Document Type

Article

Source of Publication

Computer Science and Information Systems

Publication Date

6-1-2020

Abstract

© 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.

ISSN

1820-0214

Publisher

ComSIS Consortium

Volume

17

Issue

2

First Page

403

Last Page

426

Disciplines

Computer Sciences | Social and Behavioral Sciences

Keywords

Data analytics, Facebook, Sentiment analysis, Social media

Scopus ID

85088567032

Indexed in Scopus

yes

Open Access

yes

Open Access Type

Gold: This publication is openly available in an open access journal/series

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