In the era of social media, the huge availability of digital data allows to develop several types of research in a wide range of fields. Such data is characterized by several advantages: reduced collection costs, short retrieval times and production of almost real-time outputs. At the same time, this data is unstructured and unclassified in terms of con-tent. This study aims to develop an efficient way to filter and analyze tweets by means of sentiment related to a specific topic.

(2020). Semiautomatic dictionary-based classification of environment tweets by topic . Retrieved from http://hdl.handle.net/10446/168948

Semiautomatic dictionary-based classification of environment tweets by topic

Cameletti, Michela;Schlosser, Stephan;Toninelli, Daniele;Fabris Silvia
2020-01-01

Abstract

In the era of social media, the huge availability of digital data allows to develop several types of research in a wide range of fields. Such data is characterized by several advantages: reduced collection costs, short retrieval times and production of almost real-time outputs. At the same time, this data is unstructured and unclassified in terms of con-tent. This study aims to develop an efficient way to filter and analyze tweets by means of sentiment related to a specific topic.
2020
Cameletti, Michela; Schlosser, Stephan Heinrich; Toninelli, Daniele; Fabris, Silvia
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10446/168948
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