Browsing by Author "Andalib, Maryam Alsadat"

Now showing 1 - 2 of 2
  • Thumbnail Image
    Analysis of Information Diffusion through Social Media
    Khalili, Nastaran (Virginia Tech, 2021-06-16)
    The changes in the course of communication changed the world from different perspectives. Public participation on social media means the generation, diffusion, and exposure to a tremendous amount of user-generated content without supervision. This four-essay dissertation analyzes information diffusion through social media and its opportunities and challenges through management systems engineering and data analytics. First, we evaluate how information can be shared to reach maximum exposure for the case on online petitions. We use system dynamics modeling and propose policies for campaign managers to schedule the reminders they send to have the highest number of petition signatures. We find that sending reminders is more effective in the case of increasing the signature rate. In the second essay, we investigate how people build trust/ mistrust in science during an emergency. We use data analytics methods on more than 700,000 tweets containing keywords of Hydroxychloroquine and chloroquine, two candidate medicines, to prevent and cure patients infected with COVID-19. We show that people's opinions are concentrated in the case of polarity and spread out in the case of subjectivity. Also, they tend to share subjective tweets than objective ones. In the third essay, building on the same dataset as essay two, we study the changes in science communication during the coronavirus pandemic. We used topic modeling and clustered the tweets into seven different groups. Our analysis suggests that a highly scientific and health-related subject can become political in the case of an emergency. We found that the groups of medical information and research and study have fewer tweets than the political one. Fourth, we investigated fake news diffusion as one of the main challenges of user-generated content. We built a system dynamics model and analyzed the effects of competition and correction in combating fake news. We show that correction of misinformation and competition in fake news needs a high percentage of participation to be effective enough to deal with fake news.
  • Thumbnail Image
    Model-based Analysis of Diversity in Higher Education
    Andalib, Maryam Alsadat (Virginia Tech, 2018-07-03)
    U.S. higher education is an example of a large multi-organizational system within the service sector. Its performance regarding workforce development can be analyzed through the lens of industrial and systems engineering. In this three-essay dissertation, we seek the answer to the following question: How can the U.S. higher education system achieve an equal representation of female and minority members in its student and faculty populations? In essay 1, we model the education pipeline with a focus on the system's gender composition from k-12 to graduate school. We use a system dynamics approach to present a systems view of the mechanisms that affect the dynamics of higher education, replicate historical enrollment data, and forecast future trends of higher education's gender composition. Our results indicate that, in the next two decades, women will be the majority of advanced degree holders. In essay 2, we look at the support mechanisms for new-parent, tenure-track faculty in universities with a specific focus on tenure-clock extension policies. We construct a unique data set to answer questions around the effectiveness of removing the stigma connected with automatic tenure-clock policies. Our results show that such policies are successful in removing the stigma and that, overall, faculty members that have newborns and are employed by universities that adopt auto-TCE policies stay one year longer in their positions than other faculty members. In addition, although faculty employed at universities that adopt such policies are generally more satisfied with their jobs, there is no statistically significant effect of auto TCE policies on the chances of obtaining tenure. In essay 3, we focus on the effectiveness of training underrepresented minorities (e.g., African Americans and Hispanics) in U.S. higher education institutions using a Data Envelopment Analysis approach. Our results indicate that graduation rates, average GPAs, and post-graduate salaries of minority students are higher in selective universities and those located in more diverse towns/cities. Furthermore, the graduation rate of minority students in private universities and those with affirmative action programs is higher than in other institutions. Overall, this dissertation provides new insights into improving diversity within the science workforce at different organizational levels by using industrial and systems engineering and management sciences methods.