Algorithm 1.

Shifter Effect Learning

Input: review documents 𝒟, a vector of quantified effects ft−1, review feature matrix W, parameters matrices Θ, P, Q, common sentiment words Σc
for each review r in 𝒟 do
	for each shifter w in Σs do
		Identify sentiment contexts Cw of w in r
		Identify the single modified words in Cw and the words must be in Σc
		Construct shifter features in xr by Eq. (7)
Solve Eq. (9) for f*
Return: a vector of quantified effects f*, which serves as ft for next iteration