| Autor: |
Lipizzi, Carlo, Marquez, José Emmanuel Ramirez, Dessavre, Dante Gama, Iandoli, Luca |
| Předmět: |
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| Zdroj: |
Procedia Computer Science; 2016, Vol. 80, p2216-2220, 5p |
| Abstrakt: |
In this paper we present a novel method to extract and visualize actionable information from streams of social media messages, analyzed as conversational elements. Our method has been applied to over 4 million messages related to more than 35 different events, demonstrating good results identifying conversational patterns. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Supplemental Index |
| Externí odkaz: |
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