Comparing the One Piece Network to Other Anime (and Brain) Networks

Looking for a rewarding job? Check out the free resources at https://www.80000Hours.org/notdavid If you'd like to support these videos: https://www.patreon.com/NotDavid BlueSky: https://bsky.app/profile/notdavidyt.bsky.social Insta: https://www.instagram.com/not.david.yt/ second channel: https://www.youtube.com/@notdavidsecondary9958 Which anime has the most power of friendship? Today I out myself as a weeb and look at One Piece, Naruto, Jojo’s Bizzare Adventure, Dragon Ball, and Bleach to find out how we can go about figuring it out. Notes and music list below. Special Thanks: -Brady Johnston (@BradyJohnston) is a very active member of the science blender scene and helped me immensely in figuring out how to make the networks amongst other things. Check out his channel for your science blender needs and inspiration. -Dr. J. Orlandi for the calcium recordings of the neurons. - K. Weatherhead for being a loser (but also helping me with thumbnails and titles) -Brainder for the blender brain model. - All my patreons whose contributions guilt-trip me into getting these videos finished. Chapters: 0:00 Outing myself as a weeb 1:05 Making the networks 3:56 Best friends forever 6:49 Communities 10:37 It’s a small world 14:57 The result 15:47 The twist 22:28 80000 hours Character rasters and network files: https://github.com/notDavidsGit/animesocialnetworks.git Notes: 1. The triangular structure is annoying because characters will have stronger friendship scores just by virtue of being in more episodes over all. Typically this will be the main character, which is not very interesting or informative. To try to account for this I do the following; For example, if Naruto and Sasuke are in N1 and N2 episodes individually, and they share N episodes together, then their friendship score is N/max(N1,N2). This ensures that all friendship scores are between 0 and 1. There are some drawbacks though — if two characters appear together in one episode and never appear again, they will have a perfect friendship score. However, I think this is an easy problem to fix by stipulating that characters must appear X amount of times to be counted. I didn’t do this but one could. I think there are better ways of doing this though, I’m still not happy with it. Feel free to suggest ideas in the comments! 2. Are brain networks small world? There is a lot of research in this. There has been experimental evidence but also mathematical reasoning. If you google ‘are brains small world networks” you will get a lot of resources on this so I will not recommend one here. However, it is not definitive. First, there has been reasearch that similarity measures like the ones we used here actually bias towards small world networks (see [1] below). In fact, I would not be surprised if that is why we observe small worldness in our anime networks (and due to the shape of the raster). Second, a small point that I haven’t seen addressed is that the reasons many people give for why small world networks are desirable make arguments pertaining to the STRUCTURAL network (i.e., the network from physical neuron connections). But remember, we are dealing with functional networks and these are derived from neuron activity. These arguments don’t necessarily hold. See [2] for some more criticisms of small worldness. 3. For the brain analysis I used midnight scan club [3] and the gordon 333 parcellation [4]. REFERENCES [1]:Hlinka, Jaroslav, et al. "Small-world bias of correlation networks: From brain to climate." Chaos: An Interdisciplinary Journal of Nonlinear Science 27.3 (2017). [2]: Papo, David, et al. "Beware of the small-world neuroscientist!." Frontiers in human neuroscience 10 (2016): 96. [3] Gordon, Evan M., et al. "Precision functional mapping of individual human brains." Neuron 95.4 (2017): 791-807. [4] Gordon, Evan M., et al. "Generation and evaluation of a cortical area parcellation from resting-state correlations." Cerebral cortex 26.1 (2016): 288-303. Music (in order): Not David Spotify playlist featuring artists below and others: https://open.spotify.com/playlist/7MCQxBsGqpEaqpT00VbR1p?si=db1c67c5df534340 Killer Vacation - Chris Doerksen https://open.spotify.com/artist/1xnlfswltcMH162Vk7OPhu?si=S2Ge0NhoQE-CbKkDrSZs-A Forward - Seimuc https://open.spotify.com/artist/1kQxwXIPOIZKYCZbwIw4Pz?si=e97873f647cb46a6 Above All - HOME https://open.spotify.com/artist/2exebQUDoIoT0dXA8BcN1P?si=yRgmFmP3Q2y54F23fZxZ_g Through the Crystal - Jeremy Blake (YouTube audio library) Wehrmut - Godmode (YouTube audio library) Intermission - Stux.io and Vaporwavez https://open.spotify.com/artist/5OmqY8dwR6GFMocNY3ph68?si=K_YUNRTXTXakYE6O3VKbig Loading Screen - Dyalla (YouTube audio library) Sure Thing - Chris Doerksen (see link above) Event Horizon - World Complete https://open.spotify.com/artist/7kmiMqEnJID3dyEfU3vdWq?si=IewLjOrPQ2eE_b8HZLcTQg https://worldcomplete.bandcamp.com/ Stairway - Patrick Patrikios (YouTube audio library)