Blockchain (BC) technology is gaining momentum in a variety of application domains, beyond finance. We present a text mining literature analysis of a body of published articles queried in the Scopus database, regarding BC technology and consumer trust. We applied a semiautomated text mining and topic modelling approach: we mix top-down and bottom-up procedures to align the existing literature on BC taxonomies with the gathered article’s list of keywords; we then feed automatically the latent Dirichlet allocation (LDA) algorithm to uncover relevant topics enabling to analyse the existing body of knowledge. Our analysis highlights the multidisciplinary nature of BC research within consumer trust. Among others, findings show pertinent aspects to consumer trust, such as traceability and privacy, are receiving only marginal attention from scholars. Our analysis also reveals the marketing, social and economic sciences’ researchers should devote efforts to the application of BC and its impact to consumer trust. We provide future research trends we deem crucial to be addressed regarding sustainable blockchain trustability.

--

Blockchain,Consumer trust,Consumer transparency,Privacy,Literature analysis,Topic modelling

• Ciências da Computação e da Informação - Ciências Naturais