sandy4321 Goto Github PK
Type: User
Type: User
The application is a cloud service that provides the functionality of performing sentiment analysis on stock market and financial data. The application can be hosted on Google App Engine and makes use of many of the GAE services like Search Service, MemCache, DataStore etc. Given the name of a company, data from various sources like Twitter, Facebook Graph, Google News, Google Finance etc is aggregated. For each source, different models have been pretrained using some prior data. Using different models provided us with a chance to utilize different Machine Learning methodologies based on the type of data from each source. The various techniques that we have built and tested on are :Naive Bayes, Multinomial and Bernoulli text representations, KNN.
GROUP 6 - PROJECT REPORT TWITTER SENTIMENT ANALYSIS OF US PRESIDENTIAL ELECTION
Tool for visual sentiment classification
Some code for a twitter sentiment analysis
Python and STATA - Tracking the individual sentiment through Twitter data for financial markets analysis.
twitter Political sentiment Analysis
Opinion mining of Twitter data from just before the US Presidential election of people for/against/neutral Barack Obama and Mitt Romney
A sentiment analysis module for node.js, russian language implamentation by Roman Yudin
Sentiment Analysis on Twitter data
Sentiment Analysis of @FoxyReign on Twitter
Fast Food Sentiment Analysis using Twitter data
Survey of projects on twitter sentiment analysis
This will focus on sentiment analysis, using NLTK over Python.
Workspace for Sentiment Analysis Session. Sanitizing, stemming, processing. Feature Vector creation.
Project on aspect-based sentiment analysis using SemEval's 2014 data.
We propose a model based on the bag of mixed-gram terms to deal with sentiment classification task and extracting sentimental features. We obtain a very short-dimensional vector to represent sentiment and use the sentimental representations to complete the task of sentiment classification. Furthermore, since the sentimental representa- tions and some traditional word vectors have complementary advantages, we combine the sentimental representations with convolutional neural networks that use other word vectors and ultimately implement a more efficient classifier. Experimental results show that this combination method can use static word vectors to deal with sentimental classification tasks well, and the sentimental representations here play the role of fine-turned word vectors in previous research.
Info 256 sentiment analysis using NLTK
nlp sentiment analysis using NLTK
Sentiment Analysis on Twitter Datasets
Basic Twitter sentiment analysis
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.