Linear regressions are in nearly every paper I've read. The authors always model the response variable as a linear combination of independent variables without regards to how the data is actually generated. It seems like they only use linear regression because it can produce a table with CI of "influence" of each variable ($\beta$ in $y = \alpha + \beta x + \epsilon_i $).
I want to know reasons social scientists use linear regression this much.
Also, should I use a more opinionated model (with a better fit) if possible?