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- All Subjects: Social Media
- Creators: Department of Management and Entrepreneurship
- Status: Published
Despite the importance of personal information, in many cases people do not reveal this information to the public. Predicting the hidden or missing information is a common response to this challenge. In this thesis, we address the problem of predicting user attributes and future or missing links using an egocentric approach. The current research proposes novel concepts and approaches to better understand social media users in twofold including, a) their attributes, preferences, and interests, and b) their future or missing connections and interactions. More specifically, the contributions of this dissertation are (1) proposing a framework to study social media users through their attributes and link information, (2) proposing a scalable algorithm to predict user preferences; and (3) proposing a novel approach to predict attributes and links with limited information. The proposed algorithms use an egocentric approach to improve the state of the art algorithms in two directions. First by improving the prediction accuracy, and second, by increasing the scalability of the algorithms.
Adverse Drug Reaction (ADR) identification. Such methods employ a step of drug search followed by classification of the associated text as consisting an ADR or not. Although this method works efficiently for ADR classifications, if ADR evidence is present in users posts over time, drug mentions fail to capture such ADRs. It also fails to record additional user information which may provide an opportunity to perform an in-depth analysis for lifestyle habits and possible reasons for any medical problems.
Pre-market clinical trials for drugs generally do not include pregnant women, and so their effects on pregnancy outcomes are not discovered early. This thesis presents a thorough, alternative strategy for assessing the safety profiles of drugs during pregnancy by utilizing user timelines from social media. I explore the use of a variety of state-of-the-art social media mining techniques, including rule-based and machine learning techniques, to identify pregnant women, monitor their drug usage patterns, categorize their birth outcomes, and attempt to discover associations between drugs and bad birth outcomes.
The technique used models user timelines as longitudinal patient networks, which provide us with a variety of key information about pregnancy, drug usage, and post-
birth reactions. I evaluate the distinct parts of the pipeline separately, validating the usefulness of each step. The approach to use user timelines in this fashion has produced very encouraging results, and can be employed for a range of other important tasks where users/patients are required to be followed over time to derive population-based measures.
Marketing In The Digital Age, or MITDA is a start-up business that provides seminars and lectures on digital media marketing and social media algorithms to ASU students and small businesses. We work with social media influencers to host lectures and seminars on brand awareness at ASU, and then offer classes and consulting to small-businesses who are looking to expand their online brand awareness. The content that we focus on compromises many different aspects of digital media marketing: platform specific algorithms, trends, digital media content creation (such as Photoshop and Canva), influencer brand deals and sponsorships, and influencer consultations. With MITDA, ASU students and small businesses have the opportunity to hop on quick trends, build a marketable brand to Generation Z, and learn how to stay relevant in the new marketing world of influencers and content creators.
The Winner's Circle aims to provide a digital platform for sports fans and betting addicts, in hopes to help centralize various forms of social communication between family, close friends, and strangers alike. As the legalization of sports related gambling activities become more widespread throughout the United States as well as the rest of the world, our platform has to potential to connect millions of like-minded, adrenaline-seeking fans across the globe.