Sentiment analysis in microblogging: a practical implementation

This paper presents a system that can take short messages relevant to a particular topic from a microblogging service such as Twitter or Facebook, analyze the messages for the sentiments they carry on, and classify them. In particular, the system addresses this problem by retrieving raw data from Tw...

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Detalles Bibliográficos
Autores principales: Cohen, Mauro, Damiani, Pablo, Durandeu, Sebastián, Navas, Renzo, Merlino, Hernán, Fernández, Enrique
Formato: Objeto de conferencia
Lenguaje:Inglés
Publicado: 2011
Materias:
Ciencias Informáticas
microblogging
Information Search and Retrieval
Web-based services
NLTK
Python
Twitter
social web
text mining
opinion mining
sentiment classification
sentiment analysis
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/18642
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-18642
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Informáticas
microblogging
Information Search and Retrieval
Web-based services
NLTK
Python
Twitter
social web
text mining
opinion mining
sentiment classification
sentiment analysis
spellingShingle Ciencias Informáticas
microblogging
Information Search and Retrieval
Web-based services
NLTK
Python
Twitter
social web
text mining
opinion mining
sentiment classification
sentiment analysis
Cohen, Mauro
Damiani, Pablo
Durandeu, Sebastián
Navas, Renzo
Merlino, Hernán
Fernández, Enrique
Sentiment analysis in microblogging: a practical implementation
topic_facet Ciencias Informáticas
microblogging
Information Search and Retrieval
Web-based services
NLTK
Python
Twitter
social web
text mining
opinion mining
sentiment classification
sentiment analysis
description This paper presents a system that can take short messages relevant to a particular topic from a microblogging service such as Twitter or Facebook, analyze the messages for the sentiments they carry on, and classify them. In particular, the system addresses this problem by retrieving raw data from Twitter - one of the most popular microblogging platforms - pre-processing on that raw data, and finally analyzing it using machine learning techniques to classify them by sentiment as either positive or negative
format Objeto de conferencia
Objeto de conferencia
author Cohen, Mauro
Damiani, Pablo
Durandeu, Sebastián
Navas, Renzo
Merlino, Hernán
Fernández, Enrique
author_facet Cohen, Mauro
Damiani, Pablo
Durandeu, Sebastián
Navas, Renzo
Merlino, Hernán
Fernández, Enrique
author_sort Cohen, Mauro
title Sentiment analysis in microblogging: a practical implementation
title_short Sentiment analysis in microblogging: a practical implementation
title_full Sentiment analysis in microblogging: a practical implementation
title_fullStr Sentiment analysis in microblogging: a practical implementation
title_full_unstemmed Sentiment analysis in microblogging: a practical implementation
title_sort sentiment analysis in microblogging: a practical implementation
publishDate 2011
url http://sedici.unlp.edu.ar/handle/10915/18642
work_keys_str_mv AT cohenmauro sentimentanalysisinmicrobloggingapracticalimplementation
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AT durandeusebastian sentimentanalysisinmicrobloggingapracticalimplementation
AT navasrenzo sentimentanalysisinmicrobloggingapracticalimplementation
AT merlinohernan sentimentanalysisinmicrobloggingapracticalimplementation
AT fernandezenrique sentimentanalysisinmicrobloggingapracticalimplementation
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