1. A computer-implemented method of providing a structured topic drift for a displayed set of user comments on an article, the method comprising: determining, using at least one processor, an ordered sequence of topical recommendations based on one or more properties of the displayed set of user comments and user characteristics using a sequential recommendation model, wherein each topical recommendation contains a plurality of user comments; sampling, using the at least one processor, each of the topical recommendations in the ordered sequence to produce a first set of one or more user comments for each of the topical recommendations; appending, using the at least one processor, one by one, the user comments from the first set of one or more user comments for each of the topical recommendations to bottom of the displayed set of user comments; and updating, using the at least one processor, the sequential recommendation model based on a user response to the first set of one or more user comments for each of the topical recommendations; determining, using at least one processor, a second ordered sequence of topical recommendations using the sequential recommendation model; sampling, using the at least one processor, each of the topical recommendations in the second ordered sequence to produce a second set of one or more user comments for each of the topical recommendations; and appending, using the at least one processor, one by one, the second set of one or more user comments for each of the topical recommendations to bottom of the displayed set of user comments.
6. The method as claimed in claim 1 , wherein the one or more user comments for each of the topical recommendations are sampled based on a ranking.