Source of Publication
Computer Science and Information Systems
© 2020, ComSIS Consortium. All rights reserved. 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.
Computer Sciences | Social and Behavioral Sciences
Data analytics, Facebook, Sentiment analysis, Social media
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Kajan, Ejub; Faci, Noura; Maamar, Zakaria; Sellami, Mohamed; Ugljanin, Emir; Kheddouci, Hamamache; Stojanović, Dragan H.; and Benslimane, Djamal, "Real-time tracking and mining of users’ actions over social media" (2020). All Works. 2886.
Indexed in Scopus
Open Access Type
Gold: This publication is openly available in an open access journal/series