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Data Mining for Tweet Sentiment Classification: Twitter Sentiment Analysis

de Groot, Roy

Editore: LAP LAMBERT Academic Publishing, 2012
ISBN 10: 3659295175 / ISBN 13: 9783659295171
Nuovi / Soft cover / Quantità: 1
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Titolo: Data Mining for Tweet Sentiment ...

Casa editrice: LAP LAMBERT Academic Publishing

Data di pubblicazione: 2012

Legatura: Soft cover

Condizione libro: New


Brand New, Unread Copy in Perfect Condition. A+ Customer Service!. Codice inventario libreria ABE_book_new_3659295175

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Riassunto: The goal of this work is to classify short Twitter messages with respect to their sentiment using data mining techniques. Twitter messages, or tweets, are limited to 140 characters. This limitation makes it more difficult for people to express their sentiment and as a consequence, the classification of the sentiment will be more difficult as well. The sentiment can refer to two different types: emotions and opinions. This research is solely focused on the sentiment of opinions. These opinions can be divided into three classes: positive, neutral and negative. The tweets are then classified with an algorithm to one of those three classes. Known supervised learning algorithms as support vector machines and naive Bayes are used to create a prediction model. Before the prediction model can be created, the data has to be pre-processed from text to a fixed-length feature vector. The features consist of sentiment-words and frequently occurring words that are predictive for the sentiment. The learned model is then applied to a test set to validate the model.

L'autore: Roy de Groot is a computer scientist who focuses on data analysis during his study and current work at Avanade Netherlands. He graduated for his bachelor and master Computing Science at the Utrecht University. His master thesis was about tweet sentiment classification, in which he tried to classify tweets with respect to their sentiment.

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