Information Epicenters Detection Based on the content of interaction
| dc.contributor.author | Guehairia, Oussama | |
| dc.contributor.author | Daouadi, Khair Eddine | |
| dc.date.accessioned | 2022-02-27T08:20:52Z | |
| dc.date.available | 2022-02-27T08:20:52Z | |
| dc.date.issued | 2016 | |
| dc.description.abstract | Detecting influence in online social networks is a new line of research that has not been extensively explored by researchers. Difficult to be performed on a large scale in the past, but with the recent boom in social media, written opinions are easier to attain, allowing this interesting problem to be explored. In this work, we have proposed a new approach for influencers detection. For this purpose, we have investigated on information cascade. The proposed approach is promising since it leverages web intelligence to integrate semantics to the problem of influencers detection in social networks. | en_US |
| dc.description.provenance | Submitted by snv snv (dspace.snv@univ-tebessa.dz) on 2022-02-27T08:20:52Z No. of bitstreams: 1 inf 09.rar: 2404957 bytes, checksum: aa258e9b59414157e4bf8492767110af (MD5) | en |
| dc.description.provenance | Made available in DSpace on 2022-02-27T08:20:52Z (GMT). No. of bitstreams: 1 inf 09.rar: 2404957 bytes, checksum: aa258e9b59414157e4bf8492767110af (MD5) Previous issue date: 2016 | en |
| dc.description.sponsorship | Nait-Hamoud mohamed cherif | en_US |
| dc.identifier.uri | http//localhost:8080/jspui/handle/123456789/1705 | |
| dc.language.iso | en | en_US |
| dc.publisher | Universite laarbi tebessi tebessa | en_US |
| dc.subject | Information Epicenters: Detection Based : content of interaction | en_US |
| dc.title | Information Epicenters Detection Based on the content of interaction | en_US |
| dc.type | Thesis | en_US |