arXiv subjects

T. S. Evans

Publications and source records attributed to T. S. Evans.

At least 19 recordsLinked to original sources

arXiv2026

Let There Be Claws: An Early Social Network Analysis of AI Agents on Moltbook

Within twelve days of launch, an AI-native social platform exhibits extreme attention concentration, hierarchical role separation, and one-way attention flow, consistent with the hypothesis that stratification in agent ecosystems can emerge rapidly rather than gradually. We analyse publicly observable traces from a 12-day window of Moltbook (28 January -- 8 February 2026), comprising 20,040 posts and 192,410 comments from 15,083 accounts across 759 submolts. We construct co-participation and directed-comment graphs and report reciprocity, community structure, and centrality, alongside descriptive content themes. Under a commenter--post-author tie definition, interaction is strongly asymmetric (reciprocity ~1%), and HITS centrality separates cleanly into hub and authority roles, consistent with broadcast-style attention rather than mutual exchange. Engagement is highly unequal: attention is far more concentrated than production (upvote Gini = 0.992 vs. posting Gini = 0.601), and early-arriving accounts accumulate substantially higher cumulative upvotes prior to exposure-time correction, suggesting rich-get-richer dynamics. Participation is brief and bursty (median observed lifespan 2.48 minutes; 54.8% of posts occur within six peak UTC hours). Embedding-based topic modelling identifies diverse thematic clusters, including technical discussion of memory and identity, onboarding messages, and formulaic token-minting content. These results provide an early structural baseline for large-scale agent--agent social interaction and suggest that familiar forms of hierarchy, amplification, and role differentiation can arise on compressed timescales in agent-facing platforms.

physics.soc-ph↗

arXiv2025

Understanding Main Path Analysis

Main path analysis has long been used to trace knowledge trajectories in citation networks, yet it lacks solid theoretical foundations. To understand when and why this approach succeeds, we analyse directed acyclic graphs created from two types of artificial models and by looking at over twenty networks derived from real data. We show that entropy-based variants of main path analysis optimise geometric distance measures, providing its first information-theoretic and geometric basis. Numerical results demonstrate that existing algorithms converge on near-geodesic solutions. We also show that an approach based on longest paths produces similar results, is equally well motivated yet is much simpler to implement. However, the traditional single-path focus is unnecessarily restrictive, as many near-optimal paths highlight different key nodes. We introduce an approach using ``baskets'' of nodes where we select a fraction of nodes with the smallest values of a measure we call ``generalised criticality''. Analysis of large vaccine citation networks shows that these baskets achieve comprehensive algorithmic coverage, offering a robust, simple, and computationally efficient way to identify core knowledge structures. In practice, we find that those nodes with zero unit criticality capture the information in main paths in almost all cases and capture a wider range of key nodes without unnecessarily increasing the number of nodes considered. We find no advantage in using the traditional main path methods.

physics.soc-ph↗

arXiv2025

Interdisciplinarity Revealed by Transitive Reduction of Citation Networks

We investigate the impact of transitive reduction on citation networks. Our hypothesis is that documents which lose fewer citations under transitive reduction are likely to be interdisciplinary, while a large loss of citations suggests a document is primarily cited within a single discipline. We test this hypothesis by using an artificial model of a citation network and by using data on citations from three sources: academic papers, court decisions and patents. Where needed, we applied modularity-based clustering techniques on a network defined using bibliographic coupling to classify documents by topic. A cluster-dependent measure was then used to classify the nodes as interdisciplinary or intradisciplinary. Our results provide strong support for our hypothesis in three of the four cases, with somewhat weaker but still positive support in the case of patents.

physics.soc-ph↗

arXiv2020

Predictive limitations of spatial interaction models: a non-Gaussian analysis

We present a method to compare spatial interaction models against data based on well known statistical measures that are appropriate for such models and data. We illustrate our approach using a widely used example: commuting data, specifically from the US Census 2000. We find that the radiation model performs significantly worse than an appropriately chosen simple gravity model. Various conclusions are made regarding the development and use of spatial interaction models, including: that spatial interaction models fit badly to data in an absolute sense, that therefore the risk of over-fitting is small and adding additional fitted parameters improves the predictive power of models, and that appropriate choices of input data can improve model fit.

physics.soc-ph↗

arXiv2014

Sculplexity: Sculptures of Complexity using 3D printing

We show how to convert models of complex systems such as 2D cellular automata into a 3D printed object. Our method takes into account the limitations inherent to 3D printing processes and materials. Our approach automates the greater part of this task, bypassing the use of CAD software and the need for manual design. As a proof of concept, a physical object representing a modified forest fire model was successfully printed. Automated conversion methods similar to the ones developed here can be used to create objects for research, for demonstration and teaching, for outreach, or simply for aesthetic pleasure. As our outputs can be touched, they may be particularly useful for those with visual disabilities.

physics.ed-ph↗

arXiv2014

Modelling Citation Networks

The distribution of the number of academic publications as a function of citation count for a given year is remarkably similar from year to year. We measure this similarity as a width of the distribution and find it to be approximately constant from year to year. We show that simple citation models fail to capture this behaviour. We then provide a simple three parameter citation network model using a mixture of local and global search processes which can reproduce the correct distribution over time. We use the citation network of papers from the hep-th section of arXiv to test our model. For this data, around 20% of citations use global information to reference recently published papers, while the remaining 80% are found using local searches. We note that this is consistent with other studies though our motivation is very different from previous work. Finally, we also find that the fluctuations in the size of an academic publication's bibliography is important for the model. This is not addressed in most models and needs further work.

physics.soc-ph↗

arXiv2012

Universality of Performance Indicators based on Citation and Reference Counts

We find evidence for the universality of two relative bibliometric indicators of the quality of individual scientific publications taken from different data sets. One of these is a new index that considers both citation and reference counts. We demonstrate this universality for relatively well cited publications from a single institute, grouped by year of publication and by faculty or by department. We show similar behaviour in publications submitted to the arXiv e-print archive, grouped by year of submission and by sub-archive. We also find that for reasonably well cited papers this distribution is well fitted by a lognormal with a variance of around 1.3 which is consistent with the results of Radicchi, Fortunato, and Castellano (2008). Our work demonstrates that comparisons can be made between publications from different disciplines and publication dates, regardless of their citation count and without expensive access to the whole world-wide citation graph. Further, it shows that averages of the logarithm of such relative bibliometric indices deal with the issue of long tails and avoid the need for statistics based on lengthy ranking procedures.

physics.soc-ph↗

arXiv2011

The Emergence of Leadership in Social Networks

We study a networked version of the minority game in which agents can choose to follow the choices made by a neighbouring agent in a social network. We show that for a wide variety of networks a leadership structure always emerges, with most agents following the choice made by a few agents. We find a suitable parameterisation which highlights the universal aspects of the behaviour and which also indicates where results depend on the type of social network.

physics.soc-ph↗

arXiv2011

What is being calculated with Thermal Field Theory?

Thermal field theory is reviewed briefly. It is noted that, until recently, it was not known what type of real-time Green function is being calculated in the Euclidean approach. The formal answer to this question is then given and the unexpectedly complicated answer is discussed. The physical implications of the results are then considered. (Talk given at the Lake Louise Winter Institute on Particle Physics and Cosmology, 20th - 26th February, 1994, Lake Louise, Canada)

hep-ph↗

arXiv2011

Turnover Rate of Popularity Charts in Neutral Models

It has been shown recently that in many different cultural phenomena the turnover rate on the most popular artefacts in a population exhibit some regularities. A very simple expression for this turnover rate has been proposed by Bentley et al. and its validity in two simple models for copying and innovation is investigated in this paper. It is found that Bentley's formula is an approximation of the real behaviour of the turnover rate in the Wright-Fisher model, while it is not valid in the Moran model.

physics.soc-ph↗

arXiv2011

Communities and Patterns of Scientific collaboration

This paper investigates the role of homophily and focus constraint in shaping collaborative scientific research. First, homophily structures collaboration when scientists adhere to a norm of exclusivity in selecting similar partners at a higher rate than dissimilar ones. Two dimensions on which similarity between scientists can be assessed are their research specialties and status positions. Second, focus constraint shapes collaboration when connections among scientists depend on opportunities for social contact. Constraint comes in two forms, depending on whether it originates in institutional or geographic space. Institutional constraint refers to the tendency of scientists to select collaborators within rather than across institutional boundaries. Geographic constraint is the principle that, when collaborations span different institutions, they are more likely to involve scientists that are geographically co-located than dispersed. To study homophily and focus constraint, the paper will argue in favour of an idea of collaboration that moves beyond formal co-authorship to include also other forms of informal intellectual exchange that do not translate into the publication of joint work. A community-detection algorithm is applied to the co-authorship network of the scientists that submitted in Business and Management in the 2001 UK RAE. While results only partially support research-based homophily, they indicate that scientists use status positions for discriminating between potential partners by selecting collaborators from institutions with a rating similar to their own. Strong support is provided in favour of institutional and geographic constraints. Scientists tend to forge intra-institutional collaborations; yet, when they seek collaborators outside their own institutions, they tend to select those who are in geographic proximity.

physics.soc-ph↗

arXiv2011

Interactions In Space For Archaeological Models

In this article we examine a variety of quantitative models for describing archaeological networks, with particular emphasis on the maritime networks of the Aegean Middle Bronze Age. In particular, we discriminate between those gravitational networks that are most likely (maximum entropy) and most efficient (best cost/benefit outcomes).

physics.soc-ph↗

arXiv2010

Flow graphs: interweaving dynamics and structure

The behavior of complex systems is determined not only by the topological organization of their interconnections but also by the dynamical processes taking place among their constituents. A faithful modeling of the dynamics is essential because different dynamical processes may be affected very differently by network topology. A full characterization of such systems thus requires a formalization that encompasses both aspects simultaneously, rather than relying only on the topological adjacency matrix. To achieve this, we introduce the concept of flow graphs, namely weighted networks where dynamical flows are embedded into the link weights. Flow graphs provide an integrated representation of the structure and dynamics of the system, which can then be analyzed with standard tools from network theory. Conversely, a structural network feature of our choice can also be used as the basis for the construction of a flow graph that will then encompass a dynamics biased by such a feature. We illustrate the ideas by focusing on the mathematical properties of generic linear processes on complex networks that can be represented as biased random walks and also explore their dual consensus dynamics.

physics.soc-ph↗

arXiv2010

Clique Graphs and Overlapping Communities

It is shown how to construct a clique graph in which properties of cliques of a fixed order in a given graph are represented by vertices in a weighted graph. Various definitions and motivations for these weights are given. The detection of communities or clusters is used to illustrate how a clique graph may be exploited. In particular a benchmark network is shown where clique graphs find the overlapping communities accurately while vertex partition methods fail.

physics.soc-ph↗

arXiv2010

Line Graphs of Weighted Networks for Overlapping Communities

In this paper, we develop the idea to partition the edges of a weighted graph in order to uncover overlapping communities of its nodes. Our approach is based on the construction of different types of weighted line graphs, i.e. graphs whose nodes are the links of the original graph, that encapsulate differently the relations between the edges. Weighted line graphs are argued to provide an alternative, valuable representation of the system's topology, and are shown to have important applications in community detection, as the usual node partition of a line graph naturally leads to an edge partition of the original graph. This identification allows us to use traditional partitioning methods in order to address the long-standing problem of the detection of overlapping communities. We apply it to the analysis of different social and geographical networks.

physics.data-an↗

arXiv2009

Line Graphs, Link Partitions and Overlapping Communities

In this paper, we use a partition of the links of a network in order to uncover its community structure. This approach allows for communities to overlap at nodes, so that nodes may be in more than one community. We do this by making a node partition of the line graph of the original network. In this way we show that any algorithm which produces a partition of nodes can be used to produce a partition of links. We discuss the role of the degree heterogeneity and propose a weighted version of the line graph in order to account for this.

physics.soc-ph↗

arXiv2008

Are Copying and Innovation Enough?

Exact analytic solutions and various numerical results for the rewiring of bipartite networks are discussed. An interpretation in terms of copying and innovation processes make this relevant in a wide variety of physical contexts. These include Urn models and Voter models, and our results are also relevant to some studies of Cultural Transmission, the Minority Game and some models of ecology.

physics.soc-ph↗

arXiv2007

Randomness and Complexity in Networks

I start by reviewing some basic properties of random graphs. I then consider the role of random walks in complex networks and show how they may be used to explain why so many long tailed distributions are found in real data sets. The key idea is that in many cases the process involves copying of properties of near neighbours in the network and this is a type of short random walk which in turn produce a natural preferential attachment mechanism. Applying this to networks of fixed size I show that copying and innovation are processes with special mathematical properties which include the ability to solve a simple model exactly for any parameter values and at any time. I finish by looking at variations of this basic model.

cond-mat.stat-mech↗