Modeling Topic Specific Credibility in Twitter Based on Structural and Attribute Properties

Md Habibur Rahman; Tabia Tanzin Prama; Md Musfique Anwar

doi:10.1007/978-3-030-73050-5_57

Modeling Topic Specific Credibility in Twitter Based on Structural and Attribute Properties

Md Habibur Rahman^*
, Tabia Tanzin Prama
, Md Musfique Anwar

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Scopus citations

Abstract

Online social networks (OSNs) are the most popular medium for users to generate and share their contents in various formats such as tweets, images, videos etc. with any number of peers. Thus, information on any topic diffuse very rapidly in OSNs. Therefore, it is very crucial to extract credible information from these mass volume of social user-generated contents. Existing research works on measuring trustworthiness of any content in OSNs are mainly focused on contents generated by the social users. Again, those works paid less attention to the structure of the social network. In this work, we propose an approach to measure the level of credibility of a piece of information in OSNs based on latent content of the information and the structural properties of the underlying social network.

Original language	English
Title of host publication	Hybrid Intelligent Systems - 20th International Conference on Hybrid Intelligent Systems, HIS 2020
Editors	Ajith Abraham, Thomas Hanne, Oscar Castillo, Niketa Gandhi, Tatiane Nogueira Rios, Tzung-Pei Hong
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	580-589
Number of pages	10
ISBN (Print)	9783030730499
DOIs	https://doi.org/10.1007/978-3-030-73050-5_57
State	Published - 2021
Externally published	Yes

Publication series

Name	Advances in Intelligent Systems and Computing
Volume	1375 AIST
ISSN (Print)	2194-5357
ISSN (Electronic)	2194-5365

Bibliographical note

Publisher Copyright:
© 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Keywords

Information credibility
Online social networks
Structural property
User-generated content

ASJC Scopus subject areas

Control and Systems Engineering
General Computer Science

Access to Document

10.1007/978-3-030-73050-5_57

Cite this

Rahman, M. H., Prama, T. T., & Anwar, M. M. (2021). Modeling Topic Specific Credibility in Twitter Based on Structural and Attribute Properties. In A. Abraham, T. Hanne, O. Castillo, N. Gandhi, T. Nogueira Rios, & T.-P. Hong (Eds.), Hybrid Intelligent Systems - 20th International Conference on Hybrid Intelligent Systems, HIS 2020 (pp. 580-589). (Advances in Intelligent Systems and Computing; Vol. 1375 AIST). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-73050-5_57

Rahman, Md Habibur ; Prama, Tabia Tanzin ; Anwar, Md Musfique. / Modeling Topic Specific Credibility in Twitter Based on Structural and Attribute Properties. Hybrid Intelligent Systems - 20th International Conference on Hybrid Intelligent Systems, HIS 2020. editor / Ajith Abraham ; Thomas Hanne ; Oscar Castillo ; Niketa Gandhi ; Tatiane Nogueira Rios ; Tzung-Pei Hong. Springer Science and Business Media Deutschland GmbH, 2021. pp. 580-589 (Advances in Intelligent Systems and Computing).

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title = "Modeling Topic Specific Credibility in Twitter Based on Structural and Attribute Properties",

abstract = "Online social networks (OSNs) are the most popular medium for users to generate and share their contents in various formats such as tweets, images, videos etc. with any number of peers. Thus, information on any topic diffuse very rapidly in OSNs. Therefore, it is very crucial to extract credible information from these mass volume of social user-generated contents. Existing research works on measuring trustworthiness of any content in OSNs are mainly focused on contents generated by the social users. Again, those works paid less attention to the structure of the social network. In this work, we propose an approach to measure the level of credibility of a piece of information in OSNs based on latent content of the information and the structural properties of the underlying social network.",

keywords = "Information credibility, Online social networks, Structural property, User-generated content",

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Rahman, MH, Prama, TT & Anwar, MM 2021, Modeling Topic Specific Credibility in Twitter Based on Structural and Attribute Properties. in A Abraham, T Hanne, O Castillo, N Gandhi, T Nogueira Rios & T-P Hong (eds), Hybrid Intelligent Systems - 20th International Conference on Hybrid Intelligent Systems, HIS 2020. Advances in Intelligent Systems and Computing, vol. 1375 AIST, Springer Science and Business Media Deutschland GmbH, pp. 580-589. https://doi.org/10.1007/978-3-030-73050-5_57

Modeling Topic Specific Credibility in Twitter Based on Structural and Attribute Properties. / Rahman, Md Habibur; Prama, Tabia Tanzin; Anwar, Md Musfique.
Hybrid Intelligent Systems - 20th International Conference on Hybrid Intelligent Systems, HIS 2020. ed. / Ajith Abraham; Thomas Hanne; Oscar Castillo; Niketa Gandhi; Tatiane Nogueira Rios; Tzung-Pei Hong. Springer Science and Business Media Deutschland GmbH, 2021. p. 580-589 (Advances in Intelligent Systems and Computing; Vol. 1375 AIST).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Modeling Topic Specific Credibility in Twitter Based on Structural and Attribute Properties

AU - Rahman, Md Habibur

AU - Prama, Tabia Tanzin

AU - Anwar, Md Musfique

PY - 2021

Y1 - 2021

N2 - Online social networks (OSNs) are the most popular medium for users to generate and share their contents in various formats such as tweets, images, videos etc. with any number of peers. Thus, information on any topic diffuse very rapidly in OSNs. Therefore, it is very crucial to extract credible information from these mass volume of social user-generated contents. Existing research works on measuring trustworthiness of any content in OSNs are mainly focused on contents generated by the social users. Again, those works paid less attention to the structure of the social network. In this work, we propose an approach to measure the level of credibility of a piece of information in OSNs based on latent content of the information and the structural properties of the underlying social network.

AB - Online social networks (OSNs) are the most popular medium for users to generate and share their contents in various formats such as tweets, images, videos etc. with any number of peers. Thus, information on any topic diffuse very rapidly in OSNs. Therefore, it is very crucial to extract credible information from these mass volume of social user-generated contents. Existing research works on measuring trustworthiness of any content in OSNs are mainly focused on contents generated by the social users. Again, those works paid less attention to the structure of the social network. In this work, we propose an approach to measure the level of credibility of a piece of information in OSNs based on latent content of the information and the structural properties of the underlying social network.

KW - Information credibility

KW - Online social networks

KW - Structural property

KW - User-generated content

UR - https://www.scopus.com/pages/publications/85105952246

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DO - 10.1007/978-3-030-73050-5_57

M3 - Conference contribution

AN - SCOPUS:85105952246

SN - 9783030730499

T3 - Advances in Intelligent Systems and Computing

SP - 580

EP - 589

BT - Hybrid Intelligent Systems - 20th International Conference on Hybrid Intelligent Systems, HIS 2020

A2 - Abraham, Ajith

A2 - Hanne, Thomas

A2 - Castillo, Oscar

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A2 - Nogueira Rios, Tatiane

A2 - Hong, Tzung-Pei

PB - Springer Science and Business Media Deutschland GmbH

ER -

Rahman MH, Prama TT, Anwar MM. Modeling Topic Specific Credibility in Twitter Based on Structural and Attribute Properties. In Abraham A, Hanne T, Castillo O, Gandhi N, Nogueira Rios T, Hong TP, editors, Hybrid Intelligent Systems - 20th International Conference on Hybrid Intelligent Systems, HIS 2020. Springer Science and Business Media Deutschland GmbH. 2021. p. 580-589. (Advances in Intelligent Systems and Computing). doi: 10.1007/978-3-030-73050-5_57

Modeling Topic Specific Credibility in Twitter Based on Structural and Attribute Properties

Abstract

Publication series

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

Fingerprint

Cite this