Holistic Twitter Research. Explorative study on the methods and practices, involved in the production of knowledge with social media data.
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With the establishment of social media sites as part of the daily life of online users, scholars in humanities and social sciences are raising the debate about the methods for researching these environments. The vast amount of data that derives from social networks challenges the established research techniques and invites academics to use software tools and algorithms as part of their practices of knowledge production. This thesis aims to contribute for the discussions on online research methods, by suggesting the concept of a holistic approach to the study of social media. This idea argues that data, online platforms and tools cannot be perceived as isolated objects, but as assemblages of heterogeneous agents. Employing this view, I build a case on research with data from the microblogging site Twitter, analysing the processes of knowledge-making afforded by the platform, the APIs, the database and the software tool for data visualisation Gephi. As a result of this empirical exploration, I argue that social interactions are inherently implicit and appropriated by Twitter users and thus, scholars need to develop tactics that would allow them to look beyond the logic of the database. Moreover, I show that social media research takes place on several levels and on each stage, the method of research is shaped by the actors. Thus, I argue that the concept of online research method cannot be confined within the traditional frames, but instead, it should be perceived as an evolving process, being in a state of constant flux, where heterogeneous actors influence the research decisions, mobilise traditional and new methods and negotiate the research choices of scientific exploration. The main argument of this thesis is that social media studies are not only a technological accomplishment, but should be understood as a complex holistic process.