There are 34 repositories under twitter-sentiment-analysis topic.
Stock market analyzer and predictor using Elasticsearch, Twitter, News headlines and Python natural language processing and sentiment analysis
A real-time interactive web app based on data pipelines using streaming Twitter data, automated sentiment analysis, and MySQL&PostgreSQL database (Deployed on Heroku)
Pretrained BERT model for analysing COVID-19 Twitter data
This script can tell you the sentiments of people regarding to any events happening in the world by analyzing tweets related to that event
:star2: :sparkles: Analyze and visualize Twitter Sentiment on a world map using Spark MLlib
Simple Stock Investment Recommendation System based on Machine-Learning algorithms for prediction and Twitter Sentiment Analysis.
:mag: This project is about searching the twitter for job opportunities using popular hashtags and applying sentiment analysis on this. :hash: :bird:
Sentiment analysis dashboard for Twitter hashtags
Hashformers is a framework for hashtag segmentation with Transformers and Large Language Models (LLMs).
Computes sentiment analysis of tweets of US States in real-time using Storm.
情感分析,微博情感分析,微博水军检测,水军检测,营销粉检测,僵尸粉检测,微博爬虫
A sample application that demonstrates how to build a graph processing platform to analyze sources of emotional influence on Twitter.
Twitter Sentiment Analysis For Turkish Language
This sentiment analysis project determines whether the tweets posted in the Turkish language on Twitter are positive or negative.
Sentiment Analysis of a Twitter Topic with Spark Structured Streaming
Predicting Consumer Purchase intention using Twitter Data
Sentiment Analysis Project using Natural Language Processing (NLP) Techniques
This project develops a deep learning model that trains on 1.6 million tweets for sentiment analysis to classify any new tweet as either being positive or negative.
Twitter Sentiment Analysis using #tag, words and username
FinTwit-Bot is a Discord bot designed to track and analyze financial markets by pulling data from platforms like Twitter, Reddit, and Binance. It features customizable tools for sentiment analysis, market trends, and portfolio tracking to help traders stay informed and make data-driven decisions.
AfriSenti-SemEval Shared Task 12: Sentiment Analysis for African languages : https://afrisenti-semeval.github.io/
:chart: A web app to search twitter based on #Hashtags and calculate the sentiment of tweets.
Sentiment Analysis with Deep Learning models. Implemented with Tensorflow and Keras.
This project walks you on how to create a twitter sentiment analysis model using python. Twitter sentiment analysis is performed to identify the sentiments of the people towards various topics. For this project, we will be analysing the sentiment of people towards Pfizer vaccines. We will be using the data available on Kaggle to create this machine learning model. The collected tweets from Twitter will be analysed using machine learning to identify the different sentiments present in the tweets. The different sentiments identified in this project include positive sentiment, negative sentiment and neutral sentiment. We will also be using different classifiers to see which classifier gives the best model accuracy.
This is our final year project. In this we are predicting election, results using Twitter Sentiment Analysis.
Fullstack machine learning inference template
TurkishBERTweet: Fast and Reliable Large Language Model for Social Media Analysis
Collect and process real time twitter data plotting various metrics like volume , proportion, sentiment. Analyze tweet node networks and map them geographically.
Python
Computes and visualizes the sentiment analysis of tweets of US States in real-time using Storm.
Twitter Sentiment Analysis using Textblob and Tweepy, wrapped with Flask as a web app.
📊 Adana - 1-click analytical dashboard for OSINT researchers
Detecting whether a particular tweet contains negative emotions attached with it or not from the given dataset
BiLSTM with Multi-Headed Self Attention for sentiment classification of Twitter data, implemented in Keras and PyTorch.