Travis Noakes ^* Corrie Susanna Uys Patricia Ann Harpur Izak van Zyl

• Cape Peninsula University of Technology, Cape Town, South Africa

Big Data communication researchers have called for qualitative analysis of online science conversations to better explore their meaning. A scholarly gap exists regarding the role that such methods might play in researching small data regarding micro-bloggers' science article communications. While social media attention assists with article dissemination, qualitative research into related microblogging practices is scant. In response to these gaps, this paper explores how qualitative analysis can contribute to Science Communication studies on microblogging articles. Calls for the qualitative analysis of such communications are supported by a practical example: An inter-disciplinary team applied mixed methods to better understand an unorthodox, but popular, article's promotion via Twitter over two years. Big Data studies describe patterns in micro-bloggers' activities from large sets of data. In contrast, this small data set was analysed in NVivo™ by a pragmatist, and in MAXQDA™ by a statistician. The pragmatist's multimodal content analysis found that health professionals shared links related to the article. Its popularity related to its position as a communication event within a longstanding debate in the Health Sciences.Dissident professionals shared this article to support their emergent paradigm. The article's tweeters followed a myriad of practices, such as language localisation in translating a title from English to Spanish. A semantic network analysis confirmed that terms used by the article's tweeters related strongly to the article's content, and its discussion was pro-social. Meta-inferences were then derived from the two methods' claims. These findings flagged the importance of contextualising a health science article's sharing in relation to tweeters' professional identities and stances on what is healthy. In addition, meta-critiques spotlighted challenges with preparing accurate tweet data, and their analysis via qualitative data analysis software. Such findings suggest the valuable contributions that qualitative research can make to research with microblogging data in science communication. New studies can critique this rationale or explore microblogging of key articles within important scientific debates.