How to interpret Difference-in-Differences results?

I'm relatively new at working with R, so I have some issues with interpreting my results. My goal is to analyse the vote share of left-wing parties in 4 countries after 2008 by using difference-in-differences. How do I correctly interpret these results?

My code is:

votedata$time = ifelse(votedata$year >= 2008, 1, 0)
votedata$treated = ifelse(votedata$country == "GB" | 
                           votedata$country == "FR" | 
                           votedata$country == "IT" |
                           votedata$country == "ES", 1, 0)

votedata$did = votedata$time * votedata$treated

regression = lm(votedata$voteshare ~ time + treated + did, data = votedata)
summary(regression)
voteshare

time 13.12*
(6.91)

treated 20.33***
(5.53)

did -16.24*
(9.07)

Constant 11.10**
(4.33)

Observations 69
R2 0.18
Adjusted R2 0.14
Residual Std. Error 17.85 (df = 65)
F Statistic 4.76*** (df = 3; 65)
Note: *p<0.1; **p<0.05; ***p<0.01

Looks like the effect of being in one of those 4 countries after 2008 was to decrease the share by 16.