Best Data Science Collaboration Practices

Identification of Sustainability-Related Research at USC through Machine Learning and Keyword Mapping
Are you passionate about data science and sustainability? Then this interdisciplinary project is for you! Here, we will develop a machine learning program to identify USC research publications and grants as ‘sustainability-focused’, ‘sustainability-inclusive’ or ‘not-sustainability-related’ by using pre-categorized publication samples. In addition, we will use keyword lists that relate to the 17 UN Sustainable Development Goals (SDGs) to map all research groups at USC as they relate to these SDGs (https://sdgs.un.org/goals). Lastly, we will create an interactive dashboard in R Shiny that will act as a public directory of all research at USC with classification of the research by the SDGs and broader sustainability categorization. As an example, check our github for USC curriculum: https://github.com/USC-Office-of-Sustainability/USC-SDGmap . Your work on this project is critical in boosting sustainability-related research at USC and thereby achieving our Asgmt: Earth Research Goals."
Identification of Sustainability-Related Research at USC through Machine Learning and Keyword Mapping
Mapping the Ethical Concerns Surrounding AI Research
With the recent enthusiasm about algorithmic fairness and responsible AI, many conferences are encouraging or requiring a broader impact section to assess societal harms and benefits of the AI research being presented. In this project, we will analyze the themes of these sections, with a particular focus on the ethical issues being addressed and acknowledged. We will develop tools and methods to evaluate the harms and benefits of the presented research. The goal is to see how is the community helping AI research to be less harmful but more beneficial for society. For more background on work in this area, please review this workshop.
Digital Democracy: Using Social Media to Improve Political Discourse (Spring - 2020)
Politicians in modern democracies across the world have eagerly adopted social media for engaging their constituents, entering into direct dialogs with citizens. From the perspective of political actors, there is a need to continuously gather, monitor, analyze, and visualize politically relevant information from online social media with the goal to improve communication with citizens and voters. The goal of this proposal is to create a tool that enhances interaction and dialogue between political actors and their followers. This will be achieved by creating compact and comprehensive summaries that aggregate and visualizes common narratives, thus, reducing the cognitive load required to read all the messages and streamlining the dialogue experience.
Digital Democracy: Using Social Media to Improve Political Discourse (Spring - 2020)
Measuring population-level nutrition and dietary habits from Instagram
This project will investigate the quality of Instagram textual posts as a source of data for measurements of dietary patterns and nutrition quality, focusing on spatial and textual features of posts linked to food outlets. Using an Instagram dataset of all geo-located posts at food outlets in Los Angeles for 3 months in 2014, this project will investigate whether Instagram posts, despite implicit biases (and to the extent possible, accounting for these biases), can provide a representative health signal, informative of the quality of population nutrition and dietary patterns at a highly-resolved (e.g. census tract level) spatial scale.