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scottymcgeesterwrites · 4 years ago

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Final Fantasy XV Review

Year: 2016

Original Platform: PlayStation 4

Also available on: PC (Steam), XBox One

Version I Played: PlayStation 4

Here we go. The final Final Fantasy review of the main single-player games. I just want to say, first off, we’ve been waiting for this game since 2006. It took them ten damn years to finally release this game. I clearly remember the teaser trailer they released when it was called Final Fantasy XIII Versus, and my next-door neighbor and I were so hyped for this game when we were freaking teenagers. After years of delays, Square Enix revamped it into Final Fantasy XV.

Did it live up to the wait? Well, read and find out.

Synopsis:

Noctis Lucis Caelum is the heir to the throne of the kingdom of Lucis. On his birthday, he sets off with his three best friends and bodyguards (Ignis, Prompto, Gladio) to marry his betrothed, Lunafreya. The marriage is supposed to be a political one, though Noct and Lunafreya had grown up together and become fond of each other. But peace turns to war as the empire of Niflheim betrays Insomnia and invades. Noct, now on the run, has to reclaim his right to the throne by collecting the necessary family heirlooms which will banish the darkness.

Gameplay:

Open-world Final Fantasy.

That is the big selling point for this game.

A MASSIVE step up from Final Fantasy XIII’s gameplay, Final Fantasy XV has you roaming around and attacking enemies on the field in real time. The battle system returns to something slightly more conventional by having you cast spells and use items. It seems like this is what Square really intended to do after Final Fantasy XII. Looking back, Final Fantasy XIII feels like some prototype before Final Fantasy XII, so it really becomes apparent that Final Fantasy XIII’s gameplay comes off as a huge mistake.

This game’s major’s strength comes from the player engaging with a massive world. You camp. You take on hunts. You take on a bajillion sidequests. You run across the world. You drive across the world. You can ride a chocobo across the world.

However, the dip in the gameplay comes from how easily accessible these sidequests are. The map tells you exactly where you go 24/7. I started to have an existential crisis around my 50th sidequest in a row. Why am I doing this? What’s the point? I go here to kill a thing, or go there to help someone by giving a potion or taking a picture. You start to realize that a good bulk of sidequests are either hunting daemons or fetching an item. You start to deconstruct the meaning of playing a video game as you think to yourself, “Why do I play video games?” while also thinking “But wait, one more and then I swear I’m done.”.

I get it, not everyone has the time nowadays to figure out a huge game like this. I get it, video games are now marketed to everyone for ease. At the same time, I personally love a good challenge. I mean, I’m the guy who has Dark Souls as one of his favorite video games of all time, so my opinion on the matter might definitely be skewered compared to most. I generally want to feel like I actually figured something out by myself rather than following a tracker on the screen and walking from task to task and then saying, “Okay done. Next.”.

Too much of that and playing a video game starts to feel like a 9 to 5 job to me. This game is great to play during quarantine, but at one point I saw playing this game as feeling like an actual job. Wake up, eat breakfast, time to hunt some daemons.

This is the growing conflict some people have with story-driven games versus open-world games. I see the argument focused too much on words like “linear”, but in reality we should be talking about “automation”. If a video game is too automated, then did you really play a video game? Or did you watch a movie that allows you to control the camera angle? At first, the idea of driving around an open-world Final Fantasy game sounds amazing. Isn’t that what fans always dreamed of? In reality, you don’t really drive around at your leisure. Even when you have the car set to “manual”, you can’t speed up, drive off-road, or pull off a sick drift like in The Fast and the Furious. Your car still automatically stays on the road wherever you’re going. It’s not so much “manual” as it is “I can control where and when to stop and which road to take”. Riding chocobos at your leisure is much more fun, but becomes increasingly impractical as you can just fast-travel to necessary locations in your car.

The sights and sounds of the fictional world of Eos are enough to gloss over these shortcomings though. It IS still fun to roam around and fight monsters and save the day. My bottom line is, “You don’t think about just how mindless the tasks are unless you keep playing for many days straight.”. And I poured hours into this game day after day because of the 2020 pandemic quarantine.

Graphics:

Obviously the best thus far. However, in-game facial expressions on the NPCs are still quite stilted and awkward. This game made me realize that we’ve yet to jump a hurdle when it comes to in-game graphics. The game is so polished but there are still limitations when it comes to giving the characters natural movements, both in body and lips. So an NPC could be shouting “WOW THAT’S AMAZING!” but have a straight face jumping up and down, despite the fact that the character model is the most realistic we’ve created so far in a video game. I was looking back at in-game cutscenes of Crisis Core: Final Fantasy VII, and found it ironic that they can portray body movements so much better, but that’s the trade-off. Less graphics power to portray realistic bodies, but the graphics power can then be allocated to focus on natural movements. Nowadays, all the graphics power is focused on making things look good, but that hardly leaves room for making things move naturally.

Story:

After the overly-complicated plotline of Final Fantasy XIII, Final Fantasy XV feels like a breath of fresh air. On the surface, it’s a straightforward tale of a boy seeking to become a king after his father is brutally murdered by enemy forces. The bromance between the young king and his bodyguards is endearing. Each character feels distinct and genuinely makes you laugh. The setup sounds like prime real estate for an emotionally charged storyline.

Unfortunately, it falls apart somewhere around the last quarter. What should have been a strong and straightforward story turned into a rushed, hasty mess by the final act.

The story started SO strong, they practically had it in the bag, but then it became apparent that many important elements were glossed over - especially when it came to the main villain. I realized that some things required me to read between the lines, or even were only explained in character dossiers in the archive section of the menu. Supposedly, the movie Kingsglaive: Final Fantasy XV explains more, but do you really expect me to have to watch a separate movie to understand the actual game? The final quarter of the story feels like someone was trying to finish NaNoWriMo, realized they were running out of time, and quickly jumped from scene to scene to reach that 50k word goal. The ten-year time-skip is a joke. The final chapter is sorely disappointing.

The ending was appropriate though, and even beautiful. However, the overall story didn’t have the necessary emotional weight to really make me feel anything. I thought to myself, “I feel like I should be tearing up but instead I feel nothing.”. Even Final Fantasy XII, which lacked a romance, had me swelling up at the end. Final Fantasy XV didn’t make me swell up until literally the last few seconds of the post-credits scene.

People complained about the advertising (Coleman, Cup Noodles) but that didn’t bother me.

What does bother me is the lack of variety in the main cast, and in numerous ways. There were so many interesting side characters that didn’t receive much screen time, or use at all in the story. The strong focus on only the four male leads made it a sausagefest. I was craving more out of Aranea Highwind and Iris Amicitia. They are important but don’t get any screen time at all in the final chapter, nor do we ever hear from them ever again after the time-skip. Aranea Highwind was such a cool character, but once again ends up being wasted potential.

The main cast lacked distinctive styles. When I first saw the main cast, I had a hard time telling them apart. They looked like a k-pop band. Compare the main cast of Final Fantasy XV to literally any other Final Fantasy main cast and you can immediately spot the difference.

The four main leads do have distinct personalities, and I quite loved hearing their comments and banter. It felt realistic, but at times it became ridiculous. I rolled my eyes when Prompto would say things like, “Hashtag sorry not sorry.” That was a bit too on the nose, and came off as Square trying to pander to the current generation.

But what really rubbed me the wrong way is the incredible lack of non-white characters in the entire game. Lestallum feels so wrong to me as a Hispanic. Lestallum is supposed to be modeled after Havana, Cuba.

Its music, its buildings, its activities. It has a tropical climate, and yet every single denizen is pale white. Every. Single. One. I am not exaggerating. It feels so absolutely wrong walking around that city and not seeing anyone with the slightest shade of brown. This isn’t some uncalled-for SJW rant, it’s a simple fact. Tropical climates breed tanner skins. My brain naturally did a double-take when seeing the all-white population, saying, “Hmmm, something’s wrong here.”. For God’s sake, Final Fantasy XII, made over a decade earlier, did a better job at displaying the various nuances in skin tones, and that was on the PlayStation 2! Final Fantasy X, even older, seemed to properly portray tropical beach populations, inspired by the Philippines, with the character Wakka.

I noticed that they really took the time to incorporate elements from virtually every single Final Fantasy game. Aside from the crystals, the modern settings, and other obvious elements, four male leads are reminiscent of Final Fantasy III, the sinister chancellor hearkens back to Kefka from Final Fantasy VI, the enemy Yojimbo resembles Final Fantasy X’s version of Yojimbo, a certain boss battle reminded me of Cid Raines from Final Fantasy XIII.

Also, there’s Dino. Quite possibly the most annoying Final Fantasy NPC ever.

The overly obnoxious Italian stereotype made me want to punch his face, and also took me out of the experience of the fictional world. Every time you spoke with him he's all like "HEY HOW YOU DOIN WELCOME TO OLIVE GARDEN YOU TALKIN TO ME BADA BING BADA BOOM SPICY PIECE OF MEATBALL CAPISCE? AMIRITE??"

Square seemed to treat this game as a milestone in the series, alluding to everything the series ever did. It’s a shame that the story itself wasn’t quite up to snuff to be held in such regard.

Music:

The game’s major lyrical song is copyrighted, which is a first for a Final Fantasy game. It makes sense why they chose the song “Stand by Me”, both in literal and figurative terms of the story.

The score to this game is quite fantastic. The series has its first female composer, Yoko Shimomura. I have absolutely no complaints about the music. Nobuo Uematsu didn’t even pop into my head during the entire game. It’s the first time since Uematsu’s departure that I felt immersed in the score. The motifs are distinct and strong. The battle music is vibrant and an orchestral orgasm to listen to.

Notable Theme:

��Somnus”

youtube

The main theme of the game. It plays right away in the main menu. I love how it is incorporated into the rest of the score, and my brain kept wanting to hear it to its completion.

Direct Sequel?

Nope. However, there is downloadable content that fills in the gap of events within the game. Supposedly, Final Fantasy XV is loosely connected to Final Fantasy XIII and Final Fantasy Type-O, all sharing common themes and possibly set in the same universe. You can also watch the prequel movie, Kingsglaive: Final Fantasy XV.

Did it Live up to the Hype?

Eh.

Yes, and no.

It was cool to play around, but the rest is a flaccid attempt at being a notable entry in the series “for fans and first-timers”, as the words proudly display every time you load the game. It’s not the worst in the series, but certainly not the best. It’s somewhere in the mid-to-low tier.

#final fantasy #final fantasy xv #square enix #ps4 #fantasy #fantasy rpg #rpg video game #rpg #video games #onvideogames #noctis #ignis scientia #prompto argentum #gladiolus amicitia #aranea highwind

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notquiteaghost · 5 years ago

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helo i love yuo

so, you may have seen this post where i ramble at length about the admiral (the best magnus archives character). this is that, but... even longer. 3′000 words long, to be exact

this rambling contains the admiral; jon&georgie friendship; the beholding throwing jon a bone and letting him talk to cats; the admiral: this time he's yelling; georgie/melanie origins; & bad things exclusively happening off-screen. we are on fluff about cats 24/7 lockdown

and it’s also on AO3

jon definitely had cats growing up and is the kind of person whose life feels Wrong if he doesn’t live with any

he says this to georgie offhandedly, one day, when they’re living together in a decent flat (as opposed to the Hell House they lived in the previous year with various other uni friends), and both have decent jobs (jon in a small, independent bookshop and georgie as a copyeditor), and in general their lives are Going Good

and he’s not trying to hint or anything, (or at least not consciously), just, tells a story about the small angry ex-feral his grandmother had who hated everyone, frequently disappeared for days, had to be sedated for basic vet check ups, but would lie on his feet in the evening while he read and purr, so quietly he felt more than heard it

and georgie doesn’t say anything about getting a cat in that moment either, just tells a story about her own childhood cat’s habit of stealing socks and hiding them under cabinets

but then a couple days later jon comes home and on their sofa is a tiny ball of orange fluff

georgie is sat next to him and she grins and says, “this is the admiral”

“where did he… come from?” jon asks, because he knows georgie, and he’s having visions of her breaking into the house on the end of their road and just. grabbing a cat.

(the house is occupied by an older man who cares for his many, many cats just fine, aside from how he won’t spay any of them and it seems like with every passing month another six cats have appeared)

“rebecca — she works at the library, you’ve definitely met — her cat just had a litter. he’s ten weeks, he’s had his first two shots, she gave me a huge bag of kitten food”

“right. and you decided we’re getting a kitten…?” “this morning.” “oh, of course.”

the admiral is very small, and ginger and long-haired, and he really likes to curl up on them — on georgie’s chest while she’s on the sofa, on jon’s lap when he’s reading. his favourite place to sleep very quickly becomes across their shoulders, snug between them and the back of the sofa, like a kitten hood

he’s very vocal, and has many demands, and you will listen to them. he follows jon round the flat shouting in the evening until jon gives in and goes to bed, and then the admiral lies on top of him and purrs up a storm

he’s an indoor cat, because jon and georgie live in a third floor flat, and so one of his other frequent demands is for someone to trail a tie along the floor for him to murder (yes, they have bought him many actual cat toys. yes, these are all incredibly boring and all he wants to chase are georgie’s shoelaces and jon’s ties)

he likes marbles, rubber balls, bottle tops and other small things he can bat around the tile in the kitchen, and he especially likes when someone stands at the other end of the kitchen and bats them back. they call it tennis. he always wins

if either of them do anything in the kitchen he has to be sitting on the counter to supervise. he doesn’t usually care about the actual food (unless it’s chicken) but he Has To Know

in general he just likes to have his people in his line of sight at all times. if they’re in different rooms he’ll alternate between them, sometimes with increasing frequency until he’s getting up every five minutes very pointedly and narrating his journey angrily, which almost always has the desired effect of them giving up and moving

he sits on georgie’s lap more often, because if jon’s sat on the sofa it’s rare he’s arranged in such a way to make a lap. often the admiral will sit sideways on georgie’s lap and reach out a single paw to rest on the closest part of jon. sometimes this is jon’s face

he loves new people. anyone who comes to their flat is obviously here to see him, and he’s very happy to accommodate that. if any visitors sit down he will be on their laps within seconds. why else would they have sat down! he’s lovely and they love him, obviously

he hates the hoover, it’s his sworn mortal enemy and one day he will kill it. this is unfortunate, as he’s long-haired and fluffy and without regular intervention, all the carpet in the flat would be ginger. he can’t be in the room being hoovered, as he pounces on the cable with enough murderous intent to do real damage. and after the hoovering is done he sulks

he sulks for weeks when jon moves out

he is, in fact, the reason jon & georgie remain in contact, because regardless of how vicious the things they said were by the end, the admiral pines. he lies on what was jon’s pillow and looks incredibly mournful, and georgie doesn’t think it’s fair if only she has to feel guilty about it, so she takes a picture and texts it to jon

and jon isn’t any less angry yet, but dammit the admiral is his cat too, so then they have this weird unspoken agreement where they never discuss themselves but georgie sends him frequent admiral updates and every so often jon comes round and lies on the floor so the admiral can sit on his chest and knead his stomach with pointed force while scolding him at length

(eventually they start talking properly again) (you can pry platonic jongeorgie out my cold dead hands) (jon gets distant during s2 but prior to that they go out for coffee every couple weeks) (they text a lot. jon has to come round georgie’s at least once a month or the admiral starts shredding the hoodies of his georgie has permanently stolen)

when georgie starts what the ghost, of course the admiral has to supervise. he likes to curl up in her lap while she records. if she stops petting him he reaches up to headbutt the mic

whenever he isn’t on her lap he sits on top of her script / reference files / any other sheet of paper she could need to look at. he loves to sit on paper, especially paper she doesn’t want him to sit on

the what the ghost twitter account is 30% episode announcements, articles, behind the scenes stuff, etc, and 70% admiral pictures

one tweet in particular has like 50k retweets. it’s a video of georgie getting up mid-recording to get a drink and the admiral, sat on her desk, leaning forward to meow into the mic as if continuing what georgie was saying

jon is campaigning for georgie to make the admiral his own twitter account. georgie knows she’d almost immediately neglect her own twitter account and she kind of needs to keep that up for her job. jon argues that the admiral would reach people who might otherwise not check the podcast out; georgie counters that if he thinks it’s such a good idea why doesn’t he run it; jon points out he doesn’t live with the admiral and also has a job of his own; work/life balance is a well-worn argument topic in of itself so generally then they drop it

and then jon is accused of murder and moves back in with georgie and the admiral is overjoyed, he purrs nonstop for three straight days, he tries to lie on top of jon nonstop for three straight days, he is the single good thing in jon’s life right now and jon tells him this frequently

then after a couple weeks jon starts to hear words, when the admiral meows, which. is a thing. sure is a thing. that is happening.

jon stumbles into the kitchen at 4AM, able but unwilling to sleep, on the hunt for more tea, and hears a concerned voice call “jon? jon are you okay?”, and he calls back “i’m fine i just couldn’t sleep— ” before turning round and seeing stood in the doorway not georgie but the admiral, who meows again, except jon also hears “i will lie on you”, and then he has to sit on the kitchen floor for a minute

the admiral comes over, of course, and sits on his lap, and purrs and headbutts jon’s jaw and kneads his stomach, and says “yes love you” when jon says, “thank you admiral”

so then jon stares into space for a bit, still stroking one of the admiral’s ears, before asking, hesitantly, “have you… always understood me…?”

but the admiral mrrrps in that way of his that means no, and says “since you came back” so, that’s good, at least jon’s cat isn’t walking around with a wealth of blackmail material

because, of course, he’s the kind of loud shouty man you can keep up a conversation with, and jon and georgie both have a habit of talking through their problems with him

and he doesn’t tell georgie, because this is before he comes clean about All Of It and also this is, in his opinion, a touch more batshit than even evil doors or women made of wax. and he talks to the admiral like he’s a person and they’re having a conversation anyway!

but, the thing is, georgie isn’t an idiot, and notices that when jon asks the admiral what he did with his day, he seems to actually listen to the answer, and then knows about things that the admiral saw but jon didn’t

so a couple days after jon finally explains about the eldritch fear beings and how he works for one and some others want to kill him, after georgie insisted they both stay in for a day, no mention of anything remotely supernatural, just rewatching monster factory and eating ben & jerrys, the day after that georgie sits down across from jon at the kitchen table and asks, “so, you know things? that’s the deal, yeah?” and jon nods, not awake enough to be wary about where this could be going, and georgie adds, “things like what the admiral’s saying?”

and jon. freezes. but georgie just rolls her eyes, says, “what, i can accept you’re on a crusade to stop evil mannequins from ending the world, but you talking to the cat is too far?”, and, well, that’s a good point

so then, as well as having very surreal conversations with the admiral about the relative merits of various brands of cat food, and his thoughts on the reasoning behind various human activities (“georgie is trying to befriend the microphone.” “no it's– the microphone isn’t alive.” “georgie knows that?” “she’s recording, so other people can hear what she has to say without being here.” “!!! record me!!! tell everyone to bring chicken!!!”), and why jon is an idiot fool who should never go anywhere alone again (“don’t even have claws, jon. take me, i will bite.” “i appreciate that, but–” “i am very sharp! i bite hard! i draw lots of blood!” “yes, you’re very dangerous, and that’s why i need you here, to keep georgie safe.” “i’m not kitten i know you are manipulating” “i love you very much, and i promise to be more careful, okay?” “hmph.”)

as well as that, jon is also acting as translator for georgie — if jon’s around, the admiral can understand georgie, but georgie can’t understand the admiral (if the world wasn’t ending, jon would find that absolutely fascinating, but alas)

the admiral tells them both he loves them, a lot. after they feed him, when they’re petting him, but also sometimes he’ll wake up from a nap, see jon sat in the other armchair (georgie’s flat has two armchairs, one with big armrests she found in a charity shop that’s the reading chair, one with a very low back that came with her flat and is the admiral’s), say “love you jon” with great contentment, then go back to sleep. it makes jon tear up every single time

he’s VERY upset when jon moves out. he does not agree with jon’s logic at ALL, and he rants to georgie about it at length, but she can’t understand him anymore

georgie knows the gist of it, though, and when, four days after he left, jon stops replying to her texts, or picking up her calls, she does get a touch worried, and turns up at the institute for some answers

she has melanie’s number, of course, but melanie has also been getting worse and worse about actually responding when contacted (because she’s so angry, all the time, and she just wants to hurt something, and georgie wants her to get out the institute, and melanie is worried what might happen if they argue about it again), so she goes in person, and finds basira

basira doesn’t know where jon is, hasn’t seen him in a while but that’s nothing out the ordinary, and the only person who probably would know is elias, and elias isn’t exactly… forth-coming

so georgie leaves without answers, and decides whatever jon’s done now, he didn’t see fit to tell her about it beforehand (even though, after mike crew, she made him promise), so he obviously doesn’t want her help, so fine. fine! she has enough going on, without worrying about an idiot with a death wish who she definitely doesn’t still care about to an alarming degree

she does, also, decide the institute, the– eldritch fear gods, whatever, they don’t get all her friends. she goes back to the institute the next morning, and refuses to leave until melanie talks to her

melanie looks like shit, visibly buzzing with rage but also with an air of deep, deep exhaustion, and she hasn’t even finished asking what the hell georgie wants before georgie has grabbed her arm and is dragging her outside

and melanie — there’s a knife in melanie’s pocket (there’s always a knife in melanie’s pocket), but she doesn’t reach for it, there’s no sudden surge of mindless rage, she lets georgie drag her all the way out the institute, and into a cafe four blocks away, the one that does the pastries martin likes

georgie doesn’t say anything about leaving the institute, or where jon is, or the unknowing. she orders them both drinks (a cinnamon latte for melanie, with extra whip cream, meaning georgie remembers her favourite drink still, which makes something in melanie feel fuzzy), and just immediately launches into a rant about this source she’s trying to track down for a what the ghost episode

and then she keeps doing that, every week, barging her way into the institute and barging back out with melanie in tow until melanie starts replying to her texts and answering her calls and waiting for her outside

the admiral still thinks they should be more worried about jon, but he no longer has any way to tell georgie that, and he likes the sound of melanie

when jon returns from being kidnapped, he doesn’t actually visit georgie, or even reply to her texts. she finds out he’s back from melanie, and then has to, again, turn up at the institute and demand jon come back to the flat in person. she’s incredibly angry, but not actually at jon

the admiral has a LOT to say when he sees jon again, mostly to the tune of “i TOLD YOU” and “georgie doesn’t listen” and “weeks!!! lucky you aren’t dead!!!! not safe alone!!!!!” and “idiot, idiot, love you, most idiot”. jon just sits down on the floor of georgie’s entryway and lets the admiral sit on his chest and yell

he, of course, does not agree with jon’s decision to not only leave the flat but the country. jon is a FOOL who will DIE doesn’t he love the admiral!!! doesn’t he want to stay safe!!!

georgie leans against the wall behind them and nods emphatically the whole time

once jon leaves again, the admiral is, to say the least, Upset

jon calls as regularly as he can, to reassure them both he’s alive, and georgie starts spending more and more time with melanie

the admiral loves melanie. she’s sharp and quick, would be good in a fight (not that he’s ever seen her do any violence, cats can just tell some things), and she makes georgie happy, and she’s good at ear scritches, and she doesn’t know what he’s saying exactly but she’s pretty good at getting the gist

he tries to tell georgie that melanie should move in, but can’t get her to understand the specifics. she does start inviting her round more, though, which is good. sometimes they talk into the microphone together, now

after jon returns to england and actually goes back to the archives he shows everyone who stays still long enough admiral pictures

mostly that means martin. and basira (basira is a cat person, thank you) (she hasn’t met the admiral in person despite georgie offering because she Isn’t Here To Make Friends) (but she’s still very invested in him and his exploits)

martin will come into jon’s office with tea and to check he has actually eaten today and jon will immediately go “look look come look at this” and show the video georgie sent that morning of the admiral trying to attack a fly on the other side of her bedroom window

“he’s such an idiot” jon says fondly, and martin looks at him and thinks i know the feeling

and, also, this means jon and melanie have something to talk about that isn’t a) No, Seriously, What If We Stabbed Elias, b) the circus apocalypse, or c) are you… dating my ex…

melanie is not dating georgie. melanie is possibly the only person who doesn’t realise she only isn’t dating georgie Yet

melanie would probably realise she’s in the first third of a slowburn friends-to-lovers if not for, y'know, the slaughter. she knows being around georgie makes the anger dissipate, somewhat, but it’s not yet enough to make room for any other feelings

jon asks, of course, once he’s been back a couple weeks, lying on the floor of georgie’s living room with the admiral being a loaf on his chest while georgie sits on the sofa and edits audio

“so,” he says, and georgie hits pause on the audio file and raises an eyebrow, “melanie, huh?”

“we are only talking about that if you admit you have a crush on martin,” georgie fires back, immediately

and, of course, at this point jon has a) spent several hours going On And On about martin to georgie, b) listened to Those Tapes, c) gone gallivanting round the globe and thought ‘oh martin would like that’ approx two hundred times, so he just says, “sure. i have a crush on martin, and once we’ve successfully survived preventing the world from ending, i will probably ask him out. so — melanie?”

georgie lets out a long, low groan, because melanie

she scrunches her nose up when she’s annoyed, and she’s read every goosebumps book, and one time she nearly started a fight with a guy in costa because she overheard him say something shitty about the homeless guy sat outside, and she hums old folk tunes when she’s thinking

and elias really fucked her up with that shit about her dad, and the speed at which she jumps to violence is incredibly worrying, and if georgie doesn’t remind her sometimes she forgets to eat

“once we successfully survive you preventing the world from ending,” georgie says, at length, “i will ask her out.”

jon nods. the admiral says, “been telling her melanie should move in” and then makes his annoyed mrrp noise when the force of jon’s sudden laughter almost dislodges him onto the floor

#the magnus archives #jonathan sims #georgie barker #melanie king #the admiral #yelling at clouds #fic tag #as i said on ao3 #i may follow up with s4 and shit #but no promises

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sol1056 · 6 years ago

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Something I don't understand. According to those stats you posted, VLD has got more or less similar traffic rates as other shows like Castlevania and The Dragon Prince. So why is its Twitter and Tumblr presence so massively higher? For example the trailer for S8 on Twitter has 12k likes, but the trailer of S2 of Castlevania has only got 3.6k, almost just 1/4 of Voltron. I know you said Fandom can't be used to detect actual traffic, but I thought different Fandoms could be compared to each other.

You can compare fandoms, yes, but what you’re comparing in twitter stats vs the stats I listed is the difference between engagement and viewership.

We can determine engagement by looking at traffic on twitter, tumblr, facebook, instagram, and google searches. As google is the only one of those five that has a reach beyond 20% of the internet-using public, I find it’s the best for a blunt-force measurement of audience engagement, which really boils down to “how much people are talking about it.”

Wikipedia’s page views are an extrapolation of viewership. That’s a massive segment of the population who don’t get on twitter, use facebook for family stuff, aren’t into instagram, and have never heard of tumblr (yes, lots of those people exist).

Remember, a controversial show can get people talking but that doesn’t translate automatically to them watching. If you go by twitter stats, S7 should’ve been THE most watched season of VLD ever, ‘cause boy was it blowing up the charts in terms of engagement. Thing is, its viewership stats were just fractionally higher than S6, and still nowhere near S1/S2 levels. It didn’t bring in that many more eyeballs; it just got talked about. A lot.

The other thing to keep in mind is that you’re comparing one show’s seventh season to another show’s first season and a third show’s second season. VLD has had 2 more years to build up its audience than tDP, and a year more than Castlevania (which also doesn’t come with the massive marketing push that DW puts into even its half-assed-marketed shows).

On top of that, Castlevania’s audience skews older, and those of us with jobs don’t have the time to spend all day on various platforms, so our engagement may be as strong but it’s rarely as noisy. (in other words, we’ll miss stuff ‘cause we don’t have the time to go back and see everything in our feed that happened while we were busy elsewhere.) Meanwhile, tDP’s audience skews slightly younger, and twitter is much more a 18-30 kind of platform. So tDP’s audience is either slightly too young for twitter, while its other audience (parents) are just a little older than twitter’s core audience.

So, comparison graphs. Colors for each show in each graph are:

blue: Voltron (VLD)green: She-Ra (SPOP)red: The Dragon Prince (tDP)orange: Castlevaniapurple: Trollhunters (TH)

Viewership stats (via Wiki)

Stats run from 6/1/2016 to 11/17/2018.

VLD’s S1 viewership peaked at about 38K; TH’s S1 peaked at about 21K, same as SPOP over on the far right. Castlevania hit about 72K in its first season, so its S2 drop to around 48K is about standard. tDP managed almost 50K in its first season.

Viewership drops by 30-40% with each subsequent season for the average show; a drop of less than 20% means you have a major hit on your hands. The last season almost always shows a spike, as people come back to see how it ends. If a show ends without that spike, consider it dying a quiet death.

That reality of each subsequent season losing viewers means SPOP is in a really bad place right now, unless it can do a turn-around like TH and have a powerful ending. If SPOP has more than three seasons, by the time it gets to its final season (and that resurgent viewership for the finale), it might barely be a blip on the scale. The longer the show, the higher you want the S1 levels, to offset that expected decline over the seasons.

Engagement stats (via Google)

Here’s the chatter, of people searching for each show (or related topics like toys, merch, news, fic, art, etc). Same colors as above, for each show, for the same time period.

Unfortunately, Castlevania drowns everyone else out by such a degree that we can’t really see much until we get that out of the way. So this second one, I narrowed it down to ‘Castlevania netflix’ to temporarily quiet it, a little.

Compare this to the viewership, and you can see some interesting behaviors. People talked about TH a lot more than VLD, despite TH having such lower viewership stats. There was a major spike when SPOP released its character designs, and kerfluffles get people talking. For VLD, its S3 viewership dropped as in standard but the chatter went up; S3 and S7 came close to matching S1 levels of engagement (for not always good reasons, natch).

Notably, tDP may be somewhat quiet (comparatively) over on twitter, but it’s got people talking, too. If you’re wondering, the most common related search terms are for the cast overall, then ‘avatar the last airbender’ and then Ralya, Callum, Amaya, and Claudia. Going by frequency, Rayla is the most popular character by a large margin.

The dotted line in green, at the far right, is Google’s prediction based on the past few days’ traffic, as we haven’t quite completed the first week. (A query for a year+ gets compressed to a weekly Sun-Sat view.)

Speaking of which, let’s take it down to just the past 90 days, and remove the narrowing filter on Castlevania. This graph has a bumpier view because it’s back to a daily value for each.

tDP and SPOP look very close, and there’s really only a few points difference: tDP maxed out at 43%; SPOP maxed at 37%. (Basically, take Castlevania’s highest-rated day as x, and tDP’s highpoint is 43% of x.) If I narrow Castlevania down again, we can see tDP vs SPOP chatter.

People are talking about SPOP but still not quite to the degree of engagement as tDP. Then again, SPOP also hamstrung itself by releasing three days early without a lot of warning, so it’s possible we may see another spike similar to tDP’s once word gets out that the series is actually released. Or, once early adopters create buzz and lure more people into watching.

bottom line

What people talk about isn’t always what they’re watching. And people will watch and not have the place, time, or energy to chat about it online. All of these shows are on Netflix, too, so no advertising income as a comparison point. That makes engagement a more useful data point, because the income doesn’t change based on viewership.

By that measure, TH is probably DW’s most successful series of these, followed by VLD, and then SPOP. TH is the only one inside shouting distance of what tDP managed it its first season, and none of them come close to competing with Castlevania’s numbers.

Hell, if I were DW, right now I might be having serious regrets of making VLD a Y7 property, considering Castlevania’s M rating. By platform and viewership, Netflix might be the best home for adult-oriented series where stories can explore darker themes. Of all the franchises DW has right now, VLD was possibly the best candidate for taking advantage of the platform. That M rating hasn’t hurt Castlevania in the least, and in fact may’ve been part of what propelled it so high.

#vld #voltron #castlevania #the dragon prince #she-ra #trollhunters #doing the data cronch #sol thinks about stuff

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riichardwilson · 5 years ago

Text

How to use machine learning (if you can’t code) to help your keyword research

I have previously written about why keyword research isn’t dead. A key theme I continually make is that keyword categorization is incredibly important in order to be useful so that you can optimize towards topics and clusters rather than individual keywords.

My keyword research documents often exceed 20k-50k keywords which are normally broken into two, three or sometimes more categories reflective of the site taxonomy in question.

As you can see, I have categorized the keywords into 4, filterable, columns allowing you to select a certain “topic” and view the collective search volume for a cohort of keywords. What you can’t see is that there are over 8k keywords.

A few years ago I used to categorize this fairly manually, using some simple formulas where I could. Took ages. So I made a keyword categorization tool to help me. It’s built using php and still pretty rudimentary but has sped the time I am able to do keyword research and categorize it from a couple of days to 12-15 hours depending on how many keywords there are.

I’m a sucker for a trend. So the minute all the SEO Companys started shouting about how great Python is, of course I am on the bandwagon. My goal is to streamline the keyword research process even further and I’m loving learning such an adaptable language. But then I came across this video by David Sottimano where he introduced BigML into my life. Imagine an online “drag and drop” machine learning service; a system literally anyone can use. This is BigML.

I am still pursuing my ultimate goal of mastering Python, but in the meantime, BigML has provided me with some very interesting insights that have already sped up my keyword categorization. The aim of this article is to give you some ideas about leveraging (free) technologies already out there to work smarter.

A quick note before we delve in, BigML is a freemium tool. There is a monthly fee if you want to crunch a lot of data or want added features (like more than one person on the account at one time). However, to achieve the results in this article, the free tier will be more than enough. In fact, unless you’re a serious data scientist and need to analyze a LOT of variables, the free tier will always be enough for you.

Step 1 – Getting the training data

For this example, we’ll pretend we’re doing keyword research for River Island – a large clothing retailer in the UK for all my friends across the pond. (If you’re reading this and work for River Island, I will not be doing full keyword research.)

If we look at River Island’s site taxonomy we see the following:

For the purpose of this guide, we’ll just do keyword research for men and focus on these few product items:

Let’s say, hypothetically, I want to group my keywords into the following categories and subcategories:

Tops > Coats and Jackets

> T-Shirts and vests

Bottoms > Jeans

> Trousers and Chinos

We’ll do the “Bottoms” first.

Grab the “jeans” URL for River Island and plug it into SEMRush:

Filter by the top 20 keywords and export:

I’ve chosen the top 20 because often, beyond that, you start to rank for some irrelevant and, sometimes, quite odd keywords. Yes, River Island ranks number 58 for this term:

We don’t want these terms affecting our training model.

For “jeans”, when we filter for keywords in positions 1-20 and export, we get 900 odd keywords. Drop them into a spreadsheet and add the headings “category 1” and “category 2”. You’ll then drop “bottoms” into category 1 and “jeans” into category 2 and fill down:

This is the start of your machine learning “training data”. There’s probably enough data here already, but I like to be thorough so I’m also going to grab all the keywords from a company I know ranks highly for every clothing based keyword – ASOS.

I’m going to repeat the process for their jeans page:

After I’ve exported the resulting ranking keywords from SEMRush, added them to my spreadsheet, dropped the categories down and de-duped the list I’ve got 1,300 keywords for Bottoms > Jeans.

I’m going to repeat the process for:

Bottoms > Trousers and Chinos

Tops > Coats and Jackets

Tops > T-Shirts and Vests

For these 3, I didn’t bother putting the River Island domain into SEMRush as ASOS ranked for so many keywords there will be enough data for my training model.

After a quick find and replace to get rid of branded keywords:

And a de-duplication, I’m left with nearly 8,000 keywords that are categorized into “Bottoms” and “Tops” at the first level, and “Jeans” and “Trousers/Chinos” at a secondary level.

Tip – you may need to use the trim function to get rid of any whitespace after the find and replace as otherwise this sheet will upload with errors when we use it as our training data:

Time spent so far: 5 minutes

You’d of course carry on doing this for all River Islands products and into as many categories as required. If you were doing men’s and women’s, they’d likely be the first category. You’d then possibly have a fourth category which breaks things like “jackets” up further into items like “puffer jackets” and “leather jackets”.

If you’re struggling to visualize the categories you may need, I will shortly be writing a post on that too. Sometimes it’s just common sense, but there is also a machine learning program to help with that too if you need it:

Step 2 – Training your machine learning model

Cool – we have our list of 8,000 unbranded keywords that have been categorized in 5 minutes.

Save the file as a CSV and then head to BigML and get registered. It’s free.

Now we’ll go through the following, incredibly simple steps, to train the machine learning program in categorizing keywords.

Head to the sources tab and upload your training data:

Once it’s loaded, click the file to open up the settings:

Click the “configure data source” and ensure the categories are set to “categorical”:

In most instances, the rest of the settings should be fine. If you’d like to learn more about what all the settings do, I’d recommend you watch BigML’s educational youtube channel here.

Close the “configure source” settings and click the “configure data set” button. Then deselect “category 2”:

Click the “create dataset” button:

Although, before you do, rename the “dataset name” to something like ML Blog Data (Category 1).

Select your new data set in the “data sets” tab:

It’s now “tokenized” all your keywords. From here there are so many exciting models you can train, but for the purposes of this article we’ll be doing the most simple. Navigate to the “one-click supervised model”:

After it’s finished computing, you’ll see a decision tree like this:

Again, I’m not going to go into everything you can do with this, but what it’s essentially done is created a series of if statements based on the data you’ve given it which it will use to work out the probability of a category.

For example, the circle I’ve hovered over in the image is a decision path with the following attributes – if the keyword does not contain “jeans” or “trousers”, it’s likely to be a “top” with a confidence score of 85.71%.

You can actually create something called an “ensemble model” which will be even more accurate. You’re also able to split the data and run a controlled test on it so you can see how accurate it’s going to be before you use it. If you’d like to learn more on this, reach out to me or read the documentation on the site.

So, we’ve created a model for categorizing the keywords in category one. We now need to do the same for the second category.

Head back to your sources and select your training dataset again:

Repeat the steps above, but this time deselect “category 1” when you are configuring your dataset:

As with before, create a one-click supervised model:

Voila – your second decision tree:

So now we have 2 trained models that will categorize your keywords using machine learning with a fairly high degree of accuracy.

Time spent so far: 10 minutes (maybe an hour if you did every product category on River Islands website)

Getting the rest of your keywords

We only trained a model to cover 2 categories and 4 subcategories. Assuming you trained it for every product on the River Island’s website (which will likely take you an hour or two max. Maybe even get a Virtual Assistant to do it for you and put your feet up), the rest of your keyword research is going to be so easy.

All I’m going to do now is plug the following competitor domains into SEMRush at domain level and export their whole site’s ranking keywords (to clarify, I’m not going to be going into each product folder as I did with the training data):

https://www.superdry.com/ https://www.topman.com/ https://www.ralphlauren.co.uk/ https://www.burton.co.uk/

And I could keep going.

After I’ve deduped all the keywords on these sites and got rid of branded keywords I’m left with around 100k, uncategorized keywords.

I may also employ some standard keyword research techniques such as using merge words and keyword planner or Ahrefs keyword explorer to get even more keyword suggestions. The beauty is, we don’t have to spend ages making sure the keywords we are exporting are being categorized correctly. We can literally just plug in domains and seed keywords and export.

You’re then going to dump this huge, ugly, uncategorized list into Google sheets:

Time spent so far: 25 minutes (or an hour and 25 minutes if you got every product category from River Islands website)

Using BigML’s API to categorize your keywords

Get the BigML addon on Google sheets:

You’ll need to pop your username and API key in, but you’ll find these easily within your BigML dashboard and settings.

Now the fun begins.

Highlight the array that needs to be categorized and select the model you trained that you want to use. In this instance I am using category 1 (at the moment I think we can only do one category at a time. I haven’t worked out how to both which is why we trained two different models):

Then, click “predict” and let it go:

It may take a while depending on how many keywords you have, but at least you can get on with some other tasks. You’ll notice it also gives a probability score. I tend to just filter for anything less than 50% and delete them. I’ve got 100,000 keywords, I won’t miss the odd few.

Next, we make a copy of the sheet, delete the two columns, and do exactly the same thing for category 2:

Once we have both categorizations and have deleted keywords that have a low “confidence score”, you’ll just need to clear the formatting and then run a vlookup to pull them together:

Run for as many categories as you need, and then pull in any other important data for your finalized keyword research document:

Some final notes

So there we have it – an easy way to categorize 100k keywords in less than a few hours actual working time (by that I mean you’ll have to wait for the ML to go through the keywords one by one, but you won’t be working).

I haven’t found a way to do both at the same time yet, but I imagine there is a way to do it.

The model we used is not as accurate as some of the other options in the engine. For example, using an ensemble model would yield better results, especially if the training model was smaller, but it’s slightly more complicated to configure.

You can also use the engine to discover categories and closely related topics. But that’s for another post.

It’s quite basic, but surprisingly powerful and a really nice introduction to machine learning. Have fun!

Opinions expressed in this article are those of the guest author and not necessarily Search Engine Land. Staff authors are listed here.

About The Author

Andy Chadwick is a digital marketing agency consultant, specialising in SEO Company but also covering PPC services with his company digitalquokka. He is primarily known for his unique approach to keyword research, having developed his own tools to help with the keyword categorization process. Andy started teaching himself SEO Company in 2013 when he co-founded a company that went on to net over £2.5 million in its third year. Since leaving the company in 2018 he has consulted and helped other start-ups, as well as international organizations with their digital marketing agency strategies.

Website Design & SEO Delray Beach by DBL07.co

Delray Beach SEO

source http://www.scpie.org/how-to-use-machine-learning-if-you-cant-code-to-help-your-keyword-research/ source https://scpie.tumblr.com/post/611314387316244480

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scpie · 5 years ago

Text

How to use machine learning (if you can’t code) to help your keyword research

My keyword research documents often exceed 20k-50k keywords which are normally broken into two, three or sometimes more categories reflective of the site taxonomy in question.

Step 1 – Getting the training data

If we look at River Island’s site taxonomy we see the following:

For the purpose of this guide, we’ll just do keyword research for men and focus on these few product items:

Let’s say, hypothetically, I want to group my keywords into the following categories and subcategories:

Tops > Coats and Jackets

> T-Shirts and vests

Bottoms > Jeans

> Trousers and Chinos

We’ll do the “Bottoms” first.

Grab the “jeans” URL for River Island and plug it into SEMRush:

Filter by the top 20 keywords and export:

I’ve chosen the top 20 because often, beyond that, you start to rank for some irrelevant and, sometimes, quite odd keywords. Yes, River Island ranks number 58 for this term:

We don’t want these terms affecting our training model.

I’m going to repeat the process for their jeans page:

After I’ve exported the resulting ranking keywords from SEMRush, added them to my spreadsheet, dropped the categories down and de-duped the list I’ve got 1,300 keywords for Bottoms > Jeans.

I’m going to repeat the process for:

Bottoms > Trousers and Chinos

Tops > Coats and Jackets

Tops > T-Shirts and Vests

For these 3, I didn’t bother putting the River Island domain into SEMRush as ASOS ranked for so many keywords there will be enough data for my training model.

After a quick find and replace to get rid of branded keywords:

And a de-duplication, I’m left with nearly 8,000 keywords that are categorized into “Bottoms” and “Tops” at the first level, and “Jeans” and “Trousers/Chinos” at a secondary level.

Tip – you may need to use the trim function to get rid of any whitespace after the find and replace as otherwise this sheet will upload with errors when we use it as our training data:

Time spent so far: 5 minutes

Step 2 – Training your machine learning model

Cool – we have our list of 8,000 unbranded keywords that have been categorized in 5 minutes.

Save the file as a CSV and then head to BigML and get registered. It’s free.

Now we’ll go through the following, incredibly simple steps, to train the machine learning program in categorizing keywords.

Head to the sources tab and upload your training data:

Once it’s loaded, click the file to open up the settings:

Click the “configure data source” and ensure the categories are set to “categorical”:

In most instances, the rest of the settings should be fine. If you’d like to learn more about what all the settings do, I’d recommend you watch BigML’s educational youtube channel here.

Close the “configure source” settings and click the “configure data set” button. Then deselect “category 2”:

Click the “create dataset” button:

Although, before you do, rename the “dataset name” to something like ML Blog Data (Category 1).

Select your new data set in the “data sets” tab:

After it’s finished computing, you’ll see a decision tree like this:

So, we’ve created a model for categorizing the keywords in category one. We now need to do the same for the second category.

Head back to your sources and select your training dataset again:

Repeat the steps above, but this time deselect “category 1” when you are configuring your dataset:

As with before, create a one-click supervised model:

Voila – your second decision tree:

So now we have 2 trained models that will categorize your keywords using machine learning with a fairly high degree of accuracy.

Time spent so far: 10 minutes (maybe an hour if you did every product category on River Islands website)

Getting the rest of your keywords

https://www.superdry.com/ https://www.topman.com/ https://www.ralphlauren.co.uk/ https://www.burton.co.uk/

And I could keep going.

After I’ve deduped all the keywords on these sites and got rid of branded keywords I’m left with around 100k, uncategorized keywords.

You’re then going to dump this huge, ugly, uncategorized list into Google sheets:

Time spent so far: 25 minutes (or an hour and 25 minutes if you got every product category from River Islands website)

Using BigML’s API to categorize your keywords

Get the BigML addon on Google sheets:

You’ll need to pop your username and API key in, but you’ll find these easily within your BigML dashboard and settings.

Now the fun begins.

Then, click “predict” and let it go:

Next, we make a copy of the sheet, delete the two columns, and do exactly the same thing for category 2:

Once we have both categorizations and have deleted keywords that have a low “confidence score”, you’ll just need to clear the formatting and then run a vlookup to pull them together:

Run for as many categories as you need, and then pull in any other important data for your finalized keyword research document:

Some final notes

I haven’t found a way to do both at the same time yet, but I imagine there is a way to do it.

You can also use the engine to discover categories and closely related topics. But that’s for another post.

It’s quite basic, but surprisingly powerful and a really nice introduction to machine learning. Have fun!

Opinions expressed in this article are those of the guest author and not necessarily Search Engine Land. Staff authors are listed here.

About The Author

Website Design & SEO Delray Beach by DBL07.co

Delray Beach SEO

source http://www.scpie.org/how-to-use-machine-learning-if-you-cant-code-to-help-your-keyword-research/

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