textmining

Data Science projects using Python, SQL, R, and Machine Learning

Code and analysis for "Local-global linkages in biodiversity governance" project

Sentiment analysis web app for Bank Jago reviews using Custom BiLSTM and GloVe embeddings. Built with Python and Streamlit.

A machine learning-based sentiment analysis application designed to classify text as positive or negative.

Data, analysis code, and reproducible outputs for the PACIS 2025 paper on AI curriculum and industry-demand alignment in Taiwan.

AI pipeline that mines Spotify user reviews to answer why people struggle to discover new music: collect → filter → LLM-tag (theme/sentiment/pain point) → synthesize findings. Runnable in Google Colab with no API key.

Financial news headlines offer valuable NLP data for predicting stock performance through sentiment analysis. In Finance and Banking, language serves as a key tool for analysis, capturing emotional nuances that influence investor behavior and market dynamics. The project focuses on understanding how the subtleties of financial language impact diffe

8:22 AMSMS Spam Detection using NLP & Machine Learning — classifying messages as Spam or Ham with 95.78% accuracy.

R package (in development) for retrieving, cleaning, and organizing botanical data from Flora e Funga do Brasil. It includes tools for extracting species descriptions, performing text mining to obtain functional traits, and manipulating data for ecological and taxonomic analyses.

Data and code associated with the manuscript "Reasoning Models for Text Mining in Oncology – a Comparison Between o1 Preview, GPT-4o, and GPT-5 at Different Reasoning Levels".

Text mining and analysis of “data available upon request” statements in scientific articles.

Biomedical RAG Tool for Gene - Disease Association

R-package to parse exported WhatsApp chatlog files to use them for quantifying interpersonal relationships trough textmining and meta-data

An NLP powered application that includes features for spam detection, sentiment analysis, stress detection, hate & offensive content detection, alongwith sarcasm detection. It leverages Natural Language Processing (NLP) techniques and ML models to analyze & classify text inputs, enabling smarter content moderation & emotional insights.

Charla sobre tutorial learnr para textmining - LatinR

This repository showcases data-driven text analytics using NLP techniques. It combines text preprocessing, sentiment scoring, and structured data extraction to convert unstructured text into business-ready datasets.

Word co-occurrence network analysis and visualization using Python, NLTK, and NetworkX

Text Mining project - Artificial Intelligence, Vrije University,2025