Just keep in mind an R^2 of 15 isn't that high, so these variables are only accounting for a small portion of the variance in the model.
I think there's an important control here: number of followers per user. It'd be interesting to see how followers would affect the model, especially because you could assume that "knowing to add more hashtags" likely correlates with "use of the platform," which they likely correlates with "increased # followers," who can then produce more likes on each photo.
EDIT: Another thought: if you're looking at # likes, you might want to go for a negative binomial model instead of an OLS regression, because it'll account for the dependent variable being a "count" measure.
I think there's an important control here: number of followers per user. It'd be interesting to see how followers would affect the model, especially because you could assume that "knowing to add more hashtags" likely correlates with "use of the platform," which they likely correlates with "increased # followers," who can then produce more likes on each photo.
EDIT: Another thought: if you're looking at # likes, you might want to go for a negative binomial model instead of an OLS regression, because it'll account for the dependent variable being a "count" measure.