Social media conversation monitoring: Visualize information contents of twitter messages using conversational metrics

Autor:	Luca Iandoli, Dante Gama Dessavre, Carlo Lipizzi, Jos Emmanuel Ramirez Marquez
Přispěvatelé:	Lipizzi, Carlo, Dessavre, Dante Gama, Iandoli, Luca, Marquez, Josã© Emmanuel Ramirez
Jazyk:	angličtina
Rok vydání:	2016
Předmět:	Conversation analysis Text mining Computer science media_common.quotation_subject 02 engineering and technology Conversation analysi computer.software_genre World Wide Web Social media 0502 economics and business 0202 electrical engineering electronic engineering information engineering Conversation Data mining Visualization General Environmental Science media_common Multimedia Computer Science (all) 05 social sciences Social networking (online) 020207 software engineering Information contents Content analysis Content analysi General Earth and Planetary Sciences 050211 marketing computer Flow visualization
Zdroj:	Procedia Computer Science Scopus ICCS
Popis:	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. © The Authors. Published by Elsevier B.V.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::053b48781ba7fc98a6a80c619c31293f http://hdl.handle.net/11285/628067 Zobrazit plný text záznamu