Filtering by
- All Subjects: Social Media
- Creators: Walter Cronkite School of Journalism and Mass Comm
- Creators: Davulcu, Hasan
- Resource Type: Text
- 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.
Americans today face an age of information overload. With the evolution of Media 3.0, the internet, and the rise of Media 3.5—i.e., social media—relatively new communication technologies present pressing challenges for the First Amendment in American society. Twentieth century law defined freedom of expression, but in an information-limited world. By contrast, the twenty-first century is seeing the emergence of a world that is overloaded with information, largely shaped by an “unintentional press”—social media. Americans today rely on just a small concentration of private technology powerhouses exercising both economic and social influence over American society. This raises questions about censorship, access, and misinformation. While the First Amendment protects speech from government censorship only, First Amendment ideology is largely ingrained across American culture, including on social media. Technological advances arguably have made entry into the marketplace of ideas—a fundamental First Amendment doctrine—more accessible, but also more problematic for the average American, increasing his/her potential exposure to misinformation. <br/><br/>This thesis uses political and judicial frameworks to evaluate modern misinformation trends, social media platforms and current misinformation efforts, against the background of two misinformation accelerants in 2020, the COVID-19 pandemic and U.S. presidential election. Throughout history, times of hardship and intense fear have contributed to the shaping of First Amendment jurisprudence. Thus, this thesis looks at how fear can intensify the spread of misinformation and influence free speech values. Extensive research was conducted to provide the historical context behind relevant modern literature. This thesis then concludes with three solutions to misinformation that are supported by critical American free speech theory.
Social media today is a major source of not only communication, but also news and entertainment. This year, people everywhere have had to embrace virtual environments as their main sources of communication. For students, especially, the move to virtual schoolwork in 2020 has increased the amount of time spent on technology. This observational study examined, through an anonymous online survey, how college students spend their time on social media and how it affects their mental health. The 25-question survey was open to current ASU students as of 2021, and 2020 ASU graduates. Respondents’ results concluded that while students actively use social media for communication and entertainment, it can present a burden on their mental health and their productivity.
A guide to implementing empathy in crisis communications
A reflection on my diverse educational experience as a sports journalism student, key lessons I learned about specific forms of communication and content creation within social media, written reporting and radio/podcasting and the demand for versatility among all modern journalists.
Shifting Horizons in Entrepreneurship, better known as SHE is a multimedia reporting project that explores the experiences and narratives of Arizona-based female business owners. This collaborative project uses multimedia reporting techniques such as writing, photography, social media and a podcast to showcase how women are making a space for themselves in entrepreneurship.