🤚 Getting a 2160p screen to watch 2160p movies.
👉️ Getting a 2160p screen to watch 1080p movies in split-screen with working.
moviegalaxies: Moviegalaxies, movies 410-466 (2018)
Social graphs for over 700 movies from the moviegalaxies.com website. Each node represents a character in a movie and each edge is a same-scene appearance between two characters in that movie. The weight gives the number of same-scene appearances. Networks are extracted from movie scripts automatically.
This network has 38 nodes and 96 edges.
Tags: Social, Fictional, Weighted
I'm very sad I will not be able to see Speed Racer in theaters. All the times are terrible for me.
#movies
I saw something, 'What's your favorite Spielberg film?' and it got me thinking. It's very tough. I think mine has to be Raiders. Closely followed by Minority Report. What's yours?
#film #films #movies
Welcoming your suggestions for atrociously bad 70s/80s catastrophe movies
I just watched an episode of Masters of Horror called Homecoming directed by Joe Dante.
Almost all of Dante's movies are political but you often need to interpret. In 2005 he had something to say about the Iraq War and George W. Bush. This time there was no subtlety involved.
Homecoming is not great. If it had been purely black humor it might have worked better but it also tries to be sentimental which falls flat. As a political statement I love it.
If you want the spoi…
I hope you didn't "buy" any of these movies on Playstation: https://www.playstation.com/en-gb/legal/psvideocontent/
The Man With The Golden Gun: Not bad at all!
The first film that feels modern, without any hokey effects/compositing. Weirdly unremarkable theme song too—don't think I've ever heard it anywhere else. Also, second film now not to mention SPECTRE.
And Moore is a great Bond, in a different way. Doesn't have the physicality of Connery, but inhabits the persona well.
#movies
Two Chairs Talking
Two ex-chairmen of the World SF Convention talk about books, movies and anything else we feel like...
Great Australian Pods Podcast Directory: https://www.greataustralianpods.com/two-chairs-talking/
Just saw Glennkill. Storywise it’s nice and I enjoyed it. It had Wallace and Gromit or Shawn the Sheep vibes.
The CGI sheep were incredible. Not just the wool, also their horns. I just didn’t really buy Wolverine as a shepherd. But as you know from the trailer: he gets killed early on 😀
#movies #TheSheepDetectives
Back when the Polish TV introduced the Dragon Ball series (in the late 1990s, IIRC), my parents were perplexed. How could you create a children's animated movie (because obviously animated movies must have been for children) with so much violence?
On the other hand, I'm worried about modern animated series (these formally classified as appropriate for children). They are specifically designed to keep children overstimulated, addicted to nonstop action, thirsty for more.
My brother recently told me that he set a Disney animated movie from the era of our childhood to his children. They simply didn't want to watch it, they found it so boring.
PS. I actually find these modern animations tiresome. I mean, why do things have to move that fast all the time?!
SCS Software, the creators of Euro Truck Simulator 2 put out a blog post about their upcoming "Isle of Ireland" DLC
#gaming #pcgaming #eurotrucksimulator2
A catalog of free & public domain movies from Archive.org and YouTube
https://select.github.io/movies/
movielens_100k: MovieLens 100K (1998)
Three bipartite networks that make up the MovieLens 100K Dataset, a stable benchmark dataset of 100,000 ratings from 1000 users on 1700 movies. These data capture the tag-movie, user-movie, and user-tag networks. (Also available from MovieLens are 1M, 10M and 20M folksonomy datasets.).
This network has 24129 nodes and 95580 edges.
Tags: Informational, Folksonomy, Unweighted, Multigraph, Timestamps
I Love Boosters is badass, Boots Riley is a genius, dammit, he did it again. More movies like this, less of everything else. 😂
Ok so just finished "On Her Majesty's Secret Service" and good lord it is an objectively bad film
#cinema #movies #JamesBond
A look at Doug Liman's $70M Bitcoin: Killing Satoshi movie, which uses AI for sets, lighting, and more in post-production, cutting costs from an estimated $300M (Emily Zemler/The Wrap)
https://www.thewrap.com/creative-content/m
Senator Mark Kelly, former astronaut, explains his top 3 space movies.
Do they overlap with your favorites?
#Space #MarkKelly #movies
Every day I think about how right that little gray dude was
Started writing about #selfhosting #movie #streaming using @…
wait... i can buy Sony VHS movies from Amazon?
lol
Why is a BluRay of a 1994 reasonably good, but not incredible, movie $60?
Our media world is so weird.
Geologists on the silver screen—the sequel: #movies, too ...
Revisiting HER in the Age of AI Relationships by Panic World
#movies
Graduation Day (1981)
Speaking of graduations...
The new wave band Felony performs “Gangsters of Rock” at the 55min mark in this slasher movie. I love that band!
This film was made for about $250k but grossed more $24million 🤯
Oh and Vanna White makes an appearance.
#music #movies
Boots Riley must believe good movies have the same metric as bad code – WTFs per minute, https://www.osnews.com/story/19266/wtfsm/ – and i gotta say it really works for him.
My friend and I went to see *Project Hail Mary* today. A hearty recommendation from me. I haven't been to the movies for ages but this one was definitely worth the admission (especially when it's half price on Cheapie Tuesday).
#Movies #ProjectHailMary
Hast du eine Superbox zum Serien streamen zu Hause? Verbrenn das Ding sofort! Darknet Diaries hat eine ganze Folge darüber gemacht. Sehr hörenswert.
Darknet Diaries: 172: SuperBox
https://darknetdiaries.com/episode/172/
Warum hat die Fernbedienung dazu ein Mikrofon und einen Bluetooth-…
Aadam Jacobs ging 1989 mit einem Rekorder zu einem Konzert von #Nirvana. Seitdem hat er sich seinen Spitznamen "Taper Guy"" redlich verdient. Mittlerweile nahm er mehr als 10.000 Konzerte auf Band auf. Jetzt werden die Aufnahmen digitalisiert und bei
die doku "the librarians" ist jetzt bei filmfriend.de verfügbar und im mai "film des monats"!
u.a. die stadtbücherei münster weist darauf in ihrem newsletter hin; sehr gut. 💪
» https://muenster.filmfriend.de/de/movies/the-librarians
This is an absolute gold mine for music fans, especially us #genx folks. After listening to pre-Grohl Nirvana, I'm now listening to Tracey Chapman from 1988. Thank you Aadam Jacobs and the @… !!
How Hollywood support staff are integrating AI into workflows, from mundane tasks to creative development, amid cost-cutting and workload demands (Mia Galuppo/The Hollywood Reporter)
https://www.hollywoodreporter.com/movies/movie-featur…
james cameron didn't make these shitty avatar movies with over the top messaging for you to repeat exactly what was criticized
Upcoming #Backrooms Movie used #blender for most of the #VFX :blobratheart:
MINI MOVIE REVIEW
"Remarkably Bright Creatures"
This movie was like if a Hallmark or Lifetime movie became watchable and had a budget.
It's simple and fun, and Sally Field still has it.
My wife, as usual, told me I should read the book because it's much better.
#Movies #Netflix
> "Warner Bros would prefer that you referred to their new hard R take on The Mummy as Lee Cronin’s The Mummy"
I *implore* writers to stop referring to horror movies as "hard R". That term has another meaning you should consciously avoid.
https://www.theguardian.com/fi…
I haven't been seeing a lot of movies in the theater, lately. It's mainly because hollywood hasn't been releasing a lot of movies lately. I still pay Marcus a monthly fee for their membership program, though and I am up to 7 credits. I need to make more room in my schedule to see something.
🕰️ Those were the days!
Real animation done by a real human.
Today marks 20 YEARS since "Animator vs. Animation" by Alan Becker was posted to https://www.newgrounds.com/movies
QUESTION:
What is your favorite order to see starwars if you would recommend it to a women that never watched it?
#starwars #movies #letterboxd
Got movies on my Linux laptop. But my AirPods don't connect to the laptop and I want to enjoy the audio. So I'm installing JellyFin server now to stream to my iPad ... I love it when open systems allow me to solve problems on my own.
Starting to watch Jesus Christ Vampire Hunter now, for some reason.
#movies #JesusChristVampireHunter #2000s
movielens_100k: MovieLens 100K (1998)
Three bipartite networks that make up the MovieLens 100K Dataset, a stable benchmark dataset of 100,000 ratings from 1000 users on 1700 movies. These data capture the tag-movie, user-movie, and user-tag networks. (Also available from MovieLens are 1M, 10M and 20M folksonomy datasets.).
This network has 24129 nodes and 95580 edges.
Tags: Informational, Folksonomy, Unweighted, Multigraph, Timestamps
Watched #Idiocracy (2006) today for the first time while at the gym. It's one of these movies that are both great and horrible at the same time. It also kinda feels like a prophecy... 🥴
Last night, I filled a gap in my basic knowledge by watching 'Titanic' 🙂↕️
Good movie 👍🏻
#Titanic #Movies #ShareYourMovies
just realizing Keke Palmer was Akeelah in Akeelah and the Bee. wild!
#movies
I wonder if there is a correlation between the fact I’ve watched more horror movies since I’ve transitioned.
#trans
I’m pivoting to my agentic era*
*rewatching James Bond movies
moviegalaxies: Moviegalaxies, movies 410-466 (2018)
Social graphs for over 700 movies from the moviegalaxies.com website. Each node represents a character in a movie and each edge is a same-scene appearance between two characters in that movie. The weight gives the number of same-scene appearances. Networks are extracted from movie scripts automatically.
This network has 70 nodes and 299 edges.
Tags: Social, Fictional, Weighted
Don't tell me that a film has a twist. That is in itself a spoiler.
#films #movies
Didn‘t watch this yet but ARTE already had another great doc by the same director ( @ sixtus@mastodon.social ) about AI slop and fakes on the internet. If know German or you‘re francophone. This latest one might even be English. https://chaos.social/@Katika/116534409768887613
Loved Backrooms. Found it cool as hell. One of the best flicks I've seen in a WHILE. Bizarre, all kinds of unexplained shit-- just everything I love about movies. Highly recommend.
#horror
FINALLY a reason to watch Disney , other than to rewatch Andor S1-S2 for the 7th time.
✅ Punisher One Last Kill review: The perfect antidote to Marvel's messy multiverse
https://www.polygon.com/punisher-one-last-kill-review-marvel/
movielens_100k: MovieLens 100K (1998)
Three bipartite networks that make up the MovieLens 100K Dataset, a stable benchmark dataset of 100,000 ratings from 1000 users on 1700 movies. These data capture the tag-movie, user-movie, and user-tag networks. (Also available from MovieLens are 1M, 10M and 20M folksonomy datasets.).
This network has 24129 nodes and 95580 edges.
Tags: Informational, Folksonomy, Unweighted, Multigraph, Timestamps
#LetterboxdFriday #LastFourWatched for this week- I mean, The Royal Hotel was from a previous week (not watching a ton of movies lately), but I did see three flicks since the last time. Finally took in World War Z (weird) ahead of its sequel. The Well was awesome- great twist- and Mike and Dave was hilar…
movielens_100k: MovieLens 100K (1998)
Three bipartite networks that make up the MovieLens 100K Dataset, a stable benchmark dataset of 100,000 ratings from 1000 users on 1700 movies. These data capture the tag-movie, user-movie, and user-tag networks. (Also available from MovieLens are 1M, 10M and 20M folksonomy datasets.).
This network has 24129 nodes and 95580 edges.
Tags: Informational, Folksonomy, Unweighted, Multigraph, Timestamps
Tubi becomes the first streamer to launch a native app within ChatGPT, allowing viewers to find movies or shows to watch by using conversational phrases (Lauren Forristal/TechCrunch)
https://techcrunch.com/2026/04/08/tubi-is-the-first-strea…
Watching that best of all Bond movies. Moonraker
Introducing #KinoPolis 🎞️ — a personal screening room for early cinema.
Films from 1896 to the 1930s, free to watch, organized into collections like German Expressionism, Soviet Montage, and Early Hitchcock.
Come get lost in the movies that invented movies!
http://w…
moviegalaxies: Moviegalaxies, movies 410-466 (2018)
Social graphs for over 700 movies from the moviegalaxies.com website. Each node represents a character in a movie and each edge is a same-scene appearance between two characters in that movie. The weight gives the number of same-scene appearances. Networks are extracted from movie scripts automatically.
This network has 38 nodes and 96 edges.
Tags: Social, Fictional, Weighted
Just did Mike and Dave Need Wedding Dates and it was easily one of the best, funniest comedies I've seen in a while. Just unreal 😂
#movies
moviegalaxies: Moviegalaxies, movies 410-466 (2018)
Social graphs for over 700 movies from the moviegalaxies.com website. Each node represents a character in a movie and each edge is a same-scene appearance between two characters in that movie. The weight gives the number of same-scene appearances. Networks are extracted from movie scripts automatically.
This network has 18 nodes and 50 edges.
Tags: Social, Fictional, Weighted
Kate Beckinsale to star in 'Twilight of the Dead' -- George Romero had written a treatment for it before he passed in 2017 and regarded Twilight of the Dead as the conclusion to his epic saga (six movies and various spinoffs and remakes). The most recent movie in the franchise came out in 2009.
https:/…
moviegalaxies: Moviegalaxies, movies 410-466 (2018)
Social graphs for over 700 movies from the moviegalaxies.com website. Each node represents a character in a movie and each edge is a same-scene appearance between two characters in that movie. The weight gives the number of same-scene appearances. Networks are extracted from movie scripts automatically.
This network has 42 nodes and 109 edges.
Tags: Social, Fictional, Weighted
movielens_100k: MovieLens 100K (1998)
Three bipartite networks that make up the MovieLens 100K Dataset, a stable benchmark dataset of 100,000 ratings from 1000 users on 1700 movies. These data capture the tag-movie, user-movie, and user-tag networks. (Also available from MovieLens are 1M, 10M and 20M folksonomy datasets.).
This network has 24129 nodes and 95580 edges.
Tags: Informational, Folksonomy, Unweighted, Multigraph, Timestamps
moviegalaxies: Moviegalaxies, movies 410-466 (2018)
Social graphs for over 700 movies from the moviegalaxies.com website. Each node represents a character in a movie and each edge is a same-scene appearance between two characters in that movie. The weight gives the number of same-scene appearances. Networks are extracted from movie scripts automatically.
This network has 32 nodes and 80 edges.
Tags: Social, Fictional, Weighted
moviegalaxies: Moviegalaxies, movies 410-466 (2018)
Social graphs for over 700 movies from the moviegalaxies.com website. Each node represents a character in a movie and each edge is a same-scene appearance between two characters in that movie. The weight gives the number of same-scene appearances. Networks are extracted from movie scripts automatically.
This network has 50 nodes and 169 edges.
Tags: Social, Fictional, Weighted
moviegalaxies: Moviegalaxies, movies 410-466 (2018)
Social graphs for over 700 movies from the moviegalaxies.com website. Each node represents a character in a movie and each edge is a same-scene appearance between two characters in that movie. The weight gives the number of same-scene appearances. Networks are extracted from movie scripts automatically.
This network has 37 nodes and 71 edges.
Tags: Social, Fictional, Weighted
douban: Douban friendship network (2009)
A friendship network among users on Douban.com, a Chinese website providing recommendations for books, music, and movies.
This network has 154908 nodes and 327162 edges.
Tags: Social, Online, Unweighted
https://networks.skewed.de/net/douban…
dbpedia_starring: DBpedia film-actor network
A bipartite network of movies and the actors that played in them, as extracted from Wikipedia by the DBpedia project. The date of this snapshot is uncertain.
This network has 157184 nodes and 281396 edges.
Tags: Economic, Employment, Unweighted
https://network…
moviegalaxies: Moviegalaxies, movies 410-466 (2018)
Social graphs for over 700 movies from the moviegalaxies.com website. Each node represents a character in a movie and each edge is a same-scene appearance between two characters in that movie. The weight gives the number of same-scene appearances. Networks are extracted from movie scripts automatically.
This network has 25 nodes and 91 edges.
Tags: Social, Fictional, Weighted