This paper explores the premise whether sophisticated algorithms that drive curatorship of content for consumers consider a symbolic interactionist perspective on consumer desire for content and whether content offerings, personalisation and the consequent shaping of curatorship algorithms can be based on such an understanding. Curatorship of online content, whether this be product or information based, drives value, consumer engagement and profitability. Curatorship and recommender systems also deliver a personalised experience of the product or services. A review of the reasoning behind such systems reveals that most follow an empirical perspective, namely, the use of statistical tools and information systems algorithms on a behavioural dataset. A theoretically driven approach appears to be lacking. This paper seeks a theoretical approach to online content curatorship embedded in symbolic interactionism. In addition, it seeks to tease out the approach to one that embraces both notions of content curation based on similarity but also on a desire for difference and change. The paper looks at symbolic interactionism in the context of social and individual selves, its role in collaborative filtering, advances a set of propositions for a curation and collaborative filtering model and ends with the possible implications for marketing.