Purpose The interest in life cycle assessment (LCA) studies has increased over the years, and one of the main ways of disseminating these studies is through the publication of articles in scientific journals. Coauthorship relations form a social network where it is possible to identify how research is organized and structured in a specific field of knowledge. This paper aims to show the spread of these studies and the configuration of a collaboration network based on coauthorship relations between researchers of LCA considering some properties of social networks. Methods The research was based on a bibliometric approach of 1,386 articles related to LCA and published in journals indexed in the ISI/Web of Science until 2008. A free software, Pajek, which has been largely used for the representation and analysis of social networks, was employed in this work. The properties of social networks analyzed in this study were power law, degrees of separation, giant component, and clustering. Results and discussion The research showed a social network formed by 2,598 authors from 60 countries, 88% of coauthored articles, a mean of 1.87 authors per article; the distribution of articles per author follows a power law (f (z)= 2,134.3×z −2.544 ) with a high regression coefficient (R 2 = 0.9704), a degree of separation of 6.5, a giant component embracing 37% of the authors, and a clustering coefficient of 0.75. The LCA coauthorship network has properties following power law patterns similar to other nets such as WWW. The community forms a giant component which is still small, but which, nevertheless, might experience considerable growth in the near future. The average distance between authors follows the smallworld hypothesis. The clustering degree was also coherent with other scientific communities. Conclusions In spite of being an area with less than 20 years of publications registered in the ISI/Web of Science, LCA is now experiencing fast dissemination involving a large number of articles, authors, and institutions. The LCA's coauthorship network can be characterized as a scientific community with properties verified in other networks of more consolidated academic collaboration.