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Investigating cascades in social networks: structural and temporal aspects

Investigating cascades in social networks: structural and temporal aspects
Investigating cascades in social networks: structural and temporal aspects
There has been significant interest in studying social interactions in online social networks, such as how people exchange opinions, disseminate information, and adopt certain behaviours. One phenomenon addressed is information diffusion: the way information is spread in social networks. Since their emergence, online social networks have been used by people to create and share content. They provide a set of functionalities that facilitate these and other tasks, allowing users to interact with each other. For researchers, these platforms became the basis for understanding complex human behaviours, one of which is the ‘urge’ to share content with others. Online social networks allow users to create and share various types of content daily. In fact, the bulk of the content displayed on these platforms is not original but shared. Thus, the ability to decipher the phenomenon of information diffusion became essential in diverse fields, such as marketeers who wish to create content that spreads, sociologists who wish to understand the underlying phenomenon, and web scientists who wish to understand the web as a sociotechnical entity.

In its simplest form, the information diffusion process in online social networks consists of the content that spreads, the context that facilitates the spread, and the outcome of the process. The underlying structure on which the content spreads is the network of connections between users (the social network). Therefore, the structure of the diffusion is also a network that links users, and is based on information about who influences whom to spread the content. This network is known as the cascade. In the literature, diffusion and cascades are intersecting concepts, and they are often used interchangeably. However, this work differentiates the two. Diffusion is used to ii refer to the phenomenon while cascade is used to refer to the result of the diffusion, i.e. the structural representation of the diffusion process.

This work investigates information diffusion on Tumblr, an online social network platform that provides reblogging functionality. Reblogging allows users to reblog posts, which creates a cascading behaviour that can be observed. The reblogging history is provided as a list of notes attached to each post and all of its reblogged copies. In practice, these notes have two parts: structural (who reblogged from whom) and temporal (when did the reblogging occur). These two aspects complement each other in providing an understanding of the diffusion process as it manifests in the form of a cascade. Studying such explicit cascades is important as it allows understanding the information diffusion, a phenomenon that occurs in many implicit forms on the Web.

This work’s contributions include proposing an information diffusion framework that conceptualises the elements of the diffusion (namely, the content, context and cascade) and how they relate to each other. It also proposes construction models that create cascade networks minimal contextual information and missing/degraded data. In addition, this work provides a survey of the structural and temporal features of cascades, including their definitions and implications. It also investigates Tumblr as a platform for information diffusion, analyses the structural and temporal aspects of Tumblr’s cascades and compares its features with cascades obtained from other platforms.

The main findings show that Tumblr’s most popular content create ‘large’ cascades that are deep, branching into a large number of separate and long paths, having a consistent number of reblogs at each depth and at each given time. These cascades gain their popularity throughout time in various ways; some of them feature high reblogging activities followed by idleness phases, others fluctuate more slowly accumulating rebloggings. Few cascades regain their popularity after long periods of idleness, while the majority have one outstanding popularity phase that is never repeated.
University of Southampton
Alrajebah, Nora
5953592e-dd0f-498e-b21b-c1013e557dc5
Alrajebah, Nora
5953592e-dd0f-498e-b21b-c1013e557dc5
Carr, Leslie
0572b10e-039d-46c6-bf05-57cce71d3936

Alrajebah, Nora (2018) Investigating cascades in social networks: structural and temporal aspects. University of Southampton, Doctoral Thesis, 207pp.

Record type: Thesis (Doctoral)

Abstract

There has been significant interest in studying social interactions in online social networks, such as how people exchange opinions, disseminate information, and adopt certain behaviours. One phenomenon addressed is information diffusion: the way information is spread in social networks. Since their emergence, online social networks have been used by people to create and share content. They provide a set of functionalities that facilitate these and other tasks, allowing users to interact with each other. For researchers, these platforms became the basis for understanding complex human behaviours, one of which is the ‘urge’ to share content with others. Online social networks allow users to create and share various types of content daily. In fact, the bulk of the content displayed on these platforms is not original but shared. Thus, the ability to decipher the phenomenon of information diffusion became essential in diverse fields, such as marketeers who wish to create content that spreads, sociologists who wish to understand the underlying phenomenon, and web scientists who wish to understand the web as a sociotechnical entity.

In its simplest form, the information diffusion process in online social networks consists of the content that spreads, the context that facilitates the spread, and the outcome of the process. The underlying structure on which the content spreads is the network of connections between users (the social network). Therefore, the structure of the diffusion is also a network that links users, and is based on information about who influences whom to spread the content. This network is known as the cascade. In the literature, diffusion and cascades are intersecting concepts, and they are often used interchangeably. However, this work differentiates the two. Diffusion is used to ii refer to the phenomenon while cascade is used to refer to the result of the diffusion, i.e. the structural representation of the diffusion process.

This work investigates information diffusion on Tumblr, an online social network platform that provides reblogging functionality. Reblogging allows users to reblog posts, which creates a cascading behaviour that can be observed. The reblogging history is provided as a list of notes attached to each post and all of its reblogged copies. In practice, these notes have two parts: structural (who reblogged from whom) and temporal (when did the reblogging occur). These two aspects complement each other in providing an understanding of the diffusion process as it manifests in the form of a cascade. Studying such explicit cascades is important as it allows understanding the information diffusion, a phenomenon that occurs in many implicit forms on the Web.

This work’s contributions include proposing an information diffusion framework that conceptualises the elements of the diffusion (namely, the content, context and cascade) and how they relate to each other. It also proposes construction models that create cascade networks minimal contextual information and missing/degraded data. In addition, this work provides a survey of the structural and temporal features of cascades, including their definitions and implications. It also investigates Tumblr as a platform for information diffusion, analyses the structural and temporal aspects of Tumblr’s cascades and compares its features with cascades obtained from other platforms.

The main findings show that Tumblr’s most popular content create ‘large’ cascades that are deep, branching into a large number of separate and long paths, having a consistent number of reblogs at each depth and at each given time. These cascades gain their popularity throughout time in various ways; some of them feature high reblogging activities followed by idleness phases, others fluctuate more slowly accumulating rebloggings. Few cascades regain their popularity after long periods of idleness, while the majority have one outstanding popularity phase that is never repeated.

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Final Thesis - Version of Record
Restricted to Repository staff only until 8 May 2022.
Available under License University of Southampton Thesis Licence.

More information

Published date: May 2018

Identifiers

Local EPrints ID: 420625
URI: https://eprints.soton.ac.uk/id/eprint/420625
PURE UUID: 8e4ebd14-1f9d-4d67-84a9-19a2f0353707
ORCID for Leslie Carr: ORCID iD orcid.org/0000-0002-2113-9680

Catalogue record

Date deposited: 11 May 2018 16:30
Last modified: 11 May 2019 00:37

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Contributors

Author: Nora Alrajebah
Thesis advisor: Leslie Carr ORCID iD

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