Classification of Social Media Users Based on Temporal Behaviors and Interests

Murad Hossen; Tamanna Afrose; Atashi Mani Ghosh; Md Musfique Anwar

doi:10.1007/978-981-16-1089-9_72

Classification of Social Media Users Based on Temporal Behaviors and Interests

Murad Hossen^*, Tamanna Afrose, Atashi Mani Ghosh, Md Musfique Anwar

^*Corresponding author for this work

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

1 Scopus citations

Abstract

Most existing works on categorization of social media users in online social networks (OSNs) consider only the topical interest of users as the basis for user classification. The temporal evolution of user topical interests has not been thoroughly studied to identify their effects on the classification of social users. In this paper, we investigate the problem of discovering/classifying and tracking time-sensitive activity-driven social user classification in OSNs. The users in a particular class have the tendency to be temporally similar in terms of their temporal degree of topical interests. Our main idea is based on the observation that the degree of users’ topical interests often degrades or upgrades widely over a period of time. The temporal tendency of user activities is modeled as the freshness of recent activities by tracking the social streams with a fading time window.

Original language	English
Title of host publication	Communication and Intelligent Systems - Proceedings of ICCIS 2020
Editors	Harish Sharma, Mukesh Kumar Gupta, G. S. Tomar, Wang Lipo
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	935-944
Number of pages	10
ISBN (Print)	9789811610882
DOIs	https://doi.org/10.1007/978-981-16-1089-9_72
State	Published - 2021
Externally published	Yes
Event	2nd International Conference on Communication and Intelligent Systems, ICCIS 2020 - Virtual, Online Duration: 26 Dec 2020 → 27 Dec 2020

Publication series

Name	Lecture Notes in Networks and Systems
Volume	204
ISSN (Print)	2367-3370
ISSN (Electronic)	2367-3389

Conference

Conference	2nd International Conference on Communication and Intelligent Systems, ICCIS 2020
City	Virtual, Online
Period	26/12/20 → 27/12/20

Bibliographical note

Publisher Copyright:
© 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Keywords

Fading time window
Online social network
Social stream
Temporal activity
Topical interest

ASJC Scopus subject areas

Control and Systems Engineering
Signal Processing
Computer Networks and Communications

Access to Document

10.1007/978-981-16-1089-9_72

Cite this

Hossen, M., Afrose, T., Ghosh, A. M., & Anwar, M. M. (2021). Classification of Social Media Users Based on Temporal Behaviors and Interests. In H. Sharma, M. K. Gupta, G. S. Tomar, & W. Lipo (Eds.), Communication and Intelligent Systems - Proceedings of ICCIS 2020 (pp. 935-944). (Lecture Notes in Networks and Systems; Vol. 204). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-981-16-1089-9_72

Hossen, Murad ; Afrose, Tamanna ; Ghosh, Atashi Mani et al. / Classification of Social Media Users Based on Temporal Behaviors and Interests. Communication and Intelligent Systems - Proceedings of ICCIS 2020. editor / Harish Sharma ; Mukesh Kumar Gupta ; G. S. Tomar ; Wang Lipo. Springer Science and Business Media Deutschland GmbH, 2021. pp. 935-944 (Lecture Notes in Networks and Systems).

@inproceedings{f3aa3722cf9e4b16bd035fea2ea68dfa,

title = "Classification of Social Media Users Based on Temporal Behaviors and Interests",

abstract = "Most existing works on categorization of social media users in online social networks (OSNs) consider only the topical interest of users as the basis for user classification. The temporal evolution of user topical interests has not been thoroughly studied to identify their effects on the classification of social users. In this paper, we investigate the problem of discovering/classifying and tracking time-sensitive activity-driven social user classification in OSNs. The users in a particular class have the tendency to be temporally similar in terms of their temporal degree of topical interests. Our main idea is based on the observation that the degree of users{\textquoteright} topical interests often degrades or upgrades widely over a period of time. The temporal tendency of user activities is modeled as the freshness of recent activities by tracking the social streams with a fading time window.",

keywords = "Fading time window, Online social network, Social stream, Temporal activity, Topical interest",

author = "Murad Hossen and Tamanna Afrose and Ghosh, {Atashi Mani} and Anwar, {Md Musfique}",

note = "Publisher Copyright: {\textcopyright} 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.; 2nd International Conference on Communication and Intelligent Systems, ICCIS 2020 ; Conference date: 26-12-2020 Through 27-12-2020",

year = "2021",

doi = "10.1007/978-981-16-1089-9_72",

language = "English",

isbn = "9789811610882",

series = "Lecture Notes in Networks and Systems",

publisher = "Springer Science and Business Media Deutschland GmbH",

pages = "935--944",

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}

Hossen, M, Afrose, T, Ghosh, AM & Anwar, MM 2021, Classification of Social Media Users Based on Temporal Behaviors and Interests. in H Sharma, MK Gupta, GS Tomar & W Lipo (eds), Communication and Intelligent Systems - Proceedings of ICCIS 2020. Lecture Notes in Networks and Systems, vol. 204, Springer Science and Business Media Deutschland GmbH, pp. 935-944, 2nd International Conference on Communication and Intelligent Systems, ICCIS 2020, Virtual, Online, 26/12/20. https://doi.org/10.1007/978-981-16-1089-9_72

Classification of Social Media Users Based on Temporal Behaviors and Interests. / Hossen, Murad; Afrose, Tamanna; Ghosh, Atashi Mani et al.
Communication and Intelligent Systems - Proceedings of ICCIS 2020. ed. / Harish Sharma; Mukesh Kumar Gupta; G. S. Tomar; Wang Lipo. Springer Science and Business Media Deutschland GmbH, 2021. p. 935-944 (Lecture Notes in Networks and Systems; Vol. 204).

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

TY - GEN

T1 - Classification of Social Media Users Based on Temporal Behaviors and Interests

AU - Hossen, Murad

AU - Afrose, Tamanna

AU - Ghosh, Atashi Mani

AU - Anwar, Md Musfique

PY - 2021

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N2 - Most existing works on categorization of social media users in online social networks (OSNs) consider only the topical interest of users as the basis for user classification. The temporal evolution of user topical interests has not been thoroughly studied to identify their effects on the classification of social users. In this paper, we investigate the problem of discovering/classifying and tracking time-sensitive activity-driven social user classification in OSNs. The users in a particular class have the tendency to be temporally similar in terms of their temporal degree of topical interests. Our main idea is based on the observation that the degree of users’ topical interests often degrades or upgrades widely over a period of time. The temporal tendency of user activities is modeled as the freshness of recent activities by tracking the social streams with a fading time window.

AB - Most existing works on categorization of social media users in online social networks (OSNs) consider only the topical interest of users as the basis for user classification. The temporal evolution of user topical interests has not been thoroughly studied to identify their effects on the classification of social users. In this paper, we investigate the problem of discovering/classifying and tracking time-sensitive activity-driven social user classification in OSNs. The users in a particular class have the tendency to be temporally similar in terms of their temporal degree of topical interests. Our main idea is based on the observation that the degree of users’ topical interests often degrades or upgrades widely over a period of time. The temporal tendency of user activities is modeled as the freshness of recent activities by tracking the social streams with a fading time window.

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Hossen M, Afrose T, Ghosh AM, Anwar MM. Classification of Social Media Users Based on Temporal Behaviors and Interests. In Sharma H, Gupta MK, Tomar GS, Lipo W, editors, Communication and Intelligent Systems - Proceedings of ICCIS 2020. Springer Science and Business Media Deutschland GmbH. 2021. p. 935-944. (Lecture Notes in Networks and Systems). doi: 10.1007/978-981-16-1089-9_72

Classification of Social Media Users Based on Temporal Behaviors and Interests

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this