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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.identifier.uri |
http//localhost:8080/jspui/handle/123456789/1705 |
|
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.sponsorship |
Nait-Hamoud mohamed cherif |
en_US |
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 |
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