In a just-published (online first) article for the journal Leadership, my co-author Martina Kohlberger and I applied a communication as constitutive of organizing (CCO) perspective in a case study to examine Twitter’s influence on the leadership dynamics in the 2019 Hong Kong Protests. We argue that Twitter is a powerful nonhuman leadership actor by demonstrating how it coordinates a plenum of co-participating agencies to construct meaningful narratives. In addition, we show that while many social movements call themselves leaderless, because of Twitter’s co-participation, they are not leadership-less. Using digital methods, we first harvested movement-relevant tweets based on hashtags and retweet counts from a key event of the protests, and then analysed the video content of the three most-retweeted tweets. Our analysis shows that Twitter’s various mechanisms dictate how online conversations unfold and that Twitter, therefore, influences how “authoritative text” is established. Our study contributes to the literature in three ways. First, we contribute to critical leadership studies by showing that Twitter is a leadership actor that enacts sociomaterial leadership, which further challenges the dominant human-centric and masculine views of leadership. In doing so, we reveal that the persistent leaderless movement narrative is a fantasy. Second, by illustrating how Twitter’s authorship mechanisms generate authority and polarity, we contribute to a stream of CCO studies showing that platforms influence power dynamics. Third, by attending to multivocality and dissensus, where a myriad of voices could speak up against the established and perceived injustice, we assert that Twitter as a leadership actor dictates specific modes of communication with performative effects.
Although the digital space offers many opportunities in terms of data collection, analysis and new data itself, part 3 of the series ” Thoughts on Digital Qualitative Research” addresses the challenges going hand in hand with digital research. Although each method and each research project may face other or additional questions and difficulties, the challenges presented here are valid for all scholars who aim to conduct digital qualitative inquiry.
The Nature and Quality of Data
The nature and quality of data are crucial for coherent and transparent interpretation. In early research, digital data often required grounding in the offline world to be seen as valid (Rogers, 2013). Although today not all data require grounding outside the digital sphere (Rogers, 2013) as they often describe natively digital phenomena, the methodological context is essential to understand the nature and meaning of the data analysed (Dicks, 2012). Quinton and Reynolds (2018) argue that researches have to define their stance but can freely classify their approaches in terms of methodology.
Part 2 of the series examines the emerging tensions and questions for qualitative research in a Big Data world.
Boyd and Crawford (2012) define the shift to Big Data as a socio-technical phenomenon. The term Big Data describes the huge amount of data aggregated through interaction online and the ability to cross-reference these large data sets for new insights. Discussing the troubling concept of data, Markham (2018) and Rogers (2013) argue that datafication as ideological focus and the methodological turn towards digital research techniques quantifying social processes pose a temptation as well as a challenge for qualitative research at the same time.
The technological ability to collect data does replace the question if qualitative oriented scholars should collect such large amounts of data (Tiidenberg, 2018), from an ethical as well as from a practical point of view (Markham, 2012). Further, these large data sets do not fully represent social phenomena (Markham, 2018), but Big Data changes the way knowledge is created and research is done by changing the instruments, the focus and the process of research (boyd & Crawford, 2012). Markham (2018, p. 520) sees the turn to the quantification in data analysis, the subsumption of qualitative inquiry as an add-on for data-driven science and the pursuit of generalizability as an “ongoing risk, which the interpretative movement has long sought to combat.”
In this short series about qualitative digital methods, I want to introduce basic assumptions, challenges and definitions for qualitative research in the digital space. The first part sheds light on the definition of digital research.
As Hine (2005) and Quinton and Reynolds (2018) state, there is no clear paradigm or restriction for digital research by now. Researchers try to adapt their methodological principles to the digital environment and migrate their ontological and epistemological views into the digital research field.
Recently, the increasing transdisciplinary importance of the digital has become obvious by a growing number of PhD projects, which address their respective questions from various theoretical and methodological perspectives. Across research centers, digitization poses new and relevant research questions and provides new sources of data for addressing them.
The Doctoral Program “Organizing the Digital: Relations, Publics, Societies” promotes transdisciplinary research on digital phenomena that bridges and transcends micro, meso and macro levels of analysis. The Doctoral Program thereby takes a multi-method and inter-disciplinary lens and advances conceptual research, driven by experimental, qualitative and interpretive studies, as well as related quantifications and network analyses.
The Doctoral Program assumes that its doctoral students meet the requirements of the respective curricula of the PhD/doctoral program in which they are enrolled. Additionally, students affiliated to the Doctoral Program #OrganizingtheDigital will attend specific courses focusing on topics of the DP and participate in different types of conferences in order to acquire and deepen presentation and academic discussion skills. Continue reading “Call for Applications: Doctoral Program »Organizing the Digital«”→