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Social Media Text Analysis Using Multi-Kernel Convolutional Neural Network, Anna Philips
Social Media Text Analysis Using Multi-Kernel Convolutional Neural Network, Anna Philips
Computer Science and Engineering Theses
Transportation planners and ride hailing platforms such as Uber and Lyft use their riders feedback to assess their services and monitor customer satisfaction. Social media websites such as Facebook, Instagram, LinkedIn and in particular Twitter provides a large dataset of micro-texts by users who regularly post to their social media accounts about their grievances with their ride experience. This data is often unorganized and intractable to process because of it’s extremely large size which is continuously increasing daily. In this project, we collected ride hailing service relevant text data from Twitter around New York and developed a novel Convolutional Neural …
Hiding In Plain Sight? The Impact Of Face Recognition Services On Privacy, James Richard Ortega
Hiding In Plain Sight? The Impact Of Face Recognition Services On Privacy, James Richard Ortega
Computer Science and Engineering Theses
The public at large is increasingly concerned with privacy online. While the focus is on the data privately collected by platforms, there are also privacy concerns in the realm of public data. Seemingly innocuous information shared in public, on online platforms, can be pieced together to detrimentally affect one's privacy in unexpected ways. On YouTube there exists a rich public dataset for adversaries to analyze for the purposes of breaching privacy; particularly due to the intersection of location and facial data. The goal of this work is to characterize the privacy risks that exists on YouTube, and explore the viability …