Identifying the topic-specific influential users using SLM

Authors

May Shalaby, American University in Cairo
Ahmed Rafea, American University in CairoFollow

Files

Department

Computer Science & Engineering Department

Abstract

[abstract not available]

Publication Date

2-29-2016

Document Type

Book Chapter

Book Title

Proceedings - 1st International Conference on Arabic Computational Linguistics: Advances in Arabic Computational Linguistics, ACLing 2015

ISBN

SCOPUS_ID:84969760851

Publisher

IEEE

City

Cairo, Egypt

First Page

118

Last Page

123

Keywords

Arabic, Influence, Linguistic Analysis, SLM, Social Networks, Twitter

Recommended Citation

APA Citation

Shalaby, M. & Rafea, A. (2016). Identifying the topic-specific influential users using SLM. Proceedings - 1st International Conference on Arabic Computational Linguistics: Advances in Arabic Computational Linguistics, ACLing 2015 (pp. 118-123). IEEE.

MLA Citation

Shalaby, May, et al. "Identifying the topic-specific influential users using SLM." Proceedings - 1st International Conference on Arabic Computational Linguistics: Advances in Arabic Computational Linguistics, ACLing 2015, IEEE, 2016. pp. 118-123