Compute the sentiment of each tweet based on the sentiment scores of the terms in the tweet. The sentiment of a tweet is equivalent to the sum of the sentiment scores for each term in the tweet.

Sentiment analysis of tweets using oauth2 in python.

This project uses Lexicon-based approach for sentimental analysis of 1000 recent tweets of 4 countries. A sentiment score for each tweet is computed to ascertain the overall nature of the tweet.

A sentiment analyser in R that pulls tweets related to cryptocurrencies and plots the graphs related to how +ve or -ve the tweets are. Analyses BTC, ETH and LTC

This small project uses TextBlob to analyze twitter data from a user-provided city name

Sentiment Scores (Polarity) of ASCII emoticons

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

Instagram Reimagined : Sentiment Analysis of Captions

A repository for the Modern Java Technologies Course @ FMI

Extract sentiment of every US public company from financial news headlines

Twitter Feeds were analysed during the Lok Sabha Elections 2019 to guage the overall popularities of each party and predict the winner based solely on the tweets made by the population. This was made as a part of our Data Science course (UE18CS203) at PES University.

A rating-based sentiment dataset of IMDB movie reviews (WASSA 2014)

Sentiment classifier and polarity lexicon creator

This project uses BERT(Bidirectional Encoder Representations from Transformers) for Yelp-5 fine-grained sentiment analysis. It also explores various custom loss functions for regression based approaches of fine-grained sentiment analysis.

Sentiment Analysis on Game Review using TextBlob-lexicon and rule-based sentiment.

Banglish -> Bangla (With avro phonetic) -> English (With textblob translator) -> Sentiment

The R code of implementation is provided.

A Web Scraping project to analyze product reviews in Amazon.com. A sentiment analysis is done and the reviews are sorted and highlighted in green or red based on the sentiment score.