A Curated List of Dataset and Usable Library Resources for NLP in Bahasa Indonesia
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Updated
Feb 17, 2023
A Curated List of Dataset and Usable Library Resources for NLP in Bahasa Indonesia
A comprehensive suite of high-level NLP tasks for Persian language
chakki's Aspect-Based Sentiment Analysis dataset
A collection of scripts to collect crypto market sentiment data
MBTI dataset,Sentiment Dataset,Micro Emotion,微博情感数据集,multi-label Chinese affective computing dataset. personality traits with six emotions and micro-emotions, each annotated with intensity levels.
An automatically annotated sentiment analysis dataset of product reviews in Russian.
Encyclopedic Hub for Sentiment Dictionaries
Repo for Turkish movie reviews dataset.
A perceptron based text classification based on word bag feature extraction and applied on sentiment analysis dataset
WRIME for huggingface datasets
Sentiment analysis of bangla language.
A Sentiment Analysis Dataset of Comments in Serbian
Scikit-Learn & Keras LSTM | Projeto voluntário de análise de sentimentos dos tweets da quarentena | Python
Social network analysis and content moderation system that detects harmful content, identifies influencers, and analyzes information spread using graph neural networks and natural language processing.
Fine-tuned DistilBERT pipeline for employee sentiment analysis. 30-day flight-risk model (R2=0.81, MSE=1.34). 10,000+ records. Dockerized. Springer Capital internship.
Sentiment analysis on 50,000 IMDB reviews using TF-IDF, Word2Vec, and BERT
Repo for Turkish sentiment analysis dataset, "Vitamins and Supplements Customer Reviews"
An advanced investment portfolio optimization engine that merges Modern Portfolio Theory (MPT) with AI-driven Sentiment Analysis. The system calculates optimal asset weights by balancing historical risk-return profiles with real-time market sentiment extracted via Large Language Models (LLMs).
Comparative study for IMDB movie reviews sentiment analysis using Machine Learning (TF-IDF) and Deep Learning architectures (CNN, LSTM, GRU) with pre-trained word embeddings (GloVe, Word2vec, FastText).
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