In the days just after the GOP retook the Senate last November, Americans were evenly split as to which party they thought was more extreme. They now say by an 8-point margin that Republicans are further from the mainstream.
Half of Americans now say the GOP is too extreme, up 7 points since November. The percentage saying Democrats are too extreme, which has remained relatively steady, is currently 39 percent.
Forty-eight percent of independents now say the GOP is too extreme, up 9 points from last year. The percentage of Republicans calling their own party too extreme also rose by 6 points.
One thing hasn't changed: Most Americans still want members of both parties to work together. Fifty-six percent say that Republicans should compromise some of their positions to work with Democrats, rather than stick to their positions and risk not coming to an agreement, while 68 percent say Democrats in Congress should compromise.
While most Democrats think their leaders should compromise, Republicans support a harder-edged approach, with 58 percent saying their congressional representatives should stick to their positions. Independents say that both sides should work together.
The HuffPost/YouGov poll consisted of 1,000 completed interviews conducted April 25-27 among U.S. adults using a sample selected from YouGov's opt-in online panel to match the demographics and other characteristics of the adult U.S. population.
The Huffington Post has teamed up with YouGov to conduct daily opinion polls. You can learn more about this project and take part in YouGov's nationally representative opinion polling. Data from all HuffPost/YouGov polls can be found here. More details on the poll's methodology are available here.
Most surveys report a margin of error that represents some, but not all, potential survey errors. YouGov's reports include a model-based margin of error, which rests on a specific set of statistical assumptions about the selected sample, rather than the standard methodology for random probability sampling. If these assumptions are wrong, the model-based margin of error may also be inaccurate. Click here for a more detailed explanation of the model-based margin of error.