textblob-sentiment-analysis

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).

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.

🔍 Places finder using Natural Language Processing

You can watch the working of this project at https://www.youtube.com/watch?v=me782RAMM3Y

Banglish -> Bangla (With avro phonetic) -> English (With textblob translator) -> Sentiment

In this repo i created a twitter sentiment analysis on flask app (web base).

Análise de sentimento de tweets utilizando Tweepy e Textblob.

Use NLP & Sentiment analysis in Python to determine the impact sentiment has on the price of Bitcoin

Sentiment Analysis of Youtube Video Comments using Youtube Data Api

DBMS mini project implemented to calculate rating of a movie by analyzing the reviews given by the user.

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.

Using Natural Language Processing to predict Tesla stock movement based on news article sentiment from the New York Times

Cyberbullying Detection using Semantic Analysis

simple script for downloading Youtube comments without using the Youtube API

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.

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.

Sentimental analysis and prediction tool is used to get the sentiments of people on, tweeter tweets or upload CSV file or xls file and based on people feedbacks one can apply BI logics over product.

Twitter Sentiment Analysis using python flask and Textblob

Three clicks twitter sentiment analyzer with graphical output. A 🐍 mini project