Internet of Reviews

This dataset in Portuguese contains information from 5.094 distinct smart objects collected in a Latin American market. The information includes reviews, questions, and answers, along with sentiment analysis in reviews, questions and answers. In total instances of, 3.093 reviews and 8.877 questions with their respective answers were collected. Additionally, it is possible to gather around 100,000 technical features through the provided links. Sentiment Analysis 🙂: The sentiment analysis was performed using LeIA (Lexicon for Adapted Inference), a fork of the VADER (Valence Aware Dictionary and sEntiment Reasoner) lexicon and sentiment analysis tool adapted for Portuguese texts, which categorizes sentiments as Negative, Neutral, or Positive. More information can be found here: LeIA Data Structure The data was structured by separating it by data type collected as follows: smart_objects_reviews.csv Product reviews have the following structure: review_text: string data containing the review text. rating: integer data containing the review rating. id: String data containing the product ID. sentiment_compound_review: a numerical value from 0 to 1 composed of the probability of the sentiment being positive, negative, or neutral. sentiment_review: a string value that identifies whether the sentiment is positive, negative, or neutral. smart_objects_questions.csv Product questions have the following structure: question: String data containing the customer's question answer: String data containing the seller's answer id: String data containing the product ID. sentiment_compound_question: a numerical value from 0 to 1 composed of the probability of the sentiment being positive, negative, or neutral. sentiment_compound_answer: a numerical value from 0 to 1 composed of the probability of the sentiment being positive, negative, or neutral. sentiment_question: a string value that identifies whether the sentiment is positive, negative, or neutral. sentiment_answer: a string value that identifies whether the sentiment is positive, negative, or neutral. smart_objects_products.csv Product have the following structure: id: String data containing the product ID. link: Data string containing the product link