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Research papers, University of Canterbury Library

Social media have changed disaster response and recovery in the way people inform themselves, provide community support and make sense of unfolding and past events online. During the Canterbury earthquakes of 2010 and 2011 social media platforms such as Facebook and Twitter became part of the story of the quakes in the region, as well as a basis for ongoing public engagement during the rebuild efforts in Christchurch. While a variety of research has been conducted on the use of social media in disaster situations (Bruns & Burgess, 2012; Potts, Seitzinger, Jones, & Harrison, 2011; Shklovski, Palen, & Sutton, 2008), studies about their uses in long-term disaster recovery and across different platforms are underrepresented. This research analyses networked practices of sensemaking around the Canterbury earthquakes over the course of disaster response, recovery and rebuild, focussing on Facebook and Twitter. Following a mixed methodological design data was gathered in interviews with people who started local Facebook pages, and through digital media methods of data collection and computational analysis of public Facebook pages and a historical Twitter dataset gathered around eight different earthquake-related events between 2010 and 2013. Data is further analysed through discursive and narrative tools of inquiry. This research sheds light on communication practices in the drawn-out process of disaster recovery on the ground in connecting different modes of discourse. Examining the ongoing negotiation of networked identities through technologically mediated social practices during Canterbury’s rebuild, the connection between online environments and the city of Christchurch, as a physical place, is unpacked. This research subsequently develops a new methodology to study social media platforms and provide new and detailed information on both the communication practices in issue-based online publics and the ongoing negotiation of the impact of the Canterbury earthquakes through networked digital means.

Research papers, University of Canterbury Library

This poster presents work to date on ground motion simulation validation and inversion for the Canterbury, New Zealand region. Recent developments have focused on the collection of different earthquake sources and the verification of the SPECFEM3D software package in forward and inverse simulations. SPECFEM3D is an open source software package which simulates seismic wave propagation and performs adjoint tomography based upon the spectral-element method. Figure 2: Fence diagrams of shear wave velocities highlighting the salient features of the (a) 1D Canterbury velocity model, and (b) 3D Canterbury velocity model. Figure 5: Seismic sources and strong motion stations in the South Island of New Zealand, and corresponding ray paths of observed ground motions. Figure 3: Domain used for the 19th October 2010 Mw 4.8 case study event including the location of the seismic source and strong motion stations. By understanding the predictive and inversion capabilities of SPECFEM3D, the current 3D Canterbury Velocity Model can be iteratively improved to better predict the observed ground motions. This is achieved by minimizing the misfit between observed and simulated ground motions using the built-in optimization algorithm. Figure 1 shows the Canterbury Velocity Model domain considered including the locations of small-to-moderate Mw events [3-4.5], strong motion stations, and ray paths of observed ground motions. The area covered by the ray paths essentially indicates the area of the model which will be most affected by the waveform inversion. The seismic sources used in the ground motion simulations are centroid moment tensor solutions obtained from GeoNet. All earthquake ruptures are modelled as point sources with a Gaussian source time function. The minimum Mw limit is enforced to ensure good signal-to-noise ratio and well constrained source parameters. The maximum Mw limit is enforced to ensure the point source approximation is valid and to minimize off-fault nonlinear effects.