Risk Prediction Sentiment Analysis

Himler, Tom; Sharma, Pranav; Taing, Eriq; Akula, Akshay; Joaquin, Evan

Risk Prediction Sentiment Analysis

dc.contributor.author	Himler, Tom	en
dc.contributor.author	Sharma, Pranav	en
dc.contributor.author	Taing, Eriq	en
dc.contributor.author	Akula, Akshay	en
dc.contributor.author	Joaquin, Evan	en
dc.date.accessioned	2021-12-15T03:19:24Z	en
dc.date.available	2021-12-15T03:19:24Z	en
dc.date.issued	2021-12-13	en
dc.description.abstract	Risk Sentiment Analysis proposes a solution for companies to evaluate user submitted reports to determine workplace safety. The web application develops a pipeline for managers to submit employee CSVs to be processed through a custom sentiment analysis model in AWS. Alongside that, it has graphical presentation capabilities to easily interpret queried data. Finally, the web application supports a feedback loop of re-training the model to improve its accuracy with a page dedicated for human review.	en
dc.description.notes	RiskPredictionSentimentAnalysisReport.pdf: Contains our project report. RiskPredictionSentimentAnalysisReportDocs.zip: Contains the assets for our LaTeX document for future edits. RiskPredictionSentimentAnalysisPresentation.pdf: Contains the slides for our final presentation. RiskPredictionSentimentAnalysisPresentationDoc.pptx: Contains the powerpoint slides of our final presentation for future edits.	en
dc.identifier.uri	http://hdl.handle.net/10919/107004	en
dc.language.iso	en_US	en
dc.publisher	Virginia Tech	en
dc.rights	Attribution-NonCommercial 4.0 International	en
dc.rights.uri	http://creativecommons.org/licenses/by-nc/4.0/	en
dc.subject	Machine learning	en
dc.subject	AWS	en
dc.subject	Hypertext	en
dc.subject	Sentiment Analysis	en
dc.subject	Natural Language Processing	en
dc.subject	NLP	en
dc.subject	JavaScript	en
dc.subject	React.js	en
dc.subject	AWS Comprehend	en
dc.subject	AWS S3	en
dc.subject	AWS EC2	en
dc.subject	AWS DynamoDB	en
dc.title	Risk Prediction Sentiment Analysis	en
dc.type	Presentation	en
dc.type	Report	en