Introduction: Addiction, which has recently attracted the attention of researchers, is a serious problem worldwide. The growth of relevant literature contributes to a better understanding of this problem and improves the interaction between executive organizations and academic institutions. It is important to identify the active subject areas within this field and to explore the topics which are more frequently discussed in research documents using techniques of subject clustering analysis. The main purpose of this paper is to do a content analysis of papers related to addiction in PubMed through hierarchical clustering.

Methods: This is a descriptive and applied research analyzing the content of literature through hierarchical clustering. To obtain data, a search for the keyword “Addiction” as a Mesh term in PubMed was conducted, on 21/04/2015, for papers published in 1991-2014. Descriptors were extracted from the papers retrieved, and data were analyzed using Ravar Matrix and SPSS ₂₀.

Results: According to the findings, the size of scientific literature in the area of addiction increased during the period under the study. Subject clustering led to the identification of most widely used topics, including substance related disorders, addictions to the Internet, gambling, smoking, etc.

Conclusion: Through thematic analysis of documents (descriptors), a wide range of dispersed topics were grouped into six clusters.  The members of each cluster had common characteristics and they were structurally interrelated. The main concern of researchers, as indicated by descriptors in these six clusters, were on psychological aspects of the issue.