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From Interaction to Participation: The Role of the Imagined Audience in Social Media Community Detection and an Application to Political Communication on Twitter

Research output: Conference Article in Proceeding or Book/Report chapterArticle in proceedingsResearchpeer-review

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From Interaction to Participation: The Role of the Imagined Audience in Social Media Community Detection and an Application to Political Communication on Twitter. / Hanteer, Obaida; Rossi, Luca; D'aurelio, Davide Vega; Magnani, Matteo.

2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) . IEEE, 2018.

Research output: Conference Article in Proceeding or Book/Report chapterArticle in proceedingsResearchpeer-review

Harvard

Hanteer, O, Rossi, L, D'aurelio, DV & Magnani, M 2018, From Interaction to Participation: The Role of the Imagined Audience in Social Media Community Detection and an Application to Political Communication on Twitter. in 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) . IEEE, 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) , Bercelona, Spain, 28/08/2018. https://doi.org/10.1109/ASONAM.2018.8508575

APA

Hanteer, O., Rossi, L., D'aurelio, D. V., & Magnani, M. (2018). From Interaction to Participation: The Role of the Imagined Audience in Social Media Community Detection and an Application to Political Communication on Twitter. In 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) IEEE. https://doi.org/10.1109/ASONAM.2018.8508575

Vancouver

Author

Hanteer, Obaida ; Rossi, Luca ; D'aurelio, Davide Vega ; Magnani, Matteo. / From Interaction to Participation: The Role of the Imagined Audience in Social Media Community Detection and an Application to Political Communication on Twitter. 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) . IEEE, 2018.

Bibtex

@inproceedings{8d118d7ce686491f9b0e80e9e9d890f5,
title = "From Interaction to Participation: The Role of the Imagined Audience in Social Media Community Detection and an Application to Political Communication on Twitter",
abstract = "In the context of community detection in online social media, a lot of effort has been put into the definition of sophisticated network clustering algorithms and much less on the equally crucial process of obtaining high-quality input data. User-interaction data explicitly provided by social media platforms has largely been used as the main source of data because of its easy accessibility. However, this data does not capture a fundamental and much more frequent type of participatory behavior where users do not explicitly mention others but direct their messages to an invisible audience following a common hashtag. In the context of multiplex community detection, we show how to construct an additional data layer about user participation not relying on explicit interactions between users, and how this layer can be used to find different types of communities in the context of Twitter political communication.",
author = "Obaida Hanteer and Luca Rossi and D'aurelio, {Davide Vega} and Matteo Magnani",
year = "2018",
doi = "10.1109/ASONAM.2018.8508575",
language = "English",
isbn = "978-1-5386-6052-2",
booktitle = "2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)",
publisher = "IEEE",
address = "United States",

}

RIS

TY - GEN

T1 - From Interaction to Participation: The Role of the Imagined Audience in Social Media Community Detection and an Application to Political Communication on Twitter

AU - Hanteer, Obaida

AU - Rossi, Luca

AU - D'aurelio, Davide Vega

AU - Magnani, Matteo

PY - 2018

Y1 - 2018

N2 - In the context of community detection in online social media, a lot of effort has been put into the definition of sophisticated network clustering algorithms and much less on the equally crucial process of obtaining high-quality input data. User-interaction data explicitly provided by social media platforms has largely been used as the main source of data because of its easy accessibility. However, this data does not capture a fundamental and much more frequent type of participatory behavior where users do not explicitly mention others but direct their messages to an invisible audience following a common hashtag. In the context of multiplex community detection, we show how to construct an additional data layer about user participation not relying on explicit interactions between users, and how this layer can be used to find different types of communities in the context of Twitter political communication.

AB - In the context of community detection in online social media, a lot of effort has been put into the definition of sophisticated network clustering algorithms and much less on the equally crucial process of obtaining high-quality input data. User-interaction data explicitly provided by social media platforms has largely been used as the main source of data because of its easy accessibility. However, this data does not capture a fundamental and much more frequent type of participatory behavior where users do not explicitly mention others but direct their messages to an invisible audience following a common hashtag. In the context of multiplex community detection, we show how to construct an additional data layer about user participation not relying on explicit interactions between users, and how this layer can be used to find different types of communities in the context of Twitter political communication.

U2 - 10.1109/ASONAM.2018.8508575

DO - 10.1109/ASONAM.2018.8508575

M3 - Article in proceedings

SN - 978-1-5386-6052-2

BT - 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)

PB - IEEE

ER -

ID: 83565479