Dummy interaction term in multivariate regression in ggplot
===

I want to show two graphs for a dummy-interaction term in ggplot.

My code is 

"
plot3<-ggplot (tobit, aes(issue_ideology_pre, issue_ideology_post, colour=factor (real_liberal_exposure) ))

plot3<-plot3+stat_smooth(method="lm", formula = "y~x",   
aes (fill=factor (real_liberal_exposure)), na.rm=T,alpha=0.3, size=0.5)


plot3<-plot3+scale_colour_manual(values=c("darkgrey", "blue"),name="Started liberal selective Exposure",
                               labels=c("no", "yes"), breaks=c(0,1))

plot3<-plot3+scale_fill_manual(values=c("darkgrey", "blue"),name="Started liberal selective Exposure",
                             labels=c("no", "yes"), breaks=c(0,1))



plot3<-plot3+scale_y_continuous (lim=c (1.00, 5), breaks=1:5)+scale_x_continuous (lim=c (1.00, 5), breaks=1:5)
plot3<-plot3+xlab ("Issue-Ideology at t-1")+ylab ("Issue-Ideology at t")
"


I have stored all the independent variables in x (minus the interaction) and the dependent variable in y.

I know that there is an easy way to show interaction effects with "effects", but in my opinion the ggplot solution should have two different regressions as an output, one with selectively exposed and one with non-exposed. 

However, when I remove the formula from the plot-coding, and thus run just a regression based on the bivariate regression, the result is the same.

Is there any explanations for that, or am I missing something?