An off-the-shelf pre-trained Tweet NLP Toolkit (NER, tokenization, lemmatization, POS tagging, dependency parsing) + Tweebank-NER dataset
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Updated
Jan 24, 2024 - Python
An off-the-shelf pre-trained Tweet NLP Toolkit (NER, tokenization, lemmatization, POS tagging, dependency parsing) + Tweebank-NER dataset
Hashformers is a framework for hashtag segmentation with Transformers and Large Language Models (LLMs).
Like and retweet your tweets, or search tweets by topic. It stores and serves data with a Flask webapp. 🐦 Live demo running on twitter.com/ai_testing
FinABSA is a T5-Large model trained for Aspect-Based Sentiment Analysis specifically for financial domains.
Blazing fast topic modelling for short texts.
Python package to clean raw tweets for ML applications.
Implementation of an ETL process for real-time sentiment analysis of tweets with Docker, Apache Kafka, Spark Streaming, MongoDB and Delta Lake
How Will Your Tweet Be Received? Predicting theSentiment Polarity of Tweet Replies
Music for your Mood! Tweet at us and we got you covered!
twig.py - a twitter web3 influencer truffle pig used for finding engaged users
Scrape tweets without authentication using Selenium WebDriver
Easily search tweets for topic-relevant hashtags.
Computer science master's degree project for Big Data exam. Sentiment Analysis using Lexicon with Italian tweets.
Assignment to scrape tweets based on hashtags and then analyse them through a sociological lens.
We are scraping the data from the social media Twetter to collect data about Bitcoin, the famous crypto-currency. After cleaning those data and place them in a pandas dataframe, our program is doing a sentimental analysis on each tweet and return the polarity.
learning python day 15
En esta práctica se empaqueta y distribuye una aplicación Python que descarga y analiza tweets en función de puntuaciones de sentimiento. Los resultados del análisis se guardan en una base de datos MongoDB, y la información se muestra en la web.
VADER-analysis of recent tweets by keyword
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