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Applications In Sentiment Analysis And Machine Learning For Identifying Public Health Variables Across Social Media, Eric Michael Clark
Applications In Sentiment Analysis And Machine Learning For Identifying Public Health Variables Across Social Media, Eric Michael Clark
Graduate College Dissertations and Theses
Twitter, a popular social media outlet, has evolved into a vast source of linguistic data, rich with opinion, sentiment, and discussion. We mined data from several public Twitter endpoints to identify content relevant to healthcare providers and public health regulatory professionals. We began by compiling content related to electronic nicotine delivery systems (or e-cigarettes) as these had become popular alternatives to tobacco products. There was an apparent need to remove high frequency tweeting entities, called bots, that would spam messages, advertisements, and fabricate testimonials. Algorithms were constructed using natural language processing and machine learning to sift human responses from automated …
Measuring Linguistic And Cultural Evolution Using Books And Tweets, Tyler Gray
Measuring Linguistic And Cultural Evolution Using Books And Tweets, Tyler Gray
Graduate College Dissertations and Theses
Written language provides a snapshot of linguistic, cultural, and current events information for a given time period. Aggregating these snapshots by studying many texts over time reveals trends in the evolution of language, culture, and society. The ever-increasing amount of electronic text, both from the digitization of books and other paper documents to the increasing frequency with which electronic text is used as a means of communication, has given us an unprecedented opportunity to study these trends. In this dissertation, we use hundreds of thousands of books spanning two centuries scanned by Google, and over 100 billion messages, or ‘tweets’, …