Well, duh.
My name is Mason Porter. I am a Professor in the Department of Mathematics at UCLA. Previously I was Professor of Nonlinear and Complex Systems in the Mathematical Institute at University of Oxford. I was also a Tutorial Fellow of Somerville College.
Thursday, November 30, 2023
Wednesday, November 29, 2023
2023 Relievers of the Year
Félix Bautista of the Baltimore Orioles and Devin Williams of the Milwaukee Brewers are this year's Relievers of the Year in Baseball.
Tuesday, November 28, 2023
2023 Comeback Players of the Year
Reliever Liam Hendricks of the Chicago White Sox and outfielder (and also infielder, when he was with the Dodgers) Cody Bellinger of the Chicago Cubs have been named Baseball's 2023 Comeback Players of the Year.
"A Density Description of a Bounded-Confidence Model of Opinion Dynamics on Hypergraphs"
Another of my papers has now been published in final form. Here are some details.
Title: A Density Description of a Bounded-Confidence Model of Opinion Dynamics on Hypergraphs
Authors: Weiqi Chu and Mason A. Porter
Abstract: Social interactions often occur between three or more agents simultaneously. Examining opinion dynamics on hypergraphs allows one to study the effect of such polyadic interactions on the opinions of agents. In this paper, we consider a bounded-confidence model (BCM), in which opinions take continuous values and interacting agents compromise their opinions if they are close enough to each other. We study a density description of a Deffuant–Weisbuch BCM on hypergraphs. We derive a rate equation for the mean-field opinion density as the number of agents becomes infinite, and we prove that this rate equation yields a probability density that converges to noninteracting opinion clusters. Using numerical simulations, we examine bifurcations of the density-based BCM's steady-state opinion clusters and demonstrate that the agent-based BCM converges to the density description of the BCM as the number of agents becomes infinite.
Title: A Density Description of a Bounded-Confidence Model of Opinion Dynamics on Hypergraphs
Authors: Weiqi Chu and Mason A. Porter
Abstract: Social interactions often occur between three or more agents simultaneously. Examining opinion dynamics on hypergraphs allows one to study the effect of such polyadic interactions on the opinions of agents. In this paper, we consider a bounded-confidence model (BCM), in which opinions take continuous values and interacting agents compromise their opinions if they are close enough to each other. We study a density description of a Deffuant–Weisbuch BCM on hypergraphs. We derive a rate equation for the mean-field opinion density as the number of agents becomes infinite, and we prove that this rate equation yields a probability density that converges to noninteracting opinion clusters. Using numerical simulations, we examine bifurcations of the density-based BCM's steady-state opinion clusters and demonstrate that the agent-based BCM converges to the density description of the BCM as the number of agents becomes infinite.
Friday, November 24, 2023
"Supracentrality Analysis of Temporal Networks with Directed Interlayer Coupling" (Second Edition)
The unnecessary second edition of the book Temporal Network Theory is now out. It includes a second edition of a chapter that I coauthored. Here are a few details.
Title: Supracentrality Analysis of Temporal Networks with Directed Interlayer Coupling
Authors: Dane Taylor, Mason A. Porter, and Peter J. Mucha
Abstract: We describe centralities in temporal networks using a supracentrality framework to study centrality trajectories, which characterize how the importances of nodes change with time. We study supracentrality generalizations of eigenvector-based centralities, a family of centrality measures for time-independent networks that includes PageRank, hub and authority scores, and eigenvector centrality. We start with a sequence of adjacency matrices, each of which represents a time layer of a network at a different point or interval of time. Coupling centrality matrices across time layers with weighted interlayer edges yields a supracentrality matrix C(ω), where ω controls the extent to which centrality trajectories change with time. We can flexibly tune the weight and topology of the interlayer coupling to cater to different scientific applications. The entries of the dominant eigenvector of C(ω) represent joint centralities, which simultaneously quantify the importances of every node in every time layer. Inspired by probability theory, we also compute marginal and conditional centralities. We illustrate how to adjust the coupling between time layers to tune the extent to which nodes’ centrality trajectories are influenced by the oldest and newest time layers. We support our findings by analysis in the limits of small and large ω.
Title: Supracentrality Analysis of Temporal Networks with Directed Interlayer Coupling
Authors: Dane Taylor, Mason A. Porter, and Peter J. Mucha
Abstract: We describe centralities in temporal networks using a supracentrality framework to study centrality trajectories, which characterize how the importances of nodes change with time. We study supracentrality generalizations of eigenvector-based centralities, a family of centrality measures for time-independent networks that includes PageRank, hub and authority scores, and eigenvector centrality. We start with a sequence of adjacency matrices, each of which represents a time layer of a network at a different point or interval of time. Coupling centrality matrices across time layers with weighted interlayer edges yields a supracentrality matrix C(ω), where ω controls the extent to which centrality trajectories change with time. We can flexibly tune the weight and topology of the interlayer coupling to cater to different scientific applications. The entries of the dominant eigenvector of C(ω) represent joint centralities, which simultaneously quantify the importances of every node in every time layer. Inspired by probability theory, we also compute marginal and conditional centralities. We illustrate how to adjust the coupling between time layers to tune the extent to which nodes’ centrality trajectories are influenced by the oldest and newest time layers. We support our findings by analysis in the limits of small and large ω.
Thursday, November 16, 2023
2023 Most Valuable Player Awards
Major League Baseball has announced its 2023 Most Valuable Players. To nobody's surprise, Shohei Ohtani of the Los Angeles Angels was the unanimous MVP in the Americal League. Also to nobody's surprise, Ronald Acuña, Jr. of the Atlanta Braves won the MVP award handily in the National League. Acuña, Jr. also won the MVP unanimously (which I hadn't expected), and this marks the first time that both MVPs were unanimous. Ohtani is the first baseball player ever to twice be name a unanimous MVP.
The National League MVP voting was interesting. Mookie Betts of the Los Angeles Dodgers got all 30 second-place votes, and Freddie Freeman (Dodgers) and Matt Olson (Braves) split all of the third-place and fourth-place voters (with Freeman getting 17 of the former and 13 of the latter to obtain 4 more points than Olson). Rookie of the Year Corbin Carroll of the Arizona Diamondbacks finished fifth in the voting and garnered 20 of the 30 fifth-place votes.
The National League MVP voting was interesting. Mookie Betts of the Los Angeles Dodgers got all 30 second-place votes, and Freddie Freeman (Dodgers) and Matt Olson (Braves) split all of the third-place and fourth-place voters (with Freeman getting 17 of the former and 13 of the latter to obtain 4 more points than Olson). Rookie of the Year Corbin Carroll of the Arizona Diamondbacks finished fifth in the voting and garnered 20 of the 30 fifth-place votes.
Wednesday, November 15, 2023
2023 Cy Young Awards
As with Major League Baseball's awards earlier this week, the 2023 Cy Young Awards were awarded to the expected pitchers. Blake Snell of the San Diego Padres won handily in the National League, and Gerrit Cole of the New York Yankees won unanimously in the American League.
Tuesday, November 14, 2023
2023 Managers of the Year
The Managers of the Year have been announced. Skip Schumaker of the Miami Marlins won in the National League and Brandon Hyde of the Baltimore Orioles won in the American League.
Monday, November 13, 2023
2023 Rookies of the Year
Baseball's 2023 Rookies of the Year are Gunnar Henderson of the Baltimore Orioles and Corbin Carroll of the Arizona Diamondbacks.
Both selections were unanimous, and it was clear that both selections would either be unanimous or very nearly so (and it was clear that Carroll would win unanimously).
Both selections were unanimous, and it was clear that both selections would either be unanimous or very nearly so (and it was clear that Carroll would win unanimously).
Saturday, November 11, 2023
What Happens in San Juan Capistrano Stays in San Juan Capistrano (2023 Edition)
I was just in San Capistrano for a bit more than a day to hang out with friends.
Thursday, November 09, 2023
2023 Silver Slugger Awards
The 2023 Silver Slugger awards were announced today. This includes inaugural team awards for the Braves in the National League and the Rangers in the American League.