Bookcover of Data Mining for Tweet Sentiment Classification
Booktitle:

Data Mining for Tweet Sentiment Classification

Twitter Sentiment Analysis

LAP LAMBERT Academic Publishing (2012-11-18 )

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ISBN-13:

978-3-659-29517-1

ISBN-10:
3659295175
EAN:
9783659295171
Book language:
English
Blurb/Shorttext:
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.
Publishing house:
LAP LAMBERT Academic Publishing
Website:
https://www.lap-publishing.com/
By (author) :
Roy de Groot
Number of pages:
108
Published on:
2012-11-18
Stock:
Available
Category:
Informatics
Price:
313.60 R$
Keywords:
Data analysis, text mining, Complex Event Processing, Social Media, Sentiment Analysis, Twitter, Big Data, classication

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