This paper proposes an approach to capturing and reviewing scientific literature addressing latent topics across multiple scientific fields. As latent topics like moral values are affected by word polysemy and synonymy, a traditional keyword-based approach is often ineffective and therefore inappropriate. As a result, scientific literature addressing latent topics tends to be fragmented thereby constraining efforts to address similar and complementary research challenges. A novel approach to reviewing the literature by utilizing both semantic fields and probabilistic topic models has therefore been developed. We illustrate this approach by reviewing the literature addressing the value justice in the energy sector and compare this with a regular keyword-based approach. The new approach results in a more complete overview of the relevance of energy justice as compared to the traditional keyword-based approach. This novel approach can be applied to other latent topics including other values or phenomena such as societal resistance to technologies, thereby leading to an increased understanding of existing relevant literature and the identification of new areas of research.

Original languageEnglish
Pages (from-to)2111-2128
Number of pages18
JournalApplied Energy
Publication statusPublished - Oct 2018

    Research areas

  • Energy sector, Justice, Latent topics, Moral values, Probabilistic topic models, Semantic fields

ID: 46363602