Modeling Analytical Streams for Social Business Intelligence
Journal Title: Informatics - Year 2018, Vol 5, Issue 3
Abstract
Social Business Intelligence (SBI) enables companies to capture strategic information from public social networks. Contrary to traditional Business Intelligence (BI), SBI has to face the high dynamicity of both the social network’s contents and the company’s analytical requests, as well as the enormous amount of noisy data. Effective exploitation of these continuous sources of data requires efficient processing of the streamed data to be semantically shaped into insightful facts. In this paper, we propose a multidimensional formalism to represent and evaluate social indicators directly from fact streams derived in turn from social network data. This formalism relies on two main aspects: the semantic representation of facts via Linked Open Data and the support of OLAP-like multidimensional analysis models. Contrary to traditional BI formalisms, we start the process by modeling the required social indicators according to the strategic goals of the company. From these specifications, all the required fact streams are modeled and deployed to trace the indicators. The main advantages of this approach are the easy definition of on-demand social indicators, and the treatment of changing dimensions and metrics through streamed facts. We demonstrate its usefulness by introducing a real scenario user case in the automotive sector.
Authors and Affiliations
Indira Lanza-Cruz, Rafael Berlanga and María José Aramburu
Keywords
Related Articles
- EP ID EP44150
- DOI https://doi.org/10.3390/informatics5030033
- Views 269
- Downloads 0
Data Governance in the Sustainable Smart City
The wisdom of ‘smart’ development increasingly shapes urban sustainability in Europe and beyond. Yet, the ‘smart city’ paradigm has been critiqued for favouring technological solutions and business interests over socia...
Interactive Graph Layout of a Million Nodes
Sensemaking of large graphs, specifically those with millions of nodes, is a crucial task in many fields. Automatic graph layout algorithms, augmented with real-time human-in-the-loop interaction, can potentially suppo...
Thermal-Signature-Based Sleep Analysis Sensor
This paper addresses the development of a new technique in the sleep analysis domain. Sleep is defined as a periodic physiological state during which vigilance is suspended and reactivity to external stimulations dimin...
What Is This Sensor and Does This App Need Access to It?
Mobile sensors have already proven to be helpful in different aspects of people’s everyday lives such as fitness, gaming, navigation, etc. However, illegitimate access to these sensors results in a malicious program ru...
A New Co-Evolution Binary Particle Swarm Optimization with Multiple Inertia Weight Strategy for Feature Selection
Feature selection is a task of choosing the best combination of potential features that best describes the target concept during a classification process. However, selecting such relevant features becomes a difficult m...