[UPDATE: added 8 more lists – AiPT, Broken Frontier, ComFor (German), Comic.de (German, multiple mentions only), Comicgate (German, unranked), Diamond via The Beat (comics + GNs), Tor Online (German). Arrows next to entries indicate that their rank went up or down compared to the previous version.]
Once more I compiled a little ‘master list’ out of some best-of-2019 lists on the Internet. Each title was assigned between 1 and 30 points, depending on either its rank, or on the number of titles in an unranked list (full explanation here).
THE TOP 25 COMICS OF 2019:
- House of X / Powers of X by Jonathan Hickman, Pepe Larraz and R.B. Silva (207 points)
- Laura Dean Keeps Breaking Up With Me by Mariko Tamaki and Rosemary Valero-O’Connell (171) ⇩
- Die by Kieron Gillen and Stephanie Hans (120) ⇧
- Rusty Brown by Chris Ware (110)
- The Immortal Hulk by Al Ewing and Joe Bennett (106) ⇧
- They Called Us Enemy by George Takei et al. (102) ⇩
- Clyde Fans by Seth ⇩, tied with
Daredevil by Chip Zdarsky and Marco Checchetto ⇧ (95)
- Superman’s Pal Jimmy Olsen by Matt Fraction and Steve Lieber (92) ⇩
- The Hard Tomorrow by Eleanor Davis (88) ⇩
- Mister Miracle by Tom King and Mitch Gerads (87) ⇧
- Spider-Man: Life Story by Chip Zdarsky and Mark Bagley ⇧, tied with
The Walking Dead by Robert Kirkman and Charlie Adlard ⇧ (82)
- These Savage Shores by Ram V and Sumit Kumar (79) ⇧
- Harley Quinn: Breaking Glass by Mariko Tamaki and Steve Pugh (75) ⇩
- When I Arrived at the Castle by Emily Carroll (74) ⇧
- Witch Hat Atelier by Kamome Shirahama (70) ⇩
- The Handmaid’s Tale by Margaret Atwood and Renée Nault (66) ⇧
- Hot Comb by Ebony Flowers (61) ⇩
- DCeased by Tom Taylor and Trevor Hairsine (60) ⇧
- Bitter Root by David Walker, Chuck Brown and Sanford Greene (59) ⇩
- Good Talk by Mira Jacob ⇩, tied with
George Herriman’s Krazy Kat. The Complete Color Sundays 1935–1944 ⇧ (57)
- Demon Slayer: Kimetsu no Yaiba by Koyoharu Gotōge ⇩, tied with
Sabrina by Nick Drnaso ⇧ (55)
Given the usual dominance of Anglo-American list sources, it is almost a pleasant surprise to see as many as two manga within the top 25. As for European comics… Alice Oseman is British, does that count? [Update: Oseman’s Heartstopper dropped out of the top 25 to 28th place. It’s still the highest-ranking European comic.]
The following lists were evaluated: A.V. Club, Adventures in Poor Taste, Book Riot, Broken Frontier, CBC, Chicago Public Library, ComFor (German), Comic.de (German, multiple mentions only), Comicgate (German, unranked), Comickunst (German), Diamond via The Beat (comics + GNs), Entertainment Weekly, Forbes, GameSpot, Goodreads, Gosh (adult, kids), The Guardian (Rachel Cooke, James Smart), io9, Kono Manga ga Sugoi! via Anime News Network, Oricon Top-Selling Manga in Japan by Series via Anime News Network, Paste, Publishers Weekly Critics Poll, Readings, School Library Journal, Spiegel Online (German), SyFy Wire (Best New Comic Books, Fangrrl), Tagesspiegel (German), Tor Online (German), What Culture, YALSA.
Multivariate statistics: how to measure similarity between comics (or anything, really) based on several characteristicsPosted: December 18, 2019
In recent blogposts about stylometry (e.g. here), I skipped a bit of maths that, in hindsight, might be worth talking about. As it turns out, it’s actually both highly useful and easy to understand.
The examples used here are going to be the same as in the aforementioned post, i.e. 2 scenes from Katsuhiro Ōtomo’s Akira (vol. 5, p. 16 ff, which we’ll call A1, and vol. 3, p. 125 ff, which we’ll call A2) and 2 manga chapters from the October 11, 2018 issue of Morning magazine, Miko Yasu’s Hakozume (M1) and Rito Asami’s Ichikei no karasu (M2).
Let’s say you want to compare these 4 comics based on 1 variable, e.g. the frequency of the hiragana character で de. (Which is not the most realistic stylometric indicator, but it will make more and more sense with an increasing number of variables.) Nothing easier than that. First, here are the numbers of で de per 100 hiragana for each text:
- A1: 8
- A2: 3
- M1: 6
- M2: 7
By simply subtracting the numbers from each other, we get the difference between any pair of manga and thus their similarity. Ranked from smallest difference to largest, these would be:
- A1/M2: 1
- M1/M2: 1
- A1/M1: 2
- A2/M1: 3
- A2/M2: 4
- A1/A2: 5
So the two Morning manga and one of the Akira scenes can be said to be similar, while the other Akira scene is the odd one out.
With 2 variables, it gets more interesting. Let’s assume you decide that the similarity of these manga is best based on their use of the hiragana で de and い i. The frequencies for the latter are:
- A1: 7
- A2: 8
- M1: 3
- M2: 2
On a side note, at this point it might be a good idea to think about normalisation: are the numbers of the two variables comparable, so that a difference of e.g. “2” carries the same weight for both characteristics? In our example, this is not a problem because we’re dealing with two hiragana frequencies measured on the same scale, but if your two variables are e.g. the total number of kana characters per chapter and the shoe size of the author, the former will probably have much more impact on the similarity scores than the latter, because the range of numbers is wider – unless you adjust the scale of the variables. Except if this different impact was precisely what you wanted.
To calculate the distance between any two of these points (i.e. the similarity of two manga), you’ll probably want to use Pythagoras and his a² + b² = c² formula, a.k.a. the Euclidean distance, with ‘a’ and ‘b’ representing the horizontal and vertical distances and ‘c’ being the diagonal line we’re looking for. There’s nothing wrong with that, but it might suprise you that in actual statistics and stylometrics, there are several other ways of measuring this distance. However, we’re going to stick with good old Pythagoras here.
The distance between A1 (で de: 8 / い i: 7) and A2 (3/8), for instance, would be the square root of the sum of (8-3)² and (7-8)², which is approximately 5.1. All distances, ranked from lowest to highest, would be (rounded to one decimal):
- M1/M2: 1.4
- A1/M1: 4.5
- A1/A2: 5.1
- A1/M2: 5.1
- A2/M1: 5.8
- A2/M2: 7.2
Now the two Akira excerpts appear to be more similar than before when the similarity was only based on the frequency of で de, and the similarity between the two Morning manga is greater than that between the first Akira excerpt and either of the two Morning manga.
Just as you imagine two points in 2-dimensional space forming two corners of a right-angled triangle (see above), in 3-dimensional space you have to image a rectangular cuboid – a ‘box’ (see the illustration on Wikipedia). Apparently, how to calculate the distance between the two opposite corner points of a cuboid is something you learn in high school, but I couldn’t remember and had to look it up. The formula for distance ‘d’ is: d² = a² + b² + c².
As our third variable, we’re going to use the frequency of the hiragana し shi. In the following list, the number of し shi per 100 hiragana is added as the third coordinate to each manga:
- A1 (8/7/7)
- A2 (3/8/1)
- M1 (6/3/1)
- M2 (7/2/5)
For instance, the distance between A1 and A2 is the square root of: (8-3)² + (7-8)² + (7-1)², i.e. roughly 7.9. Here are all the distances:
- M1/M2: 4.2
- A1/M2: 5.5
- A2/M1: 5.8
- A1/M1: 7.5
- A1/A2: 7.9
- A2/M2: 8.2
As we can see, the main difference between this similarity ranking and the previous one is that the similarity between the two Akira scenes has become smaller.
You might have guessed it by now: even though it gets harder to imagine (and even more so to illustrate) a space of more than 3 dimensions, we can apply more or less the same formula regardless of the number of variables. We only need to add a new summand/addend for each new variable. For 4 variables, the distance between two points would be the square root of (a² + b² + c² + d²). These are the distances if we add the hiragana て te (which occurs 7 times per 100 hiragana in A1, 2 times in A2, 6 in M1, 4 in M2) as the 4th dimension:
- M1/M2: 4.7
- A1/M2: 6.2
- A2/M1: 7.1
- A1/M1: 7.5
- A2/M2: 8.5
- A1/A2: 9.3
Note how the changes become smaller now – apart from the last two pairs having swapped places, the similarity ranking is the same as before.
So how about 25 hiragana frequencies? This is more than half of all the different hiragana in our (100-hiragana samples of the) four manga. I added 21 random hiragana (see the graph) to the 4 from the previous section, and these are the resulting distances:
- A1/M2: 9.7
- A2/M1: 11.0
- A1/A2: 12.5
- M1/M2: 13.0
- A2/M2: 13.3
- A1/M1: 14.7
Who would have thought that? Now it looks as if the ‘scientists’ scene from Akira (A1) is similar to Ichikei no karasu (M2), and the ‘insurgent thugs’ scene from Akira (A2) is similar to Hakozume (M1). Which is what we suspected all along. So who knows, maybe we can do away with all this maths stuff after all? However, the usual caveat applies: proper stylometry should really be based on larger samples than 100 characters per text.
I’m conducting a short poll on manga readership outside of Japan (primarily in English-speaking countries) before 1994. If you have read any manga back then, please take a minute (or five, but it probably won’t take longer) to participate: https://forms.gle/UFmaXR35mrBxPE97A
Please note that there is a German version with different reply options; residents of German-speaking countries who have read manga before 1997 are asked to use this one: https://forms.gle/syHfF1Ew1CukdXAy7
The poll closes on December 15, 2019.
Only one manga this time, but it’s a long one…
Language: English (translated from Japanese)
Author: Osamu Tezuka
Publisher: Vertical (originally Shōgakukan / Akita Shoten)
Year: 2012 (original run 1967-1969)
Number of volumes: 1
Price: US-$ 24.95
The character named Dororo is actually only the sidekick of the real protagonist, Hyakkimaru. In medieval Japan, Lord Daigo strikes a deal with 48 demons: in exchange for one body part of his unborn child for each of the demons, Daigo wants the power to become ruler of all of Japan. And indeed, when Daigo’s son Hyakkimaru is born, he has “no arms or legs, nor eyes or ears, but holes in the face where the eyes, nose and mouth should have been” (p. 60). Daigo and his wife abandon Hyakkimaru, but he is found by a doctor who raises him.
The doctor equips Hyakkimaru with artificial limbs that work just as fine as natural ones – if not better, for when teenage Hyakkimaru sets out to leave his foster father to travel the world, the doctor upgrades the prostheses with gimmicks such as hidden blades, acid jets, and explosives. Furthermore, Hyakkimaru has somehow developed the supernatural ability to communicate telepathically – actively and passively across any distance – as well as read people’s minds. And despite having glass eyes, he can ‘sense’ his surroundings and even detect demons that are invisible to other people. One can easily see the ‘Daredevil problem’ at work here – a disability that doesn’t affect the character at all.
Still, Hyakkimaru is bothered about his condition. “I can’t see, hear, speak, or smell, and lack arms and legs… nothing works” (p. 94). So in order to change that, he becomes a demon slayer, for with each demon he kills he regains a body part. Luckily for him, he only needs half a page (p. 98) of training to become the deadliest swordfighter alive, effortlessly defeating any human opponent (and most non-human ones, for that matter) he encounters. In a way, this is even more boring than shōnen manga nowadays, in which there is at least some development – in One Piece and what have you, the enemies become stronger and stronger, and so does the hero. In Dororo, the hero becomes weaker, if at all.
Thankfully, however, Dororo doesn’t fall into the ‘monster of the week’ trap. There are standalone episodes in which Hyakkimaru and Dororo enter a village where strange things are happening, then they find the demon that’s behind it all, which they then defeat. Most episodes advance an overarching plot though, which eventually reunites Hyakkimaru with his biological parents, and you can bet that this is an awkward meeting.
Despite all this drama and mystery, Dororo is rather light-hearted in tone with lots of visual and textual gags (some of which probably get lost in translation, but the Vertical edition does a good job by providing explanatory footnotes at some points). Published shortly before Kirihito, Dororo is still – expertly – drawn in Tezuka’s idiosyncratic cartoonish style in which all male characters have big legs and no nipples etc., and this style is well suited for a humorous manga. Which isn’t to say that Dororo is kids’ stuff; there is a lot of blood and death shown here.
This is where Dororo excels. It is a no-holds-barred depiction of a grim Japanese ‘Dark Age’ in which samurai mercilessly exploit their peasant serfs and sometimes kill them without a second thought. The peasants are often not much better though: each time Hyakkimaru and Dororo rescue a village from a demon, the villagers chase them away as outcasts and freaks. Rather than giving an accurate account of a historical period, Tezuka gives a powerful reflection about human nature that transcends time and space.
In the end, Dororo is perhaps a typical manga of its time that tries to be many different things and to appeal to many different audiences at once. From the perspective of today, in which we’re used to having our manga genres neatly compartmentalised, such a humor/action/supernatural/drama/history hybrid might be hard to stomach.
Scariest moment: the horror in Dororo is not based on shock but rather on disgust. The countless demons come in all sorts of horrid shapes, some of which are contrasted with disguises as beautiful women. The most hideous of them might be the one in the ‘Bandai’ chapter (pp. 143-176).
Rating: ● ● ○ ○ ○
For Japan, the 2010s were marked by a historic event at the beginning of the decade: the Tōhoku earthquake and tsunami on March 11, 2011, and the ensuing nuclear accident at the Fukushima Daiichi power plant. It’s somewhat surprising that there haven’t been many more manga on this topic, although I bet a lot of manga critics are going to interpret pretty much any manga published afterwards as somehow inspired by the triple disaster, just as they did with the Hiroshima nuclear bombing. Apart from 1F, the other big ‘3.11’ manga is Daisy, created in 2012 but not published in German until 2016 (and not yet available in English as far as I know).
Daisy (デイジー ~3.11女子高生たちの選択~ / Daisy – 3.11 Joshikōseitachi no Sentaku)
Language: German (translated from Japanese)
Author: Reiko Momochi; based on a novel by Teruhiro Kobayashi, Darai Kusanagi, and Tomoji Nobuta
Publisher: Egmont (originally Kōdansha)
Year: 2016 (originally 2013)
Number of volumes: 1
Price: € 14
Website: https://www.egmont-manga.de/buch/daisy-aus-fukushima/ (German), https://www.mangaupdates.com/series.html?id=87087 (Baka-Updates)
On the one hand, Daisy – full title in German: Daisy aus Fukushima (“Daisy from Fukushima”) – is a typical shōjo manga about a group of friends in their last year of high school: Ayaka, Moe, Mayu, and narrator Fumi play in a band, fall in love with boys, worry about which career to pursue after graduation, quarrel and reconcile again. On the other hand, they live in Fukushima-shi (Fukushima City), and after that fateful 11th March their lives are affected in many ways.
Even though Fukushima-shi is well outside of the evacuation zone, radioactivity has become a constant threat. It keeps guests from staying at Ayaka’s parents’ hotel, it deters customers from buying rice from Mayu’s father’s farm, and it makes Moe abandon her home town. Before the disaster, Fumi’s plan had been to go away to Tokyo to university, but now she wonders if leaving Fukushima at this time would make her a traitor.
It’s quite a feat of this manga to make this peculiar feeling palpable; these effects of the disaster that are much more subtle than radiation poisoning; this creeping fear of an invisible danger that is so unlike the blind panic of people running from a tidal wave. Daisy is similar to 1F in this regard: they both don’t show how the tsunami hits the coast or how reactors explode, and both focus on characters from outside of the evacuation zone – the main difference, of course, being that the ones in Daisy are fictional.
Reiko Momochi, who is perhaps best known for her similarly serious shōjo manga series Confidential Confessions (Mondai teiki sakuhinshū), provides solid artwork in which particularly character close-ups excel with discreet shading lines and screen tones.
When talking about the manga of the 2010s, Daisy is definitely one to rank among the most representative of this decade.
Rating: ● ● ● ● ○
Akira Code 7 Alert is an unofficial animated short film by Richard Nyst that went online on YouTube two weeks ago. I hesitate to call it a ‘fan film’ because it looks so professional. The interesting thing about it is that it focuses on characters from the Akira manga that didn’t make it into the anime: the caretaker robots, also known as ‘Security Balls’, which the military employs for riot control. (They are quite relevant though if one reads Akira as a cyberpunk manga, as I have argued elsewhere.) In animation, they are reminiscent of the Tachikoma in the Ghost in the Shell: Stand Alone Complex anime series. Or maybe the other way round: you can see that Masamune Shirow most likely got the inspiration for the Fuchikoma in his Ghost in the Shell manga from Katsuhiro Ōtomo’s Akira manga.
Disclosure: I’m credited as “Japanese script advisor” in the film.
As with Tardi, the Joann Sfar exhibition does a good job of showcasing the artist’s vast body of work. There are many original inked pages on display, mostly of Le chat du rabbin but also of lesser known comics such as L’Ancien Temps or Aspirine, as well as his watercolours for La Fontaine’s Fables, oil paintings in connection with his Je l’appelle monsieur Bonnard project, excerpts from his live-action film Gainsbourg, lots of one-panel cartoons (with German translations provided this time) and much more.
It is perhaps easier to say what we don’t get to see here, and there are two surprising omissions: one is Professeur Bell, a series of no less than 5 albums (the last three of which have been drawn by Hervé Tanquerelle). There are only some reading copies provided in the museum library, but no original art. The other omission, which I find more severe because it was my introduction to Sfar, is Donjon. Of course, Sfar only drew very few Donjon albums himself and merely co-wrote others. But it would have been interesting if the show had shed some light on the process of the writing collaboration between Sfar and Lewis Trondheim. In Basel, only a few Donjon album copies are (mis)placed in some kind of children’s section for the visitor to read, next to Petit Vampire…
Another question one might ask is: are black-and-white ink drawings really representative of Sfar’s art? Can you talk about Sfar’s comics without mentioning Brigitte Findakly, who coloured most of them? When you think of e.g. Le chat du rabbin, you probably think of the grey cat with its large yellow-green eyes, the brown-skinned daughter of the rabbi and her colourful dresses, the light blue sky over Algiers… At least some side-by-side comparisons of inked and coloured pages would have been a sensible addition to this exhibition.
The Flesch reading-ease score (FRES, also called FRE – ‘Flesch Reading Ease’) is still a popular measurement for the readability of texts, despite some criticism and suggestions for improvement since it was first proposed by Rudolf Flesch in 1948. (I’ve never read his original paper, though; all my information is taken from Wikipedia.) On a scale from 0 to 100, it indicates how difficult it is to understand a given text based on sentence length and word length, with a low score meaning difficult to read and a high score meaning easy to read.
Sentence length and word length are also popular factors in stylometry, the idea here being that some authors (or, generally speaking, kinds of text) prefer longer sentences and/or words while others prefer shorter ones. Thus such scores based on sentence length and word length might serve as an indicator of how similar two given texts are. In fact, FRES is used in actual stylometry, albeit only as one factor among many (e.g. in Brennan, Afroz and Greenstadt 2012 (PDF)). Over other stylometric indicators, FRES would have the added benefit that it actually says something in itself about the text, rather than being merely a number that only means something in relation to another.
The original FRES formula was developed for English and has been modified for other languages. In the last few stylometry blogposts here, the examples were taken from Japanese manga, but FRES is not well suited for Japanese. The main reason is that syllables don’t play much of a role in Japanese readability. More important factors are the number of characters and the ratio of kanji, as the number of syllables per character varies. A two-kanji compound, for instance, can have fewer syllables than a single-kanji word (e.g. 部長 bu‧chō ‘head of department’ vs. 力 chi‧ka‧ra ‘power’). Therefore, we’re going to use our old English-language X-Men examples from 2017 again.
The comics in question are: Astonishing X-Men #1 (1995) written by Scott Lobdell, Ultimate X-Men #1 (2001) written by Mark Millar, and Civil War: X-Men #1 (2006) written by David Hine. Looking at just the opening sequence of each comic (see the previous X-Men post for some images), we get the following sentence / word / syllable counts:
- AXM: 3 sentences, 68 words, 100 syllables.
- UXM: 6 sentences, 82 words, 148 syllables.
- CW:XM: 7 sentences, 79 words, 114 syllables.
We don’t even need to use Flesch’s formula to get an idea of the readability differences: the sentences in AXM are really long and those in CW:XM are much shorter. As for word length, UXM stands out with rather long words such as “unconstitutional”, which is reflected in the high ratio of syllables per word.
Applying the formula (cf. Wikipedia), we get the following FRESs:
- AXM: 59.4
- UXM: 40.3
- CW:XM: 73.3
Who would have thought that! It looks like UXM (or at least the selected portion) is harder to read than AXM – a FRES of 40.3 is already ‘College’ level according to Flesch’s table.
But how do these numbers help us if we’re interested in stylometric similarity? All three texts are written by different writers. So far we could only say (again – based on a insufficiently sized sample) that Hine’s writing style is closer to Lobdell’s than to Millar’s. The ultimate test for a stylometric indicator would be to take an additional example text that is written by one of the three authors, and see if its FRES is close to the one from the same author’s X-Men text.
Our 4th example will be the rather randomly selected Nemesis by Millar (2010, art by Steve McNiven) from which we’ll also take all text from the first few panels.
These are the numbers for the selected text fragment from Nemesis:
- 8 sentences, 68 words, 88 syllables.
- This translates to a FRES of 88.7!
In other words, Nemesis and UXM, the two comics written by Millar, appear to be the most dissimilar of the four! However, that was to be expected. Millar would be a poor writer if he always applied the same style to each character in each scene. And the two selected scenes are very different: a TV news report in UXM in contrast to a dialogue (or perhaps more like the typical villain’s monologue) in Nemesis.
Interestingly, there is a TV news report scene in Nemesis too (Part 3, p. 3). Wouldn’t that make for a more suitable comparison?
Here are the numbers for this TV scene which I’ll call N2:
- 4 sentences, 81 words, 146 syllables.
- FRES: 33.8
Now this looks more like Millar’s writing from UXM: the difference between the two scores is so small (6.5) that they can be said to be almost identical.
Still, we haven’t really proven anything yet. One possible interpretation of the scores is that the ~30-40 range is simply the usual range for this type of text, i.e. TV news reports. So perhaps these scores are not specific to Millar (or even to comics). One would have to look at similar scenes by Lobdell, Hine and/or other writers to verify that, and ideally also at real-world news transcripts.
On the other hand, one thing has worked well: two texts that we had intuitively identified as similar – UXM and N2 – indeed showed similar Flesch scores. That means FRES is not only a measurement of readability but also of stylometric similarity – albeit a rather crude one which is, as always, best used in combination with other metrics.
Now that the Reiwa era has begun, some people are compiling lists of the best manga from the Heisei era, even though 1989–2019 seems like a ridiculously long time to do so, and comparisons to the previous Shōwa era (1926–1989) are difficult due to their different lengths. However, towards the end of this year, lots of people are going to wonder what the best manga of the 2010s were, and then it will come in handy that we’ve taken an in-depth look at manga from the middle of this decade (technically speaking its 7th year) in this series of blogposts.
Wolf Girl & Black Prince (オオカミ少女と黒王子 / Ōkami shōjo to kuro ōji) vol. 11
Language: German (translated from Japanese)
Author: Ayuko Hatta
Publisher: Kazé (originally Shūeisha)
Year: 2016 (originally 2011)
Number of volumes: 16
Price: € 7
Website: https://www.kaze-online.de/Programm/Manga/Wolf-Girl-Black-Prince-Band-11.html (German), https://www.mangaupdates.com/series.html?id=66333 (Baka-Updates)
Even people who usually don’t read romance/shōjo stories seem to like this manga (and/or its anime adaptation). For some reason, though, apparently it has never been published in English. In 2016, the final two volumes came out in Japan, but in Germany, that year saw the publication of vols. 6-11, which is why I’ll deal with vol. 11 here.
Previously in Wolf Girl & Black Prince: in order to remain popular among her friends, 17-year old Erika pretends that her attractive classmate Kyōya is her boyfriend. She secretly begs him to play along so that her friends don’t find out that they’re not actually dating. He agrees to act as if they were a couple, but in private he is mean to her. In the end, however, they fall in love with each other and begin an actual relationship.
And that is the plot of about the first three volumes. The series could have ended there, but like with so many other long-running manga, the cash cow wasn’t dry yet. In the case of Wolf Girl & Black Prince, 13 more volumes followed which tell us of the romantic life of Erika and Kyōya, and of course their large cast of friends. In this eleventh volume, for instance, the first chapter is about Erika falling ill and Kyōya reluctantly caring for her, while the second and third chapters deal with romantic rivals (a co-worker at Erika’s job and a classmate who gets closer to Kyōya).
That isn’t to say that these ‘middle volumes’ are entirely without appeal. There are still moments in which Erika and Kyōya come across as compelling characters – she continues to be slightly selfish but also masochistic, he remains cool and distant. What really sets Wolf Girl & Black Prince apart from many other shōjo manga is its relatively mature content. For instance, the characters talk almost openly about sex (and also sometimes explicitly use that word), though sexual acts are never depicted.
One could probably say a lot about this manga from a gender perspective. The way in which Kyōya (“I’m going to steal your virginity!”) treats Erika, and the way in which Erika lets herself be treated by him, makes it clear that we’re not exactly reading a feminist manifesto here.
Another thing worth mentioning is that most volumes (at least in this Kazé edition) contain bonus stories. These can be spin-off stories from the main one, or unrelated one-shots. In the case of vol. 11, it’s a 38-page one-shot high school love story. On the flipside, though, this means that you only get 130 pages of the main story.
The artwork is of an extremely high quality and, in accordance with the humorous tone of this manga, is full of charming cartoonish characters. Too bad the story has lost its drive long ago and seems to go nowhere. Otherwise Wolf Girl & Black Prince would have indeed been one of the best manga of 2016.
Rating: ● ● ● ○ ○