This repository contains my grad-school project for a text analysis app.
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Updated
Jun 5, 2019 - R
This repository contains my grad-school project for a text analysis app.
🍵 Create and administrate validation tests for automated content analysis tools.
👚 Speedy Word Embedding Association Test & Extras using R
To find the accurate review and sentiment about the product and tag the opinion as positive, negative or neutral.
Final course project under the JHU data science course. This app uses a predictive text model built from the large corpus data. The model was built using the tidyverse package and n – gram function. The app was built using the Shiny package and it allows user to enter string and app will predict the next word.
Sentiment Analysis of Tweets for a renowned shoe brand
This repository contains the Text Analysis project from the Applied Data Science course at Columbia University
This shiny app explores the transcripts of the Government Digital Service podcast, analysing the transcripts for sentiment and characteristics.
Text analysis, also known as text mining, is the process of automatically classifying and extracting meaningful information from unstructured text. It involves detecting and interpreting trends and patterns to obtain relevant insights from data in just seconds.
Analyze how people perceive plant-based diets online and generate marketing insights on the plant-based products.
Over 30,000 news about Myanmar which were published in 2021 were scrapped from the web and their titles were analyzed.
Final Project for Brad Pasanek's "Hacking for Humanists"--UVA ENSP 3599 Fall 2015.
Simple text mining using R programming. We will take a text file and then we will perform cleaning and simple analysis on it. We will then represent the data using wordclouds.
Web scraping y análisis de texto sobre un corpus de texto de noticias de la prensa chilena
Sentiment Analysis on technological challenges faced by seniors at a local senior living community.
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