GitHub / rochitasundar / Twitter-Sentiment-Analysis

Data consists of tweets scrapped using Twitter API. Objective is sentiment labelling using a lexicon approach, performing text pre-processing (such as language detection, tokenisation, normalisation, vectorisation), building pipelines for text classification models for sentiment analysis, followed by explainability of the final classifier

JSON API: https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rochitasundar%2FTwitter-Sentiment-Analysis

Topics: feature-importance, gridsearchcv, lemmatization, linearsvc-model, multinomial-naive-bayes, pipeline, random-forest, regex, sentiment-classification, stemming-porters, stratified-sampling, textblob, tfidfvectorizer, xgboost-model

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