Name
Abstract | ||
|---|---|---|
Social media analysis has become a major issue not only for marketing and business, but also in a wide variety of other fields such as catastrophes and politics. Social media contents that are created in real-time by users contain elements related to time and location, and by analyzing this, it is possible to make predictions through trajectory analysis by extracting the trajectory in which the contents are spread out. In this study, we use AsterixDB that reflects the features for processing large quantities of social media contents in real-time to analyze social media contents, and propose a trajectory analysis system that extracts keyword trajectories to verify its effectiveness through experiment. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1145/3022227.3022272 | IMCOM |
Field | DocType | Citations |
Data science,Social media,Computer science,Real-time computing,Trajectory analysis,Multimedia,Trajectory | Conference | 2 |
PageRank | References | Authors |
0.41 | 13 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| So-Yeop Yoo | 1 | 5 | 1.80 |
| Taesoo Park | 2 | 2 | 0.41 |
| Jein Song | 3 | 2 | 0.41 |
| Ok-Ran Jeong | 4 | 181 | 22.02 |