impact of old reviews on new reviews I am working on e-commerce, how to rank smartphones in the same category. I want to calculate a weighted average of sentiment score from reviews posted by buyers.

Weights will be based on how many days before review was posted, as people might give more importance to recent reviews than old reviews. Now to find weight for previous day review, i want to understand impact of previous reviews on current review. i.e. impact of t-1, t-2, t-3 on t.

I want to know for how many days should i aggregate review sentiment?
Welcome to DataScience.SE. Let's see if I've interpreted your question correctly:


  i want to understand impact of previous reviews on current review


Keep track of which reviews a reviewer has read (randomly withhold some if you have to), and use this information together the rating of the new review to create a regressor to estimate the score of a new review given the age and score of selected previous reviews.

You can do similar regressions with the topic and sentiment, if you use embeddings.