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Identifying the Topic-Specific Influential Users in Twitter

by May Shalaby, Ahmed Rafea
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 179 - Number 18
Year of Publication: 2018
Authors: May Shalaby, Ahmed Rafea
10.5120/ijca2018916316

May Shalaby, Ahmed Rafea . Identifying the Topic-Specific Influential Users in Twitter. International Journal of Computer Applications. 179, 18 ( Feb 2018), 34-39. DOI=10.5120/ijca2018916316

@article{ 10.5120/ijca2018916316,
author = { May Shalaby, Ahmed Rafea },
title = { Identifying the Topic-Specific Influential Users in Twitter },
journal = { International Journal of Computer Applications },
issue_date = { Feb 2018 },
volume = { 179 },
number = { 18 },
month = { Feb },
year = { 2018 },
issn = { 0975-8887 },
pages = { 34-39 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume179/number18/28970-2018916316/ },
doi = { 10.5120/ijca2018916316 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:55:47.362251+05:30
%A May Shalaby
%A Ahmed Rafea
%T Identifying the Topic-Specific Influential Users in Twitter
%J International Journal of Computer Applications
%@ 0975-8887
%V 179
%N 18
%P 34-39
%D 2018
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Social Influence can be described as the ability to have an effect on the thoughts or actions of others. Influential members in online communities are becoming the new media to market products and sway opinions. Also, their guidance and recommendations can save some people the search time and assist their selective decision making. The objective of this research is to detect the influential users in a specific topic on Twitter. From a collection of tweets matching a specified query, the influential users are to be detected in an online fashion. In order to address this, the issue of which set of features can best lead us to the topic-specific influential users is investigated along with how these features can be expressed in a model to produce a list of ranked influential users.

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Index Terms

Computer Science
Information Sciences

Keywords

Twitter Feature Selection

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