research-article

Automated Detection of Social Roles in Online Communities using Deep Learning

Authors:

Piyumini Wijenayake,

Daswin de Silva,

Damminda Alahakoon,

Saliya KirigeeganageAuthors Info & Claims

ICSIM '20: Proceedings of the 3rd International Conference on Software Engineering and Information Management

Pages 63 - 68

https://doi.org/10.1145/3378936.3378973

Published: 07 March 2020 Publication History

Editorial Notes

A corrigendum was issued for this paper on April 21, 2020. You can download the corrigendum from the supplemental material section of this citation page.

Abstract

Online communities are an increasingly important aspect in the digital age, for business organizations, diverse industry sectors and overall, in modern society. The social role of each end-user, influencers to followers, and content providers to receivers is a primary consideration when evaluating the purpose and contribution of any online community. Most existing research on the detection of social roles in online communities is based on manual observations and analysis. This paper introduces a technique for automating the detection and extraction of social roles from online communities. Given the large volume of text and value of content, it is no longer viable to manually encode and detect social roles and contributions. The machine learning approach is based on a deep recurrent neural network and a word embedding model. A dataset consisting of over 1.2 million textual posts extracted from an online community on higher education in Australia was used to demonstrate the technique. This technique can be applied to any online community to automatically identify social roles, their influence and interactions.

Supplementary Material

p63-wijenayake-corrigendum (p63-wijenayake-corrigendum.pdf)

Corrigendum to "Automated Detection of Social Roles in Online Communities using Deep Learning" by Wijenayake et al., Proceedings of the 3rd International Conference on Software Engineering and Information Management (ICSIM '20).

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Cited By

Wang RLu TZhang PGu N(2025)Role Identification Based Method for Cyberbullying Analysis in Social Edge ComputingTsinghua Science and Technology10.26599/TST.2024.901006630:4(1659-1684)Online publication date: Aug-2025
https://doi.org/10.26599/TST.2024.9010066
Vatnani VBarlow J(2024)The Effect of Individual Traits on Emerging Roles in Synchronous Computer-Mediated GroupsProceedings of the ACM on Human-Computer Interaction10.1145/36410208:CSCW1(1-22)Online publication date: 26-Apr-2024
https://dl.acm.org/doi/10.1145/3641020
Eryilmaz EThoms BAhmed Z(2024)Theory-Guided Multiclass Text Classification in Online Academic DiscussionsJournal of Computer Information Systems10.1080/08874417.2024.2371435(1-12)Online publication date: 2-Jul-2024
https://doi.org/10.1080/08874417.2024.2371435
Show More Cited By

Index Terms

Automated Detection of Social Roles in Online Communities using Deep Learning
1. Computing methodologies
  1. Artificial intelligence
    1. Natural language processing
      1. Information extraction
  2. Machine learning
    1. Machine learning approaches
      1. Neural networks

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ICSIM '20: Proceedings of the 3rd International Conference on Software Engineering and Information Management

January 2020

258 pages

ISBN:9781450376907

DOI:10.1145/3378936

Copyright © 2020 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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University of Science and Technology of China: University of Science and Technology of China

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New York, NY, United States

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Published: 07 March 2020

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ICSIM '20

ICSIM '20: The 3rd International Conference on Software Engineering and Information Management

January 12 - 15, 2020

NSW, Sydney, Australia

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Cited By

Wang RLu TZhang PGu N(2025)Role Identification Based Method for Cyberbullying Analysis in Social Edge ComputingTsinghua Science and Technology10.26599/TST.2024.901006630:4(1659-1684)Online publication date: Aug-2025
https://doi.org/10.26599/TST.2024.9010066
Vatnani VBarlow J(2024)The Effect of Individual Traits on Emerging Roles in Synchronous Computer-Mediated GroupsProceedings of the ACM on Human-Computer Interaction10.1145/36410208:CSCW1(1-22)Online publication date: 26-Apr-2024
https://dl.acm.org/doi/10.1145/3641020
Eryilmaz EThoms BAhmed Z(2024)Theory-Guided Multiclass Text Classification in Online Academic DiscussionsJournal of Computer Information Systems10.1080/08874417.2024.2371435(1-12)Online publication date: 2-Jul-2024
https://doi.org/10.1080/08874417.2024.2371435
Carstens JFriess D(2024)AI Within Online Discussions: Rational, Civil, Privileged?Minds and Machines10.1007/s11023-024-09658-034:2Online publication date: 4-May-2024
https://doi.org/10.1007/s11023-024-09658-0
Rabchevsky AAshikhmin EYasnitsky L(2023)Synthesis of Datasets for Neural Networks Based on Expert KnowledgeCyber-Physical Systems and Control II10.1007/978-3-031-20875-1_50(535-544)Online publication date: 21-Jan-2023
https://doi.org/10.1007/978-3-031-20875-1_50
Rabchevskiy AYasnitskiy L(2022)Creating and Using Synthetic Data for Neural Network Training, Using the Creation of a Neural Network Classifier of Online Social Network User Roles as an ExampleDigital Science10.1007/978-3-030-93677-8_36(412-421)Online publication date: 17-Jan-2022
https://doi.org/10.1007/978-3-030-93677-8_36
Abbas A(2021)Social network analysis using deep learning: applications and schemesSocial Network Analysis and Mining10.1007/s13278-021-00799-z11:1Online publication date: 25-Oct-2021
https://doi.org/10.1007/s13278-021-00799-z
Rabchevskiy AAshikhmin ERabchevskiy E(2021)Modelling the Structure of Protest Movement Advocacy in Social Media Using Graph and Neural Network AnalysisScience and Global Challenges of the 21st Century - Science and Technology10.1007/978-3-030-89477-1_1(3-15)Online publication date: 14-Oct-2021
https://doi.org/10.1007/978-3-030-89477-1_1

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