Date of Graduation
5-2020
Document Type
Thesis
Degree Name
Bachelor of Science
Degree Level
Undergraduate
Department
Computer Science and Computer Engineering
Advisor/Mentor
Gauch, Susan
Committee Member/Reader
Gauch, Susan
Committee Member/Second Reader
Streeter, Lora
Committee Member/Third Reader
Gauch, John
Abstract
Sentiment analysis is a natural language processing technique that aims to classify text based on the emotions expressed in them. It is a research area that has been around for almost 20 years and has seen a lot of development. The works presented in this paper attempts to target a less-developed area in sentiment analysis known as multilingual sentiment analysis. More specifically, multilingual sentiment analysis of micro-texts. Using the existing WordNet lexicon and a domain-specific lexicon for a corpus of Spanish tweets, we analyze the effectiveness of these techniques.
Keywords
sentiment analysis, lexicon, corpus, textblob, classifier
Citation
Roca, J. (2020). Lexicon Based Approaches to Sentiment Analysis of Spanish Tweets: A Comparative Study. Computer Science and Computer Engineering Undergraduate Honors Theses Retrieved from https://scholarworks.uark.edu/csceuht/78