## Wednesday, May 18, 2022

### What Happens in Davis Stays in Davis.

I am off to a short workshop at UC Davis.

However, I just almost accidentally boarded a flight to Hawaii.

I am flying to Sacramento for the workshop at UC Davis.

[I also just noticed: One of the PhD students in my class is actually here and probably on the same flight.]

## Saturday, May 14, 2022

### A Great Visual Illusion: Radiating the Same Luminance

This is a great visual illusion.

The top and bottom chess pieces radiate the same luminance. (I did some sampling to check, and it seems to check out.)

(Tip of the cap to Luiz Pessoa.)

## Wednesday, May 04, 2022

### 2022 Rock & Roll Hall of Fame Inductees

The Rock & Roll Hall of Fame has announced its 2022 inductees! They include Duran Duran, Eurythmics, Pat Benatar, and Harry Belafonte.

## Sunday, May 01, 2022

### "Topological Data Analysis of Spatial Systems"

A book chapter of ours was just published in final form. It is Chapter 16 in this book. Here are some other details about it.

Title: Topological Data Analysis of Spatial Systems

Authors: Michelle Feng, Abigail Hickok, and Mason A. Porter

Abstract: In this chapter, we discuss applications of topological data analysis (TDA) to spatial systems. We briefly review a recently proposed level-set construction of filtered simplicial complexes, and we then examine persistent homology in two cases studies: street networks in Shanghai and anomalies in the spread of COVID-19 infections. We then summarize our results and provide an outlook on TDA in spatial systems.

## Friday, April 22, 2022

### "Role Detection in Bicycle-Sharing Networks Using Multilayer Stochastic Block Models"

A new paper of mine was published in final form today. The project started in January 2017 as a group project by students in the first course that I ever taught at UCLA. It's taken awhile, but we're finally done!

Title: Role Detection in Bicycle-Sharing Networks Using Multilayer Stochastic Block Models

Authors: Jane Carlen†, Jaume de Dios Pont, CassidyMentus, Shyr-Shea Chang, Stephanie Wang, and Mason A. Porter

Abstract: In urban systems, there is an interdependency between neighborhood roles and transportation patterns between neighborhoods. In this paper, we classify docking stations in bicycle-sharing networks to gain insight into the human mobility patterns of three major cities in the United States. We propose novel time-dependent stochastic block models, with degree-heterogeneous blocks and either mixed or discrete block membership, which classify nodes based on their time-dependent activity patterns. We apply these models to (1) detect the roles of bicycle-sharing stations and (2) describe the traffic within and between blocks of stations over the course of a day. Ourmodels successfully uncover work blocks, home blocks, and other blocks; they also reveal activity patterns that are specific to each city. Our work gives insights for the design and maintenance of bicycle-sharing systems, and it contributes new methodology for community detection in temporal and multilayer networks with heterogeneous degrees.

## Tuesday, April 12, 2022

### A Gallery of Ancience d20 Dice

Here is a gallery of ancient d20 dice. I love it! (It includes the one that I discussed in this post. Also see this post and this post. The second of these also showed up in a previous post.

Also, this reminds me: I need more dice.

(Tip of the cap to Chris Klausmeier.)

## Saturday, March 26, 2022

### Hence is the Relief Pitcher

Tink Hence, a relief pitcher, is a prospect in the Cardinal's farm system.

I hope that he makes the Majors, so that we can bring back more of these jokes. My favorite one was when Chin Lung Hu came up with the Dodgers; I always wanted him to reach first base.

And Hence's first name is also great. "Tink Hence" is such a great baseball name. Because.

## Wednesday, March 16, 2022

### Dodgers Sign Freddie Freeman!

The Dodgers have reached a deal with free agent Freddie Freeman. As usual with the Dodgers, it'a Moneyball with money.

## Wednesday, March 02, 2022

### "In-Degree Centrality in a Social Network is Linked to Coordinated Neural Activity"

Another paper of mine was just published in final form. Here are some details.

Title: In-Degree Centrality in a Social Network is Linked to Coordinated Neural Activity

Authors: Elisa C. Baek, Ryan Hyon, Karina López, Emily S. Finn, Mason A. Porter, and Carolyn Parkinson

Abstract: Convergent processing of the world may be a factor that contributes to social connectedness. We use neuroimaging and network analysis to investigate the association between the social-network position (as measured by in-degree centrality) of first-year university students and their neural similarity while watching naturalistic audio-visual stimuli (specifically, videos). There were 119 students in the social-network study; 63 of them participated in the neuroimaging study. We show that more central individuals had similar neural responses to their peers and to each other in brain regions that are associated with high-level interpretations and social cognition (e.g., in the default mode network), whereas less-central individuals exhibited more variable responses. Self-reported enjoyment of and interest in stimuli followed a similar pattern, but accounting for these data did not change our main results. These findings show that neural processing of external stimuli is similar in highly-central individuals but is idiosyncratic in less-central individuals.

## Friday, February 25, 2022

### XKCD FTW: Greek Letters

Today's xkcd is fantastic! This is a big win. The mouseover is also great (and I am guilty as charged).

Wait until Randall Munroe finds out about mathfrak…

## Thursday, February 17, 2022

### What Happens in Austin Stays in Austin

I am in Austin for the wedding of an old college friend. Some of our mutual friends from college are also coming. Yay!

## Tuesday, January 25, 2022

### David Ortiz Elected to Baseball's Hall of Fame!

The Baseball Hall of Fame results were announced today, and David Ortiz is the only person who was elected by the writers this year. As usual, you can see all of the ballots that have been made public so far at this website. You can also see a discussion of winners and losers from this year's results.

Two of the era committees elected several Hall of Famers last month.

This year, Roger Clemens, Barry Bonds, Curt Schilling, and Sammy Sosa were all in their 10th and final years of eligibility. Clems and Bonds crept up to 65% of the vote, but that's still below the 75% that is needed for induction. Schilling, given his repeated crap, lost many votes. With Clemens, Bonds, Schilling, and Ortiz no longer on the ballot next year and few newcomers of note joining the ballot, holdover Scott Rolen (who went up to around 63% of the vote this year) will likely be elected in 2023 (yay!). Newcomer Carlos Beltrán is the only new person on the ballot next year with any chance. The weak ballot will help him, but we'll see how the Astros cheating scandal affects his vote total. Todd Helton and Billy Wagner finally surpassed 50% of the vote this year, and I expect Todd Helton to make another big jump next year. Both merit election, but it it may take some time for Wagner and I think that Helton is more likely to be elected in 2024 than in 2023. Andruw Jones surpassed 40%, so he's also trending upward. Support for Omar Vizquel tanked because of his shenanigans, and he doesn't belong in the Hall of Fame anyway. Jimmy Rollins and Alex Rodriguez were the only other newcomers to the ballot besides David Ortiz to get at least 5% of the vote.

We will see how the era committees deal with Bonds, Clemens, and Schilling. They'll get into the Hall eventually (as they should, even with their horseshit), but it may take a while.

Update (1/26/22): Also see the voting round-up from Jay Jaffe.

Update (1/27/22): Here is Jay Jaffe's candidate-by-candidate breakdown of the 2022 voting.

Update (1/31/22): Here is Jay Jaffe's five-year outlook of the Hall of Fame balloting in the writers' ballot.

## Monday, January 17, 2022

### "A Multilayer Network Model of the Coevolution of the Spread of a Disease and Competing Opinions"

A new paper of mine just came out in final form. Here are some details.

Title: A Multilayer Network Model of the Coevolution of the Spread of a Disease and Competing Opinions

Authors: Kaiyan Peng, Zheng Lu, Vanessa Lin, Michael R. Lindstrom, Christian Parkinson, Chuntian Wang, Andrea L. Bertozzi, Mason A. Porter

Abstract: During the COVID-19 pandemic, conflicting opinions on physical distancing swept across social media, affecting both human behavior and the spread of COVID-19. Inspired by such phenomena, we construct a two-layer multiplex network for the coupled spread of a disease and conflicting opinions. We model each process as a contagion. On one layer, we consider the concurrent evolution of two opinions — pro-physical-distancing and anti-physical-distancing — that compete with each other and have mutual immunity to each other. The disease evolves on the other layer, and individuals are less likely (respectively, more likely) to become infected when they adopt the pro-physical-distancing (respectively, anti-physical-distancing) opinion. We develop approximations of mean-field type by generalizing monolayer pair approximations to multilayer networks; these approximations agree well with Monte Carlo simulations for a broad range of parameters and several network structures. Through numerical simulations, we illustrate the influence of opinion dynamics on the spread of the disease from complex interactions both between the two conflicting opinions and between the opinions and the disease. We find that lengthening the duration that individuals hold an opinion may help suppress disease transmission, and we demonstrate that increasing the cross-layer correlations or intra-layer correlations of node degrees may lead to fewer individuals becoming infected with the disease.

## Sunday, January 16, 2022

### The PrickRank' Algorithm

One way to gather information is to purposely write an incorrect 'factual' statement on social media.

People love to correct others (often obnoxiously, but at least one acquires info).

Google has PageRank, and social-media platforms like Twitter have this PrickRank algorithm'.

(This monicker is destined to become a classic, just like FIPO.)

## Sunday, January 09, 2022

### The Donkey Kong Visual Illusion

This visual illusion ought to be called the "Donkey Kong Illusion"

## Thursday, January 06, 2022

### "A Bounded-Confidence Model of Opinion Dynamics on Hypergraphs"

A new paper of mine just came out in final form. Here are some details about it.

Title: A Bounded-Confidence Model of Opinion Dynamics on Hypergraphs

Authors: Abigail Hickok, Yacoub Kureh, Heather Z. Brooks, Michelle Feng, and Mason A. Porter

Abstract: People's opinions evolve with time as they interact with their friends, family, colleagues, and others. In the study of opinion dynamics on networks, one often encodes interactions between people in the form of dyadic relationships, but many social interactions in real life are polyadic (i.e., they involve three or more people). In this paper, we extend an asynchronous bounded-confidence model (BCM) on graphs, in which nodes are connected pairwise by edges, to an asynchronous BCM on hypergraphs, in which arbitrarily many nodes can be connected by a single hyperedge. We show that our hypergraph BCM converges to consensus for a wide range of initial conditions for the opinions of the nodes, including for nonuniform and asymmetric initial opinion distributions. We also show that, under suitable conditions, echo chambers can form on hypergraphs with community structure. We demonstrate that the opinions of nodes can sometimes jump from one opinion cluster to another in a single time step; this phenomenon (which we call opinion jumping") is not possible in standard dyadic BCMs. Additionally, we observe a phase transition in the convergence time of our BCM on a complete hypergraph when the variance $\sigma^2$ of the initial opinion distribution equals the confidence bound $c$. We prove that the convergence time grows at least exponentially fast with the number of nodes when $\sigma^2 > c$ and the initial opinions are normally distributed. Therefore, to determine the convergence properties of our hypergraph BCM when the variance and the number of hyperedges are both large, it is necessary to use analytical methods instead of relying only on Monte Carlo simulations.