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...
Guardado en:
| Autores principales: | , , , , , |
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| Formato: | Objeto de conferencia |
| Lenguaje: | Inglés |
| Publicado: |
2011
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| Materias: | |
| Acceso en línea: | http://sedici.unlp.edu.ar/handle/10915/18642 |
| Aporte de: |
| Sumario: | 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 |
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