Barrett, The Honors College Thesis/Creative Project Collection
Barrett, The Honors College at Arizona State University proudly showcases the work of undergraduate honors students by sharing this collection exclusively with the ASU community.
Barrett accepts high performing, academically engaged undergraduate students and works with them in collaboration with all of the other academic units at Arizona State University. All Barrett students complete a thesis or creative project which is an opportunity to explore an intellectual interest and produce an original piece of scholarly research. The thesis or creative project is supervised and defended in front of a faculty committee. Students are able to engage with professors who are nationally recognized in their fields and committed to working with honors students. Completing a Barrett thesis or creative project is an opportunity for undergraduate honors students to contribute to the ASU academic community in a meaningful way.
Partial differential equation (PDE) models are widely used for modeling processes in the physical sciences, economics, and sociology, but are otherwise new to the realm of social media. They allow researchers to construct a single spatiotemporal mathematical model to predict, in the case of this study, the level of information…
Partial differential equation (PDE) models are widely used for modeling processes in the physical sciences, economics, and sociology, but are otherwise new to the realm of social media. They allow researchers to construct a single spatiotemporal mathematical model to predict, in the case of this study, the level of information saturation at particular points in space at specific times. Utilizing data from the popular social network Twitter, this study presents a preliminary work looking into the effects of aggregating spatial data on such a PDE model. In other literature, the source of analytical and statistical bias that results from arbitrary spatial aggregation is known as the modifiable areal unit problem (MAUP). We use a previously-studied dataset from the 2011 Egyptian revolution for simulation, and group data points using several distance metrics based on geographical location and geo-cultural similarity. This paper will attempt to show that a PDE model, necessarily dependent upon aggregating data, is subject to significant bias when said data are arbitrarily organized and grouped for simulation. We look primarily into the zoning problem, which amounts to maintaining a fixed number of regions located in different areas across the globe, but make note of the scale problem, an inherent issue in PDE modeling that results from aggregating data points into increasingly larger regions. From looking at specific values from each simulation, this study shows that such a model is not free from the MAUP and that consideration of how data are aggregated needs to be made for future studies. In addition, it also suggests that geo-political and geo-cultural spatial metrics generate better diffusive patterns for tweet propagation than do simple geographical proximity metrics.
