An Innovative Way to Model Twitter Topic-Driven Interactions Using Multiplex Networks

Obaida Hanteer; Luca Rossi

doi:10.3389/fdata.2019.00009

An Innovative Way to Model Twitter Topic-Driven Interactions Using Multiplex Networks

Obaida Hanteer, Luca Rossi

Research output: Conference Article in Proceeding or Book/Report chapter › Article in proceedings › Research › peer-review

Abstract

We propose a way to model topic-based implicit interactions among Twitter users. Our model relies on grouping Twitter hashtags, in a given context, into themes/topics and then using the multiplex network model to construct a thematic multiplex where each layer corresponds to a topic/theme, and users within a layer are connected if and only if they used the same hashtag. We show, by testing our model on a real-world Twitter dataset, that applying multiplex community detection on the thematic multiplex can reveal new types of communities that were not observed before using the traditional ways of modeling Twitter interactions

Original language	English
Title of host publication	Frontiers in Big Data. Workshop Proceedings of the 13th International AAAI Conference on Web and Social Media
Publisher	Frontiers
Publication date	6 Jun 2019
DOIs	https://doi.org/10.3389/fdata.2019.00009
Publication status	Published - 6 Jun 2019

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title = "An Innovative Way to Model Twitter Topic-Driven Interactions Using Multiplex Networks",

abstract = "We propose a way to model topic-based implicit interactions among Twitter users. Our model relies on grouping Twitter hashtags, in a given context, into themes/topics and then using the multiplex network model to construct a thematic multiplex where each layer corresponds to a topic/theme, and users within a layer are connected if and only if they used the same hashtag. We show, by testing our model on a real-world Twitter dataset, that applying multiplex community detection on the thematic multiplex can reveal new types of communities that were not observed before using the traditional ways of modeling Twitter interactions",

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An Innovative Way to Model Twitter Topic-Driven Interactions Using Multiplex Networks. / Hanteer, Obaida; Rossi, Luca.

Frontiers in Big Data. Workshop Proceedings of the 13th International AAAI Conference on Web and Social Media. Frontiers, 2019.

Research output: Conference Article in Proceeding or Book/Report chapter › Article in proceedings › Research › peer-review

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AB - We propose a way to model topic-based implicit interactions among Twitter users. Our model relies on grouping Twitter hashtags, in a given context, into themes/topics and then using the multiplex network model to construct a thematic multiplex where each layer corresponds to a topic/theme, and users within a layer are connected if and only if they used the same hashtag. We show, by testing our model on a real-world Twitter dataset, that applying multiplex community detection on the thematic multiplex can reveal new types of communities that were not observed before using the traditional ways of modeling Twitter interactions

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An Innovative Way to Model Twitter Topic-Driven Interactions Using Multiplex Networks

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