Hashformers is a framework for hashtag segmentation with Transformers and Large Language Models (LLMs).
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Updated
Jun 4, 2023 - Python
Hashformers is a framework for hashtag segmentation with Transformers and Large Language Models (LLMs).
implementing an end-to-end tweets ETL/Analysis pipeline.
Exploring Jaccard and Cosine similarities performances then visualising their output using k means and kmeans with pca. Additional input on time series analysis, web scrapping and twitter scrapping.
Dataset: Fighting the COVID-19 Infodemic: Modeling the Perspective of Journalists, Fact-Checkers, Social Media Platforms, Policy Makers, and the Society
This project is submitted as python implementation in the contest of Analytics Vidhya called "Identify the Sentiments". I enjoyed the joining of this competition and all its process. This submited solution got the rank 118 in the public leaderboard.
Text Classification Using Siamese Neural Networks - Contrastive Loss, Triplet Loss. This architecture works well when the training data is less.
Tweets Sentiment Analysis Project to classify the the polarity of tweets either as ‘Positive’, ‘Negative’, and ‘Neutral' with high accuracy
Notebook used to explore and classify 500,000 tweets about Elon Musk in an unsupervised manner.
Python Notebooks for Collecting Tweets and Analyze their text using various text classification and clustering techniques
Twish is a web application that allows you to host tweets classifiers (Machine Learning-based, rule-based, whatever-based). Once you have set up the app, your users can enter a search term and Twish will collect tweets based on it and classify them using the classifiers you set up.
Sentiment Analysis On Financial Tweets
Sentiment analysis of tweets using machine learning
Kaggle NLP warm up.
A project about Sentiment analysis on Corona tweets
Submission for CL4HEALTH @ LREC-COLING 2024
Corona Tweets Sentiment Classification with BiLSTM
This repository is a project looking at tweets that used the #BLM and analyzed the sentiment and words used as well as utilized topic modeling with Latent Semantic Analysis and Latent Dirichlet Allocation to pull out the main themes that are used when the #BLM is used.
This repository presents my bachelor project titled "Mapping and Tracking Sentiment Arcs in Social Media Streams"
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