Investigating and Supporting Sensemaking within Online Health Communities

This dissertation focuses on understanding and supporting individual and collective sensemaking within online health communities (OHCs). This major goal was achieved in three aims. In Aim 1, this dissertation contributes a rich descriptive account of collective sensemaking in OHCs forums by describing how it occurs and develops, what triggers it, what elements constitute collective construction of meaning, and what conversational moves positively contribute to this process. Further, it describes how collective sensemaking in OHCs is impacted by the interplay between informational and socio-emotional needs of OHCs members. Moreover, it examines how design of different social computing platforms influences OHCs members’ ability to meet their informational and socio-emotional needs and engage in collective sensemaking. In Aim 2, this dissertation explores the design space of tools for supporting individual sensemaking through optimized information access. Through the design and evaluation of a prototype DisVis it examines the impact of such tools on OHCs members’ ability to understand information within discussion threads. In the final Aim 3, this dissertation proposes a novel approach for meeting the three main needs identified in Aims 1 and 2: promoting individual sensemaking, while at the same time encouraging collective sensemaking, and facilitating development of social awareness and ties among community members. The design and evaluation of the novel solution for visualizing discussion threads that synergistically addresses these three needs—dSense—provides insights for future research and design of interactive solutions for supporting individual and collective sensemaking within OHCs

Argumentation in biology : exploration and analysis through a gene expression use case

Argumentation theory conceptualises the human practice of debating. Implemented as computational argumentation it enables a computer to perform a virtual debate. Using existing knowledge from research into argumentation theory, this thesis investigates the potential of computational argumentation within biology. As a form of non-monotonic reasoning, argumentation can be used to tackle inconsistent and incomplete information - two common problems for the users of biological data. Exploration of argumentation shall be conducted by examining these issues within one biological subdomain: in situ gene expression information for the developmental mouse. Due to the complex and often contradictory nature of biology, occasionally it is not apparent whether or not a particular gene is involved in the development of a particular tissue. Expert biological knowledge is recorded, and used to generate arguments relating to this matter. These arguments are presented to the user in order to help him/her decide whether or not the gene is expressed. In order to do this, the notion of argumentation schemes has been borrowed from philosophy, and combined with ideas and technologies from arti cial intelligence. The resulting conceptualisation is implemented and evaluated in order to understand the issues related to applying computational argumentation within biology. Ultimately, this work concludes with a discussion of Argudas - a real world tool developed for the biological community, and based on the knowledge gained during this work