Introduction: This paper deals with what academic texts and datasets are referred to and discussed on Twitter. We used document object identifiers as references to these items. Method: We streamed tweets from the Twitter application programming interface including the strings "dx" and "doi" while simultaneously streaming tweets posted by and to the authors of the tweets captured. By doing so we were able to capture tweets referring to a digital object as well as the replies to these tweets. Analysis: The captured tweets were analysed in different ways, both quantitatively and qualitatively: 1) Bibliometric analyses were made on the digital object identifiers, 2) the thirty of these most mentioned and retweeted were analysed and 3) the conversations with at least ten tweets were analysed using content analysis. Results: Research from the natural sciences was most prominent, as was research published in open access journals. Different types of conversations relating to the digital objects were found, both when looking at them qualitative and their visual structure in terms of nodes and arcs. The conversations involved academics but were not always academic in nature. Conclusions: Digital object identifiers were mainly referred to for self-promotion, as conversation starters or as arguments in discussions.