Charging The Net: Social Activism in Women's Professional Tennis

This dissertation is an analysis of social activism within women’s professional tennis. In the 46 years since the women known as the Original 9 began protesting against the pay inequality between men’s and women’s tennis, subsequent cohorts of women have brought different issues and concerns to women’s tennis, expanding its scope and efforts.  Using qualitative research, including interviews with former players and press conference participation at tournaments to access current players, this study shows the lineage of social activism within women’s tennis and the issues, expressions, risks and effects of each cohort. Intersectionality theoretically frames this study, and analyses of performativity appears regularly. Each generational cohort is a chapter of this study. The Original 9 of the Movement Cohort fought for equal prize money. The Bridge Cohort, the era of Evert and Navratilova, continued the Movement Cohort’s push for equal prize money; however, they also ushered in identity politics (including gender, sexuality, and nationality, but with the notable exception of race). The Professional Cohort, the current era, followed the Bridge Cohort and is characterized by its focus on corporatization and mass-marketing. As such, there is a focus among the players on individualism which can seem like a lack of social activism is occurring. However, race, neglected during the Bridge Cohort, emerged during the Professional Cohort. The individualism of this cohort made space for Blackness to show unapologetically, though, within certain constraints. Finally, a few players are working on social justice issues in society at large, as well as trying to institute change within women’s tennis. These players make up the Post-Professional Cohort (or, as Pam Shriver from the Bridge Cohort calls them, “Bridge Throwbacks”).  This study shows the evolution of social activism within women’s tennis, as it reflects larger social change. Though bound together as one unified body, the social activism engaged in by each generation focused on different issues, making each generational cohort distinct from the whole of women’s professional tennis.

Mathematical Programming Models for Influence Maximization on Social Networks

In this dissertation, we apply mathematical programming techniques (i.e., integer programming and polyhedral combinatorics) to develop exact approaches for influence maximization on social networks. We study four combinatorial optimization problems that deal with maximizing influence at minimum cost over a social network. To our knowl- edge, all previous work to date involving influence maximization problems has focused on heuristics and approximation. We start with the following viral marketing problem that has attracted a significant amount of interest from the computer science literature. Given a social network, find a target set of customers to seed with a product. Then, a cascade will be caused by these initial adopters and other people start to adopt this product due to the influence they re- ceive from earlier adopters. The idea is to find the minimum cost that results in the entire network adopting the product. We first study a problem called the Weighted Target Set Selection (WTSS) Prob- lem. In the WTSS problem, the diffusion can take place over as many time periods as needed and a free product is given out to the individuals in the target set. Restricting the number of time periods that the diffusion takes place over to be one, we obtain a problem called the Positive Influence Dominating Set (PIDS) problem. Next, incorporating partial incentives, we consider a problem called the Least Cost Influence Problem (LCIP). The fourth problem studied is the One Time Period Least Cost Influence Problem (1TPLCIP) which is identical to the LCIP except that we restrict the number of time periods that the diffusion takes place over to be one. We apply a common research paradigm to each of these four problems. First, we work on special graphs: trees and cycles. Based on the insights we obtain from special graphs, we develop efficient methods for general graphs. On trees, first, we propose a polynomial time algorithm. More importantly, we present a tight and compact extended formulation. We also project the extended formulation onto the space of the natural vari- ables that gives the polytope on trees. Next, building upon the result for trees---we derive the polytope on cycles for the WTSS problem; as well as a polynomial time algorithm on cycles. This leads to our contribution on general graphs. For the WTSS problem and the LCIP, using the observation that the influence propagation network must be a directed acyclic graph (DAG), the strong formulation for trees can be embedded into a formulation on general graphs. We use this to design and implement a branch-and-cut approach for the WTSS problem and the LCIP. In our computational study, we are able to obtain high quality solutions for random graph instances with up to 10,000 nodes and 20,000 edges (40,000 arcs) within a reasonable amount of time.