Gender Differences in Emotional Responses to Hooking Up

The present research looked to explore the relationship between the emotional responses of college students to different hooking up behaviors. Seven hundred and nine undergraduates participated in a web-based survey that included a demographic questionnaire, SDS, PANAS, AUDIT, and a measure of hooking up. This measure examined the frequency with which they participated in eight different types of hooking up varying by degree of familiarity to their hook partner and whether or not the hook up was coital or non-coital, as well as their emotional responses to the behavior and their perception of the emotional responses of their partner. Results showed that both menand women experienced more positive emotional responses to hooking up behaviors than negative emotional responses. Men experienced significantly more positive emotional responses to hook up behaviors than did women. Women experienced significantly more negative emotional responses for hook ups that were coital with strangers than did men, while men experienced more positive emotional responses for hook ups that were coital with strangers, coital with acquaintances, and coital with partners that were previous romantic partners than did women. Men also experienced more positive emotional responses for hook ups that were non-coital with strangers and non-coital withacquaintances. Men tended to rate their partner’s positive emotional responses higher than what women reported experiencing, particularly for hook ups with less familiar partners. Women’s ratings of their partner’s negative emotional responses were lower than what men actually reported experiencing. The data collected provide several opportunities for future analyses to be conducted and this research will add to the relatively small body of literature on hooking up.

Visualization Techniques For The Analysis Of Network Simulation Results

The Simulation Automation Framework for Experiments (SAFE) streamlines the de- sign and execution of experiments with the ns-3 network simulator. SAFE ensures that best practices are followed throughout the workflow a network simulation study, guaranteeing that results are both credible and reproducible by third parties. Data analysis is a crucial part of this workflow, where mistakes are often made. Even when appearing in highly regarded venues, scientific graphics in numerous network simulation publications fail to include graphic titles, units, legends, and confidence intervals. After studying the literature in network simulation methodology and in- formation graphics visualization, I developed a visualization component for SAFE to help users avoid these errors in their scientific workflow. The functionality of this new component includes support for interactive visualization through a web-based interface and for the generation of high-quality, static plots that can be included in publications. The overarching goal of my contribution is to help users create graphics that follow best practices in visualization and thereby succeed in conveying the right information about simulation results.