticket| credit card information/ email contact into recorded by ticketmaster
  9. listened to pandora | likes, dislikes, skips recorded by pandora to track and personalize stations
  10. browsed internet | data recorded on what I look at to better advertise to me
  11. facebook | data collected to better advertise to me
  12. watched tv | viewership data collected by networks
  13. bought curtains on amazon | credit card and shipping info collected by amazon

Fact Checking Politicians

The New York times recently put out a chart rating each presidential candidate for their accuracy of statements. The statements were grouped into six categories, ranging from pants-on-fire lies to true. The post is aimed at a wide audience, from adults who are trying to choose a candidate to the candidates and their teams. With this graph the New York Times both urges average citizens to think more critically about what candidates say and pushes candidates into having to be more careful with the way they present data.

truth-lies

New York Times article- All Politicians Lie.

The chart on a whole is relatively clear and easy to read. The color scheme chosen both helps to differentiate between true and false and I appreciate that the author steered clear of loaded colors within the two party system. It is easy to find general summary information located along the left and right side, and to get a sense of the candidates general ranking. However, there are a few problems with this representation. The first being that, although the criteria used to place statements into categories is listed, it is still a pretty arbitrary metric. In addition, some of the candidates have vastly more statements that have been checked, and this information is not presented clearly.

I feel as though this presentation is effective in sparking an interest people to fact check candidates and think more critically about what they are saying. There has also been a strong response in campaigns around fact-checking journalism. The graph uses humor (title of categories) as a way to engage readers, however, I also feel that this takes away some legitimacy of the information being delivered, which is exactly what the chart is trying to fix.