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Identification of trends in the stock prices of a company by performing fundamental analysis of the company. News articles were provided as training data-sets to the model which classified the articles as positive or neutral. Sentiment score was computed by calculating the difference between positive and negative words present in the news articl…
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.
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.
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.
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 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 case-study investigates what was world's reaction on Twitter during covid-19 pandemic. Tweets over a period of 7 months were classified as hate, offensive along with emotions involved.
Replication materials. Máté Á, Sebők M, Barczikay T (2021) The effect of central bank communication on sovereign bond yields: The case of Hungary. PLoS ONE 16(2): e0245515. https://doi.org/10.1371/journal.pone.0245515