Sentiment Strength Detection in Bahasa Indonesia
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Updated
Mar 23, 2017 - Python
Sentiment Strength Detection in Bahasa Indonesia
Twitter Sentiment Analysis
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.
Sentiment Analysis on Tweets based on Recurrent Neural Network and attention model, implemented using Tensorflow library.
Text Mining Clustering positive and Negative words from a document using KMeans (Python implementation)
Calculates a "polarity score" and other notable stats on specific Youtube videos. The Polarity Score represents the overall viewer sentiment towards the video.
Experimenting with Twitter API's and gathering tweets from twitter
Sentiment classification of live tweets into positive, negative and neutral polarity.
sentiment analysis
Analyze Tweets using NLTK and Tweepy
Logistic Regression and Feature Engineering.
Extract sentiment of every US public company from financial news headlines
Given a users review, predict the stars given by the reviewer
sample scripts that show use of NLP in python.Some will be proof of concepts while others will be tutorials
Sentiment Analysis on Game Review using TextBlob-lexicon and rule-based sentiment.
Banglish -> Bangla (With avro phonetic) -> English (With textblob translator) -> Sentiment
Project collects tweets, using the tweepy library to access the Twitter API for search/filter and streaming functionality, and extracts data fields along with running Sentiment Analysis on the collected tweets.
A Sentiment Analysis Dataset of Comments in Serbian
Codes for our paper "SentiLARE: Sentiment-Aware Language Representation Learning with Linguistic Knowledge" (EMNLP 2020)
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