{"repo":"hoangsonww/Amazon-Reviews-Analysis","free":true,"listed":false,"github":"https://github.com/hoangsonww/Amazon-Reviews-Analysis","clone":"git clone https://github.com/hoangsonww/Amazon-Reviews-Analysis.git","description":"🧐 This project analyzes Amazon Fine Food Reviews to investigate whether negative reviews are more emotionally intense and lexically repetitive than positive ones. Using R, we apply sentiment analysis and lexical diversity metrics to uncover patterns in consumer review language.","language":"R","stars":11,"topics":["amazon-food-reviews","data-analysis","data-visualization","ggplot2","hypothesis-testing","r","r-markdown","r-programming","r-scripts","r-studio"],"license":"MIT","category":"analytics","readme_excerpt":"Lexical Diversity and Sentiment Intensity in Amazon Fine Food Reviews LING-460: Textual Analysis with R at UNC-Chapel Hill, Spring 2025. Table of Contents 1. Motivation 2. Research Question 3. Research Hypothesis 4. Prediction 5. Procedure 6. Analysis Results - Descriptive Statistics - Statistical Tests - Regression Analysis 7. Data Analysis 8. Visualizations 9. Conclusions 10. References Motivation Consumer reviews provide rich insights into the evaluative language that people use to express their satisfaction or dissatisfaction. The way consumers articulate their experiences can reveal underlying linguistic patterns, where factors such as lexical diversity and emotional tone contribute to the expression of opinions. Understanding these patterns has implications for marketing, consumer research, and sentiment analysis in natural language processing. Our project addresses the broader question of whether the language used in negative reviews differs fundamentally from that used in positive reviews. Dataset: https://www.kaggle.com/datasets/snap/amazon-fine-food-reviews?resource=download. Research Question Do negative reviews exhibit lower lexical diversity and higher negative sentiment intensity than positive reviews? - Lexical diversity is measured by the type-token ratio (TTR), which quantifies the ratio of unique words to the total number of words in a review. - Negative sentiment intensity is measured by the proportion of negative words (using a standard sentiment lexicon) ","default_branch":null,"files":null,"tree":[],"storefront":"/r/hoangsonww","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/hoangsonww/Amazon-Reviews-Analysis/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}