Elections are a pillar of American democracy. But for many Americans today, our democratic process feels under siege.
A divided electorate and intense partisanship have led to a tense public mood where feelings of polarization run deep. People are now more attached to their party affiliation than any other social identifier – like race and religion – according to Stanford scholar Shanto Iyengar. He argues that this only amplifies polarization further.
Meanwhile, the internet has changed how information – essential to a healthy democracy – is being shared.
Reports of fake news, propaganda from the United States and abroad and algorithms deciding what information we see has led some people – including Stanford Law Professor Nathaniel Persily – to question what can influence democratic processes in the age of the internet.
In addition, the surprise victories in the last election spurred a debate about how information about the American electorate is gathered as well as the ways in which it is covered in the media.
As the 2018 U.S. midterm elections approach, how can we better understand how these issues affect politics and decision-making today? Stanford scholars from across the social and political sciences are working together to explain how these processes unfold.
A country divided?
The American public believes that it has polarized. But according to Stanford political scientist Morris P. Fiorina, political attitudes look much like they did in the 1970s and 1980s – well before polarization was widely discussed in political discourse.
Instead, said Fiorina, what Americans see is partisan sorting by their elected officials.
Political party affiliation has become the most distinctive part of a person’s identity today, said political communication scholar Shanto Iyengar, and succeeds all other identifiers, like race, religion or ethnicity.
What led to Americans feeling so polarized, and passionately so? How is polarization perpetuated? Here are Stanford scholars’ research about this phenomenon:
News in the age of the algorithm
One defining issue that emerged from the 2016 election, and salient again in 2018, is ensuring that the flow of information that contributes to a healthy democracy is not a hoax or “fake news” – false information usually intended for political or commercial advantage.
Stanford researchers have been studying the prevalence of “fake news,” as well as understanding the ways in which information spreads in the digital media age, such as personalized algorithms and clickbait headlines. Some Stanford faculty are also exploring ways to help news and tech industries deal with these challenges.
Here are Stanford scholars’ work on this issue:
The political horse race
During election season, it is common to see blow-by-blow coverage about the popularity between two candidates: How many points is she ahead? Who is slipping behind? Can he pull a surprise lead on election night?
Also known as horse race journalism, these stories tend to focus more on polling data than policies, competition than competence. According to research by Stanford scholars, there are spillover effects when viewing elections through a lens of polling popularity.
Here are some findings on the predicaments and unintended consequences of election forecasting: