Name
Abstract | ||
|---|---|---|
A novel, simple, and effective approach to modeling online user behavior extracts and analyzes digital DNA sequences from user online actions and uses Twitter as a benchmark to test the proposal. Specifically, the model obtains an incisive and compact DNA-inspired characterization of user actions. Then, standard DNA analysis techniques discriminate between genuine and spambot accounts on Twitter. ... |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/MIS.2016.29 | IEEE Intelligent Systems |
Keywords | DocType | Volume |
DNA,Twitter,Biological information theory,Fingerprint recognition,Data mining,Media,Bioinformatics,Knowledge management,Social sciences | Journal | 31 |
Issue | ISSN | Citations |
5 | 1541-1672 | 19 |
PageRank | References | Authors |
0.65 | 6 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Cresci, S. | 1 | 235 | 21.79 |
| Roberto Di Pietro | 2 | 2337 | 162.88 |
| Marinella Petrocchi | 3 | 362 | 44.01 |
| Angelo Spognardi | 4 | 391 | 30.19 |
| Maurizio Tesconi | 5 | 281 | 32.06 |