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Authors: Indira Lázara Lanza Cruz and Rafael Berlanga Llavori

Affiliation: Llenguatges I Sistemes Informatics, Universitat Jaume I, Castellón and Spain

Keyword(s): Social Business Intelligence, Indicators, Data Streaming.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Business Analytics ; Business Intelligence Applications ; Data Analytics ; Data Engineering ; Interactive and Online Data Mining ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Mining Text and Semi-Structured Data ; Soft Computing ; Symbolic Systems ; Web Mining

Abstract: In this paper we present a framework based on Linked Open Data Infrastructures to perform analysis tasks in social networks based on dynamically defined indicators. Based on the typical stages of business intelligence models, which starts from the definition of strategic goals to define relevant indicators (Key Performance Indicators), we propose a new scenario where the sources of information are the social networks. The fundamental contribution of this work is to provide a framework for easily specifying and monitoring social indicators based on the measures offered by the APIs of the most important social networks. The main novelty of this method is that all the involved data and information is represented and stored as Linked Data. In this work we demonstrate the benefits of using linked open data, especially for processing and publishing company-specific social metrics and indicators.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Lanza Cruz, I. and Berlanga Llavori, R. (2018). Defining Dynamic Indicators for Social Network Analysis: A Case Study in the Automotive Domain using Twitter. In Proceedings of the 10th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2018) - KDIR; ISBN 978-989-758-330-8; ISSN 2184-3228, SciTePress, pages 221-228. DOI: 10.5220/0006932902210228

@conference{kdir18,
author={Indira Lázara {Lanza Cruz}. and Rafael {Berlanga Llavori}.},
title={Defining Dynamic Indicators for Social Network Analysis: A Case Study in the Automotive Domain using Twitter},
booktitle={Proceedings of the 10th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2018) - KDIR},
year={2018},
pages={221-228},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006932902210228},
isbn={978-989-758-330-8},
issn={2184-3228},
}

TY - CONF

JO - Proceedings of the 10th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2018) - KDIR
TI - Defining Dynamic Indicators for Social Network Analysis: A Case Study in the Automotive Domain using Twitter
SN - 978-989-758-330-8
IS - 2184-3228
AU - Lanza Cruz, I.
AU - Berlanga Llavori, R.
PY - 2018
SP - 221
EP - 228
DO - 10.5220/0006932902210228
PB - SciTePress

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