A social communication model based on simplicial complexes

Wang, Dong; Zhao, Yi; Hui, Leng; Small, Michael

doi:10.1016/j.physleta.2020.126895

Cited by 33 publications

(20 citation statements)

References 34 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…While the degree distribution provides a glimpse into the structure of a complex network, models that extend pairwise relationships to multi-node relationships occurring in the system, and that allow for higher-order interactions, have been known for some time now to be important for capturing the richness and higher-order topological structures in real networks (Iacopini et al 2019), (Albert and Barabási 2002), , (Boccaletti et al 2006), (Guilbeault, Becker, and Centola 2018). In particular, in the last several years, simplicial complexes have been widely used to analyze aspects of diverse multilayer systems, including social relation (Wang et al 2020), social contagion (Pastor-Satorras et al 2015), protein interaction (Serrano, Hernández-Serrano, and Gómez 2020), linguistic categorization (Gong et al 2011), and transportation (Lin and Ban 2013). New measurements, such as simplicial degree (Serrano, Hernández-Serrano, and Gómez 2020), simplicial degree based centralities , (Estrada and Ross 2018), and random walks (Schaub et al 2020) have all been proposed to not only measure the relevance of a simplicial community and the quality of higher-order connections, but also the dynamical properties of simplicial networks.…”

Section: Related Workmentioning

confidence: 99%

Can Scale-free Network Growth with Triad Formation Capture Simplicial Complex Distributions in Real Communication Networks?

Kejriwal¹,

Shi²

2022

Preprint

View full text Add to dashboard Cite

In recent years, there has been a growing recognition that higher-order structures are important features in real-world networks. A particular class of structures that has gained prominence is known as a simplicial complex. Despite their application to complex processes such as social contagion and novel measures of centrality, not much is currently understood about the distributional properties of these complexes in communication networks. Furthermore, it is also an open question as to whether an established growth model, such as scale-free network growth with triad formation, is sophisticated enough to capture the distributional properties of simplicial complexes. In this paper, we use empirical data on five real-world communication networks to propose a functional form for the distributions of two important simplicial complex structures. We also show that, while the scale-free network growth model with triad formation captures the form of these distributions in networks evolved using the model, the best-fit parameters are significantly different between the real network and its simulated equivalent. An auxiliary contribution is an empirical profile of the two simplicial complexes in these five real-world networks. 1

show abstract

Section: Related Workmentioning

confidence: 99%

Can Scale-free Network Growth with Triad Formation Capture Simplicial Complex Distributions in Real Communication Networks?

Kejriwal¹,

Shi²

2022

Preprint

View full text Add to dashboard Cite

show abstract

“…This could serve to produce an a priori expected stability of the system. Furthermore, one could study probability-based Markov chains on P [29,33,37,44]. Random walks might represent coalitions merging with other coalitions according to the probability that can be extracted from the agreement probability vectors v ij .…”

Section: Stab(p ) ≤ Stab(cp )mentioning

confidence: 99%

“…Applications in fields as disparate as topological data analysis [8,9,30,32], signal processing [2,3,17,23,28], and neuroscience [17] abound. Social science applications are also starting to emerge; connections to game theory are wellestablished [13,14,25], and recent work uses simplicial complexes to model social communication and opinion dynamics [18,22,44].…”

mentioning

confidence: 99%

Political structures and the topology of simplicial complexes

Mock¹,

Volic²

2021

Preprint

View full text Add to dashboard Cite

We use the topology of simplicial complexes to model political structures following [1]. Simplicial complexes are a natural tool to encode interactions in the structures since a simplex can be used to represent a subset of compatible agents. We translate the wedge, cone, and suspension operations into the language of political structures and show how these constructions correspond to merging structures and introducing mediators. We introduce the notions of the viability of an agent and the stability of a political system and examine their interplay with the simplicial complex topology, casting their interactions in category-theoretic language whenever possible. We introduce a refinement of the model by assigning weights to simplices corresponding to the number of issues the agents agree on. In addition, homology of simplicial complexes is used to detect non-viabilities, certain cycles of incompatible agents, and the (non)presence of mediators. Finally, we extend some results from [1], bringing viability and stability into the language of friendly delegations and using homology to examine the existence of R-compromises and D-compromises. Contents 14 5.2. Stability of political structures 17 5.3. Merging and mediating political structures 18 5.4. Weighted simplicial complex model 20 5.5. Homology and political structures 23 6. Delegations and compromises 25 7. Future directions 28 References 29

show abstract

“…triangles, tetrahedra etc.) have been successfully used to model a variety of systems such a social communication networks [16], complex systems [17,18], disease spreading [19] etc. and are a rapidly growing field of data analysis.…”

Section: Introductionmentioning

confidence: 99%

The collective vs individual nature of mountaineering: a network and simplicial approach

Krishnagopal¹

2022

Preprint

View full text Add to dashboard Cite

Mountaineering is a sport of contrary forces: teamwork plays a large role in mental fortitude and skills, but the actual act of climbing, and indeed survival, is largely individualistic. This work studies the effects of the structure and topology of relationships within climbers on the level of cooperation and success. It does so using simplicial complexes, where relationships between climbers are captured through simplexes that correspond to joint previous expeditions with dimension given by the number of climbers minus one and weight given by the number of occurrences of the simplex. First, this analysis establishes the importance of relationships and shows that chances of failure to summit reduce drastically when climbing with repeat partners. From a climber-centric perspective, it finds that climbers that belong to simplexes with large dimension were more likely to be successful, across all experience levels. Then, the distribution of relationships within a group is explored to identify collective human behavior determining expedition styles: from polarized to cooperative. Expeditions containing simplices with large dimension, and usually low weight, implying that a large number of people participated in a small number of joint expeditions, tended to be more cooperative, benefiting all members of the group, not just those that were part of the simplex. On the other hand, the existence of small, usually strong, subgroups lead to a polarized style where climbers that were not a part of the subgroup were less likely to succeed. Lastly, this work examines the effects of individual features (such as age, gender, experience etc.) and expedition-wide factors (number of camps, total number of days etc.) that may play bigger roles in individualistic and cooperative expeditions respectively. Centrality indicates that individual traits of youth and oxygen use while ascending are strong drivers of success. Of expedition-wide factors, the expedition size and number of expedition days are found to be strongly correlated with success rate.

show abstract

A social communication model based on simplicial complexes

Cited by 33 publications

References 34 publications

Can Scale-free Network Growth with Triad Formation Capture Simplicial Complex Distributions in Real Communication Networks?

Can Scale-free Network Growth with Triad Formation Capture Simplicial Complex Distributions in Real Communication Networks?

Political structures and the topology of simplicial complexes

The collective vs individual nature of mountaineering: a network and simplicial approach

Contact Info

Product

Resources

About