349725

An Analytical Based Model For Remarking Online Conversations

Article

Last updated: 03 Jan 2025

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Tags

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Abstract

The massive amount of social media data is considered as an effective resource to extract valuable knowledge. Nowadays, the social media analytical became an advanced informatics tool for collecting, monitoring, and analyzing data. So, it supports the business needs for improving the product and service in order to increase their profit. This paper proposes an analytical model for remarking online conversation and estimating the customer's perception based on the machine learning techniques. In addition, it investigates the impact of brand community features on the customer's perception. Based on that, the online conversation is automatically remarked by the degree of conversation polarity as well as the impact of brand community. Finally, The findings emphasized that the brand community features have an impact on the customer's perception in percentage up to 45.6%. Also, it realized that in many statuses the remarks provide a significant feedback that forces the business for making decision and enhancing capabilities.

DOI

10.21608/ijicis.2024.261424.1314

Keywords

social media analytical, Conversation Polarity, automatic remark

Authors

First Name

Eman

Last Name

Elsayed Mahmoud

MiddleName

-

Affiliation

computer science department, CIC

Email

emanelsayedmahmoud@gmail.com

City

-

Orcid

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Volume

24

Article Issue

1

Related Issue

46955

Issue Date

2024-03-01

Receive Date

2024-01-08

Publish Date

2024-03-31

Page Start

105

Page End

115

Print ISSN

1687-109X

Online ISSN

2535-1710

Link

https://ijicis.journals.ekb.eg/article_349725.html

Detail API

https://ijicis.journals.ekb.eg/service?article_code=349725

Order

349,725

Type

Original Article

Type Code

494

Publication Type

Journal

Publication Title

International Journal of Intelligent Computing and Information Sciences

Publication Link

https://ijicis.journals.ekb.eg/

MainTitle

An Analytical Based Model For Remarking Online Conversations

Details

Type

Article

Created At

23 Dec 2024