Name
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 rec-ommendations. 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 com-panies to make decisions about what, when, and how to respond to users' actions over social media. Questions that Social Miner allows to answer in-clude what actions were frequently executed and why certain actions were executed more than others. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.2298/CSIS190822002K | COMPUTER SCIENCE AND INFORMATION SYSTEMS |
Keywords | DocType | Volume |
Data analytics,Facebook,Sentiment analysis,Social media | Journal | 17 |
Issue | ISSN | Citations |
2 | 1820-0214 | 0 |
PageRank | References | Authors |
0.34 | 0 | 8 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ejub Kajan | 1 | 18 | 5.37 |
| Noura Faci | 2 | 228 | 27.53 |
| Zakaria Maamar | 3 | 0 | 0.34 |
| Mohamed Sellami | 4 | 24 | 10.59 |
| Emir Ugljanin | 5 | 6 | 8.26 |
| Hamamache Kheddouci | 6 | 339 | 53.61 |
| Dragana Stojanovic | 7 | 0 | 0.34 |
| Djamal Benslimane | 8 | 932 | 90.92 |