Modern temporal network theory: a colloquium

Holme, Petter

doi:10.1140/epjb/e2015-60657-4

Cited by 646 publications

(668 citation statements)

References 348 publications

(612 reference statements)

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“…For detailed reviews on the topic we refer the reader to Refs. [41,42,43]. Over the last years an increasing body of literature has been focused on the study of such properties and their relation to effective controlling strategies.…”

Section: Controlling Contagion Processes In Real Temporal Networkmentioning

confidence: 99%

“…While this approximation can be used to study a range of processes such as the spreading of some diseases in contact networks or the propagation of energy in power grids it fails to describe many others phenomena in which the two timescales are comparable [12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40]. In these cases, such as the spreading of ideas, memes, information and some type of diseases the diffusion processes take place in timevarying networks [41,42,43]. Thus their study and modeling needs to consider the interplay between the two simultaneously unfolding dynamics.…”

Section: Introductionmentioning

confidence: 99%

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Control Strategies of Contagion Processes in Time-Varying Networks

Karsai

Perra

2017

Theoretical Biology

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The vast majority of strategies aimed at controlling contagion processes on networks consider a timescale separation between the evolution of the system and the unfolding of the process. However, in the real world, many networks are highly dynamical and evolve, in time, concurrently to the contagion phenomena. Here, we review the most commonly used immunization strategies on networks. In the first part of the chapter, we focus on controlling strategies in the limit of timescale separation. In the second part instead, we introduce results and methods that relax this approximation. In doing so, we summarize the main findings considering both numerical and analytically approaches in real as well as synthetic time-varying networks.

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Section: Controlling Contagion Processes In Real Temporal Networkmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Control Strategies of Contagion Processes in Time-Varying Networks

Karsai

Perra

2017

Theoretical Biology

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“…In González-Bailón et al [26], the authors exemplify this pitfall, as a network of protesters being recruited surely saw significant changes during their study's time period. Given the fast growing literature on temporal networks [31,32], more attention is required in analyzing the dynamics of networked political activities.…”

Section: Network and Centralitymentioning

confidence: 99%

A Biased Review of Biases in Twitter Studies on Political Collective Action

Cihon

Yasseri

2016

Front. Phys.

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In recent years researchers have gravitated to Twitter and other social media platforms as fertile ground for empirical analysis of social phenomena. Social media provides researchers access to trace data of interactions and discourse that once went unrecorded in the offline world. Researchers have sought to use these data to explain social phenomena both particular to social media and applicable to the broader social world. This paper offers a minireview of Twitter-based research on political crowd behavior. This literature offers insight into particular social phenomena on Twitter, but often fails to use standardized methods that permit interpretation beyond individual studies. Moreover, the literature fails to ground methodologies and results in social or political theory, divorcing empirical research from the theory needed to interpret it. Rather, investigations focus primarily on methodological innovations for social media analyses, but these too often fail to sufficiently demonstrate the validity of such methodologies. This minireview considers a small number of selected papers; we analyse their (often lack of) theoretical approaches, review their methodological innovations, and offer suggestions as to the relevance of their results for political scientists and sociologists.

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“…Following the current terminology, we can call these aggregate networks. This may be reasonable in some context [22,12,15,3,29,16,28,7,8] but networks involving interpersonal relations and events -either historical or fictional -are intrinsically dynamic [13,18,14]. Edges may come and go, as well as characters.…”

Section: Introductionmentioning

confidence: 99%

Temporal Network Analysis of Literary Texts

Prado

Dahmen

Bazzan

et al. 2016

Advs. Complex Syst.

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We study temporal networks of characters in literature focusing on Alice's Adventures in Wonderland (1865) by Lewis Carroll and the anonymous La Chanson de Roland (around 1100). The former, one of the most influential pieces of nonsense literature ever written, describes the adventures of Alice in a fantasy world with logic plays interspersed along the narrative. The latter, a song of heroic deeds, depicts the Battle of Roncevaux in 778 A.D. during Charlemagne's campaign on the Iberian Peninsula. We apply methods recently developed by Taylor et al. [26] to find time-averaged eigenvector centralities, Freeman indices and vitalities of characters. We show that temporal networks are more appropriate than static ones for studying stories, as they capture features that the time-independent approaches fail to yield.

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Modern temporal network theory: a colloquium

Cited by 646 publications

References 348 publications

Control Strategies of Contagion Processes in Time-Varying Networks

Control Strategies of Contagion Processes in Time-Varying Networks

A Biased Review of Biases in Twitter Studies on Political Collective Action

Temporal Network Analysis of Literary Texts

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