There are 4 repositories under textblob-sentiment-analysis topic.
An affect generator based on TextBlob and the NRC affect lexicon. Note that lexicon license is for research purposes only.
This project performed sentimental analysis based on opinion words (like good, bad, beautiful, wrong, best, awesome, etc) of selected opinion target ( like product name for amazon product reviews).
Emotion AI (Sentiment Analysis) of Tweets using TextBlob and Django (Python)
A Hack of the Hour presents to you a product that is meant to strengthen the relationship between a Therapist & their Client. A product that is meant to channel the Client's emotions and feelings anywhere, anytime. Providing a detailed analysis to the therapist, tailored to the Client itself.
In this project, I explore various machine learning techniques including Principal Component Analysis (PCA), Support Vector Machines (SVM), Artificial Neural Networks (ANN), and Sentiment Analysis in an effort to predict the directional changes in exchange rates for a list of developed and developing countries.
In this repo i created a twitter sentiment analysis on flask app (web base).
A simple Python Program to Analyze Sentiments using TextBlob Python Library.
Vecna is a Python chatbot which recommends songs and movies depending upon your feelings
Análise de sentimento de tweets utilizando Tweepy e Textblob.
Twitter Sentiment analysis with polarity and subjectivity using Python
Sentiment Analysis of Youtube Video Comments using Youtube Data Api
🔍 Places finder using Natural Language Processing
In this project we have built a model which takes a dataset as an input andas an output gives the percentage of posive ,negative and neutral tweets in the given dataset. It is done using natural language processing library using scikit learn machine learning libraries such as textblob.
Banglish -> Bangla (With avro phonetic) -> English (With textblob translator) -> Sentiment
Live sentiment analysis of tweets using Kafka
You can watch the working of this project at https://www.youtube.com/watch?v=me782RAMM3Y
DBMS mini project implemented to calculate rating of a movie by analyzing the reviews given by the user.
Investigate the impact of general news headlines on Stock Indices
Use NLP & Sentiment analysis in Python to determine the impact sentiment has on the price of Bitcoin
python'la yaptığım ekşi sözlük tutum ölçme programı
This Python code retrieves thousands of tweets, classifies them using TextBlob and VADER in tandem, summarizes each classification using LexRank, Luhn, LSA, and LSA with stopwords, and then ranks stopwords-scrubbed keywords per classification.
Using Natural Language Processing to predict Tesla stock movement based on news article sentiment from the New York Times
Twitter Sentiment Analysis using python flask and Textblob
Cyberbullying Detection using Semantic Analysis
tweety scrape all the tweets using python and selenium with No API rate limits. No restrictions. Extremely fast.
simple script for downloading Youtube comments without using the Youtube API
Summarize News Article
Predicting product recommendation score using the data available on the website of the client
This is a sentiment analysis project with web UI.
Python and flask projects
In this project I used textblob library in Python and tried to do some analysis on the text provided. I summerized the text, find out the sentiment and also point out the subjectivity of the text. I implemented a simple UI using HTML,CSS,JavaScript and also Flask as my API handling back end tool.
Using SparkML to build different machine learning models for simulating a small scale of big data management
this repo contains files for my analysis on disney land visitor reviews using NLP
Three clicks twitter sentiment analyzer with graphical output. A 🐍 mini project
Web Application that emulates the UI of Spotify, integrating a robust recommender system that utilize the audio features of selected songs to provide personalized recommendations and Analytical Engine capable of analyzing songs & genres.
Applications of NLP like Topic Modeling, Sentiment Analysis, Word Cloud along with Web Scraping.