Project developed in Python 3.5 making use of Bokeh library to display the opinion of users of the debate of June 13, 2016 among the candidates for the presidency of the government of Spain.
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Updated
Sep 18, 2017 - Python
Project developed in Python 3.5 making use of Bokeh library to display the opinion of users of the debate of June 13, 2016 among the candidates for the presidency of the government of Spain.
résumé automatique de texte oriente vers la prévention, l’éradication et détection des maladies ravageuses déclenchées sur les réseaux sociaux (twitter) cas de l’ebola , meningite et malaria
Perform sentimental analysis on the Elon-musk tweets (Elon-musk.csv)
A simple sentiment detector open-source module for node.js
We'll build a sentiment analysis platform using the IMDB dataset.
Experimenting with Twitter API's and gathering tweets from twitter
Supplementary data for the 2021 JNLE article "Automatic Generation of Lexica for Sentiment Polarity Shifters" by Schulder, Wiegand and Ruppenhofer.
Analyzing human sentiment using machine learning-based techniques: A case study on COVID-19 pandemic
Womens Clothing E-Commerce Reviews Sentiment Analysis
A PHP & MySQL based Sentiment Polarity Analyzer
Given a users review, predict the stars given by the reviewer
This research wants to build a time serie of the polarity of tweets related to a cluster of firms, and compare it to the time serie of the same firms in the stock market.
In this project a streamlit app is created in which user can upload any english language audio file to get its transcripts, sentiment analysis report, list of statements according to its nature like positive, negative or neutral and at last extractive summary of the whole audio.
Custom Sentiment API
Sentiment mining on Yelp reviews
Web Scrapping British Airways review to gain company insights. Build a random forest model to predict customer buying behavior.
Sentiment Analysis & Monte Carlo Tree Search with Nested Rollout Policy Adaptation for Business
Sentiment Analysis of Geotagged Tweets from Los Angeles County
sentiment analysis
Supplementary data for the doctoral thesis "Sentiment Polarity Shifters: Creating Lexical Resources through Manual Annotation and Bootstrapped Machine Learning" by Marc Schulder.
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