Real-Time Tracking and Mining of Users’ Actions over Social Media

Ejub Kajan¹, Noura Faci², Zakaria Maamar³, Mohamed Sellami⁴, Emir Ugljanin⁵, Hamamache Kheddouci², Dragan H. Stojanović⁵ and Djamal Benslimane²

State University of Novi Pazar
Vuka Karadžica bb, 36300 Novi Pazar, Serbia
dr.ejubkajan@gmail.com
Univ Lyon, Université Claude Bernard Lyon 1, LIRIS
69622, Villeurbanne Cedex, France
firstname.lastname@univ-lyon1.fr
Zayed University
Po Box 19282, Dubai, U.A.E
zakaria.maamar@zu.ac.ae
Télécom SudParis, SAMOVAR, Institut Polytechnique de Paris
91011, Evry Cedex, France
mohamed.sellami@telecom-sudparis.eu
University of Niš
Aleksandra Medvedeva 14, 18106 Niš, Serbia
emirugljanin@gmail.com, dragan.stojanovic@elfak.ni.ac.rs

Abstract

With the advent of Web 2.0 technologies and social media, companies are actively looking for ways to know and understand what users think and say about their products and services. Indeed, it has become the practice that users go online using social media like Facebook to raise concerns, make comments, and share recommendations. All these actions can be tracked in real-time and then mined using advanced techniques like data analytics and sentiment analysis. This paper discusses such tracking and mining through a system called Social Miner that allows companies to make decisions about what, when, and how to respond to users’ actions over social media. Questions that Social Miner allows to answer include what actions were frequently executed and why certain actions were executed more than others.

Key words

Data analytics, Facebook, Sentiment analysis, Social media

Digital Object Identifier (DOI)

https://doi.org/10.2298/CSIS190822002K

Publication information

Volume 17, Issue 2 (June 2020)
Year of Publication: 2020
ISSN: 2406-1018 (Online)
Publisher: ComSIS Consortium

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How to cite

Kajan, E., Faci, N., Maamar, Z., Sellami, M., Ugljanin, E., Kheddouci, H., Stojanović, D. H., Benslimane, D.: Real-Time Tracking and Mining of Users’ Actions over Social Media. Computer Science and Information Systems, Vol. 17, No. 2, 403–426. (2020), https://doi.org/10.2298/CSIS190822002K