mbodke/Twitter-Sentiment-Analysis-using-R-shiny
Project based on text mining:
This tool helps you quickly understand public opinion and mood from Twitter. You provide a Twitter username or a trending hashtag, and the system extracts tweets, analyzes them, and presents a visual summary of positive and negative sentiments, including word clouds. Marketers, public relations professionals, or social researchers can use this to gauge real-time public reactions.
No commits in the last 6 months.
Use this if you need a quick and easy way to understand the sentiment around a specific Twitter user or hashtag, geographically focused within the US.
Not ideal if you require deep, nuanced linguistic analysis beyond basic sentiment, or if your primary interest is in historical data or very large-scale, complex text mining.
Stars
10
Forks
17
Language
R
License
—
Category
Last pushed
Sep 28, 2017
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/nlp/mbodke/Twitter-Sentiment-Analysis-using-R-shiny"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
quanteda/quanteda
An R package for the Quantitative Analysis of Textual Data
juliasilge/tidytext
Text mining using tidy tools :sparkles::page_facing_up::sparkles:
massimoaria/tall
Text Analysis for aLL
keyATM/keyATM
An R package for Keyword Assisted Topic Models
gagolews/stringi
Fast and Portable Character String Processing in R (with the Unicode ICU)