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Sentiment Analysis Of Twitter Data, Evan L. Munson
Sentiment Analysis Of Twitter Data, Evan L. Munson
Theses and Dissertations
The rapid expansion and acceptance of social media has opened doors into users’ opinions and perceptions that were never as accessible as they are with today's prevalence of mobile technology. Harvested data, analyzed for opinions and sentiment can provide powerful insight into a population. This research utilizes Twitter data due to its widespread global use, in order to examine the sentiment associated with tweets. An approach utilizing Twitter #hashtags and Latent Dirichlet Allocation topic modeling were utilized to differentiate between tweet topics. A lexicographical dictionary was then utilized to classify sentiment. This method provides a framework for an analyst to …
Verification And Validation Of Faarr Model And Data Envelopment Analysis Models For United States Army Recruiting, Gene M. Piskator
Verification And Validation Of Faarr Model And Data Envelopment Analysis Models For United States Army Recruiting, Gene M. Piskator
Theses and Dissertations
This research has two objectives-to verify and validate the U.S. Army's Forecast and Allocation of Army Recruiting Resources (FAARR) model and to develop a Data Envelopment Analysis (DEA) modeling strategy. First, the FAARR model was verified using a simulation of a known production function and validated using sensitivity analysis and ex-post forecasts. FAARR model forecasts were not accurate and were extremely sensitive to any changes in the model's linear programming constraints and to changes in recruiting resource levels. Second, this research describes a three phase modeling strategy to build accurate DEA models. DEA has become a popular tool to evaluate …