Submission of an in-class NLP sentiment analysis competition held at Microsoft AI Singapore group. This submission entry explores the performance of both lexicon & machine-learning based models

Generate synthetic labeled data for extremely low-resource languages using bilingual lexicons.

Goodness of Pronunciation Pipelines for OOV Removal

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.

Final Year Project: Sentiment Analysis Approach for Reputation Evaluation

Simple lexicon-based persian sentiment analysis

This repository contains introductory notebooks for text mining and web scrapping.

The purpose of creating this application is to help the government, especially the Directorate General of Taxes (DJP) in improving and fixing the problems that exist in the M - Tax application. This application is built using Flask as its framework and uses the Long Short - Term Memory (LSTM) and Lexicon Based algorithms in conducting sentiment …

An exploratory view on the the Wikidata lexicographic data

Lexicon based segmentation of cursive handwritten images, and recognizing the characters using deep learning model.

Analysing Mexico’s President speeches: A study of political propaganda and populist rhetoric using NLP methods

sentiment analysis with Lexicon, Machine Learning and Deep learning methods

A complete platform for gathering, pre-processing, and labeling tweets.

Lexicon-based sentiment analysis on Malay tweets that pulled from Twitter. My final year project in 2020.

This repository about implementation of sentiment analysis using Lexicon Based method.

This project focuses on sentiment analysis using Natural Language Processing (NLP) techniques applied to Twitter data. Sentiment analysis is the process of determining the emotional tone behind a piece of text, and in this case, we are analyzing sentiments expressed in tweets.

VADER Sentiment Analysis Tool with C++. Valence Aware Dictionary and sEntiment Reasoner (VADER) is a lexicon and rule-based sentiment tool designed to measure sentiment of text from social media. Originally written in Python, this is a port to C++.

Source code of paper "Incorporating prior knowledge into word embedding for Chinese word similarity measurement", accepted by ACM Transactions on Asian and Low-Resource Language Information Processing (TALLIP).