Towards automatic assessment of the social media impact of news content

Autor:	Tom De Nies, Wesley De Neve, Gerald Haesendonck, Fréderic Godin, Rik Van de Walle, Erik Mannens
Rok vydání:	2013
Předmět:	World Wide Web Content analysis Social media optimization Computer science Key (cryptography) Relevance (information retrieval) Social media Media relations Content (Freudian dream analysis)
Zdroj:	WWW (Companion Volume) Scopus-Elsevier
DOI:	10.1145/2487788.2488069
Popis:	In this paper, we investigate the possibilities to estimate the impact the content of a news article has on social media, and in particular on Twitter. We propose an approach that makes use of captured and temporarily stored microposts found in social media, and compares their relevance to an arbitrary news article. These results are used to derive key indicators of the social media impact of the specified content. We describe each step of our approach, provide a first implementation, and discuss the most imminent challenges and discussion points.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ff158b06ca98f27c3097175374f38d53 https://doi.org/10.1145/2487788.2488069 Zobrazit plný text záznamu