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Sentiment analysis in microblogging: a practical implementation

Cohen, Mauro et al · SEDICI UNLP · 2011

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Author / responsible party
Cohen, Mauro et al
Publisher
SEDICI UNLP
Year
2011
Language
English

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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 Presentado en el XII Workshop Agentes y Sistemas Inteligentes (WASI) Red de Universidades con Carreras en Informática (RedUNCI)

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APA 7

Cohen, M. E. A. (2011). Sentiment analysis in microblogging: a practical implementation. SEDICI UNLP. http://sedici.unlp.edu.ar/handle/10915/18642

MLA

Cohen, Mauro et al. Sentiment analysis in microblogging: a practical implementation. SEDICI UNLP, 2011. http://sedici.unlp.edu.ar/handle/10915/18642.

Chicago

Cohen, Mauro et al. 2011. Sentiment analysis in microblogging: a practical implementation. SEDICI UNLP. http://sedici.unlp.edu.ar/handle/10915/18642.

Harvard

Cohen, M. E. A. 2011, Sentiment analysis in microblogging: a practical implementation, SEDICI UNLP, available at: http://sedici.unlp.edu.ar/handle/10915/18642 [Accessed 6 Aug. 2026].

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Title
Sentiment analysis in microblogging: a practical implementation
Author / contributors
Cohen, Mauro et al
Publisher
SEDICI UNLP
Publication year
2011
Language
English

Subjects

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Ciencias Informáticas; microblogging; Information Search and Retrieval; Web-based services; NLTK; Python; Twitter; social web; text mining; opinion mining; sentiment classification; sentiment analysis
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