A Pipeline for Multimedia Twitter Analysis through Graph Databases: Preliminary Results

Roberto Boselli, Mirko Cesarini, Fabio Mercorio, Mario Mezzanzanica, Alessandro Vaccarino

Abstract

Twitter is a microblogging service where users post not only short messages, but also images and other multimedia contents. Twitter can be used for analyzing people public discussions, as a huge amount of messages are continuously broadcasted by users. Analysis have usually focused on the textual part of messages, but the non-negligible number of images exchanged calls for specific attention. In this paper we describe how the tweet multimedia contents can be turned into a knowledge graph and then used for analyzing the messages sent during marketing campaigns. The information extraction and processing pipeline is built on top of off-theshelf APIs and products while the obtained knowledge is modelled through a Graph Database. The resulting knowledge graph was useful to explore and identify similarities among different marketing campaigns carried out using Twitter, providing some preliminary but promising results.

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Paper Citation


in Harvard Style

Boselli R., Cesarini M., Mercorio F., Mezzanzanica M. and Vaccarino A. (2017). A Pipeline for Multimedia Twitter Analysis through Graph Databases: Preliminary Results . In - KomIS, ISBN , pages 0-0. DOI: 10.5220/0006490703430349


in Bibtex Style

@conference{komis17,
author={Roberto Boselli and Mirko Cesarini and Fabio Mercorio and Mario Mezzanzanica and Alessandro Vaccarino},
title={A Pipeline for Multimedia Twitter Analysis through Graph Databases: Preliminary Results},
booktitle={ - KomIS,},
year={2017},
pages={},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006490703430349},
isbn={},
}


in EndNote Style

TY - CONF
JO - - KomIS,
TI - A Pipeline for Multimedia Twitter Analysis through Graph Databases: Preliminary Results
SN -
AU - Boselli R.
AU - Cesarini M.
AU - Mercorio F.
AU - Mezzanzanica M.
AU - Vaccarino A.
PY - 2017
SP - 0
EP - 0
DO - 10.5220/0006490703430349