ADVERTISEMENT ALLOCATION AND TRUST MECHANISMS DESIGN IN SOCIAL NETWORKS

Social network sites (SNS), such as Facebook, Google+ and Twitter, have attracted hundreds of millions of users daily since their appearance. Within SNS, users connect to each other, express their identity, disseminate information and form cooperation by interacting with their connected peers. The increasing popularity and ubiquity of SNS usage and the invaluable user behaviors and connections give birth to many applications and business models. We look into several important problems within the social network ecosystem. The first one is the SNS advertisement allocation problem. The other two are related to trust mechanisms design in social network setting, including local trust inference and global trust evaluation. In SNS advertising, we study the problem of advertisement allocation from the ad platform's angle, and discuss its differences with the advertising model in the search engine setting. By leveraging the connection between social networks and hyperbolic geometry, we propose to solve the problem via approximation using hyperbolic embedding and convex optimization. A hyperbolic embedding method, \hcm, is designed for the SNS ad allocation problem, and several components are introduced to realize the optimization formulation. We show the advantages of our new approach in solving the problem compared to the baseline integer programming (IP) formulation. In studying the problem of trust mechanisms in social networks, we consider the existence of distrust (i.e. negative trust) relationships, and differentiate between the concept of local trust and global trust in social network setting. In the problem of local trust inference, we propose a 2-D trust model. Based on the model, we develop a semiring-based trust inference framework. In global trust evaluation, we consider a general setting with conflicting opinions, and propose a consensus-based approach to solve the complex problem in signed trust networks.

INVISIBLE LABOR FOR DATA: INSTITUTIONS, INFRASTRUCTURE, AND VIRTUAL SPACE

Americans are accustomed to a wide range of data collection in their lives: census, polls, surveys, user registrations, and disclosure forms. When logging onto the Internet, users’ actions are being tracked everywhere: clicking, typing, tapping, swiping, searching, and placing orders. All of this data is stored to create data-driven profiles of each user. Social network sites, furthermore, set the voluntarily sharing of personal data as the default mode of engagement. But people’s time and energy devoted to creating this massive amount of data, on paper and online, are taken for granted. Few people would consider their time and energy spent on data production as labor. Even if some people do acknowledge their labor for data, they believe it is accessory to the activities at hand. In the face of pervasive data collection and the rising time spent on screens, why do people keep ignoring their labor for data? How has labor for data been become invisible, as something that is disregarded by many users? What does invisible labor for data imply for everyday cultural practices in the United States? Invisible Labor for Data addresses these questions. I argue that three intertwined forces contribute to framing data production as being void of labor: data production institutions throughout history, the Internet’s technological infrastructure (especially with the implementation of algorithms), and the multiplication of virtual spaces. There is a common tendency in the framework of human interactions with computers to deprive data and bodies of their materiality. My Introduction and Chapter 1 offer theoretical interventions by reinstating embodied materiality and redefining labor for data as an ongoing process. The middle Chapters present case studies explaining how labor for data is pushed to the margin of the narratives about data production. I focus on a nationwide debate in the 1960s on whether the U.S. should build a databank, contemporary Big Data practices in the data broker and the Internet industries, and the group of people who are hired to produce data for other people’s avatars in the virtual games. I conclude with a discussion on how the new development of crowdsourcing projects may usher in the new chapter in exploiting invisible and discounted labor for data.

Identification and assessment of potential wind energy project sites in the State of Maryland

Gemstone Team Renewables

SOCIAL STRUCTURE OF ASIAN ELEPHANTS (ELEPHAS MAXIMUS) IN SRI LANKA

Asian elephants (Elephas maximus) are critically endangered and live in fragmented populations spread across 13 countries. Yet in comparison to the African savannah elephant (Loxodonta africana), relatively little is known about the social structure of wild Asian elephants because the species is mostly found in low visibility habitat. A better understanding of Asian elephant social structure is critical to mitigate human-elephant conflicts that arise due to increasing human encroachments into elephant habitats. In this dissertation, I examined the social structure of Asian elephants at three sites: Yala, Udawalawe, and Minneriya National Parks in Sri Lanka, where the presence of large open areas and high elephant densities are conducive to behavioral observations. First, I found that the size of groups observed at georeferenced locations was affected by forage availability and distance to water, and the effects of these environmental factors on group size depended on site. Second, I discovered that while populations at different sites differed in the prevalence of weak associations among individuals, a core social structure of individuals sharing strong bonds and organized into highly independent clusters was present across sites. Finally, I showed that the core social structure preserved across sites was typically composed of adult females associating with each other and with other age-sex classes. In addition, I showed that females are social at all life stages, whereas males gradually transition from living in a group to a more solitary lifestyle. Taking into consideration these elements of Asian elephant social structure will help conservation biologists develop effective management strategies that account for both human needs and the socio-ecology of the elephants.