Cyberpunk book chapter on Akira and Ghost in the Shell now available online

Two years ago, The Routledge Companion to Cyberpunk Culture was published, containing a short chapter by Lars Schmeink and me on the seminal anime films by Katsuhiro Ōtomo and Mamoru Oshii. Lars Schmeink has now put a pre-proof HTML version of that text on his website, and I have uploaded a post-print / accepted version (i.e. without the publisher’s layout) to Humanities Commons where you can read and download it free of charge. Now I can proudly say again that all my publications are available in Open Access.

Book review: Rémi Lopez, The Impact of Akira

Rémi Lopez: The Impact of Akira. A Manga [R]evolution. Translated by Jennifer Ligas. Toulouse: Third Éditions, 2020. 192 pages. ISBN: 2377842801. Print: $ 29.95, ebook: $ 13.99

When I first heard that there was going to be a book about Katsuhiro Ōtomo’s Akira, I was very excited and could hardly wait to read it – naturally, given that I had spent years studying this manga (and still am). Did it live up to my expectations? Find out in my review in the current issue of Asian Studies:

If my criticisms of this book seem overly harsh, bear in mind that I only tried to assess its value for a scholarly audience (for which it wasn’t even written). For other readers, it might still be an enjoyable book.

Another reason why I am pleased with this little review article is that it marks my first foray into a journal from the field of Japanese Studies or Asian Studies. I have always been bemoaning a certain divide, or at least a lack of communication, between manga scholars from Japanese Studies and comics scholars from other disciplines (like myself). Publishing in journals (or speaking at conferences) of the ‘other party’ might be small contributions to improving this situation.

A review copy of the ebook version was provided by Third Éditions.

Benedict Anderson’s Imagined Communities – in comics?

First published in 1983, Benedict Anderson’s book Imagined Communities. Reflections on the Origin and Spread of Nationalism remains tremendously influential in the Humanities today. In it, the nation is defined as “an imagined political community […]. It is imagined because the members of even the smallest nation will never know most of their fellow-members” (p. 6; all page numbers here refer to the 2016 revised edition by Verso). By using the word “imagined”, Anderson emphasises that national consciousness it not something pre-existing that only needs to be “awakened” – it needs to be actively created.

One of the instruments through which a nation can be created is what Anderson calls “print-capitalism”, a system within which e.g. newspapers forge a community out of their readers (pp. 35-36). This process is aided by “the fatality of human linguistic diversity” as readers felt “connected” to their “fellow-readers” due to their sharing the same “language-field”, regardless of their location on the globe (pp. 43-44). Furthermore, newspapers “brought together, on the same page” a variety of commercial, political and cultural news items of regional or local interest, which instilled in readers the feeling that all these things they read about were connected to each other and to the readers themselves, and thus “created an imagined community” (p. 62).

Language itself can facilitate the formation of nations, particularly when the vernacular language in which people speak and write differs from the official language-of-state, as was the case in the various nations of the Austro-Hungarian Empire in the 19th century (p. 78). Then again, rulers can also be “naturalized” and employ an “official nationalism” in order to culturally homogenify their territory and counter popular national movements (p. 86).

Education is another factor that contributed to the creation of imagined communites; for instance, the colonial subjects of the multiethnic Dutch East Indies “knew that from wherever they had come they still had read the same books and done the same sums” (pp. 121-122). Then there is the complex of “Census, Map, Museum” (ch. 10, pp. 163-185) – devices through which colonial rulers categorised their subjects and at the same time inadvertently helped form their national identities.

Thus Anderson discusses various ways to create nations, but the point is that they need someone to create them. Otherwise, the idea of a particular imagined community would fail to catch on and people would not identify with it as their nation. For our example today, we’re going to examine such failed creations of nations in a comic. While this isn’t going to prove Anderson’s theory right or wrong, it will hopefully illustrate some of his ideas.

Our example is going to be Sarah (沙流羅 sarura, also known in English as The Legend of Mother Sarah), written by Katsuhiro Ōtomo, drawn by Takumi Nagayasu, and originally published from 1990-2004 – more specifically its first (German) volume. In a war-torn future, the eponymous protagonist gets separated from her four children and sets out on an epic quest to reunite with them. The background of this plot is mainly told in a prologue text: there has been a nuclear war which has left Earth uninhabitable. The survivors fled to space colonies. There, scientists developed a bomb to tilt the earth axis, which would slowly cleanse the planet of radiation and eventually allow it to be settled again. This plan split people into a supporting and an opposing faction who called themselves “Epoch” and “Mother Earth”, respectively. The hostilities between these factions led to terrorism and even civil war. The bomb was launched after all, and even though the terrestrial climate is still somewhat hostile, people started returning to the earth’s surface, where the fighting between Epoch and Mother Earth continues. The bone of contention is no longer the use of the bomb, though, but global domination.

Epoch guards against civilians. Detail of p. 19 from Sarah vol. 1 by Katsuhiro Ōtomo and Takumi Nagayasu.

Can Epoch and Mother Earth be regarded as nations in Anderson’s sense? In the very first scene of the manga, which still is a kind of prologue to the actual story, we already see representations of Epoch: while people are fleeing from a space station which is shattered by explosions, they are watched by armed men with the letter E on their hats, helmets and bandanas. The same E logo is crudely painted on walls inside the space station, indicating that Epoch rules this place. The ordinary people, however, do not sport any Epoch signs. They are no so much protected by the Epoch gunmen as controlled, the latter sifting through the crowd looking for enemies. And when a panic breaks out and everyone tries to board the escape shuttles at once, the Epoch men indiscriminately shoot into the crowd to stop them.

A Mother Earth officer. Panel from Sarah vol. 1, p. 73 by Katsuhiro Ōtomo and Takumi Nagayasu.

Then the action shifts to earth in the present day, i.e. some time after the exodus from the space stations. Sarah, accompanying a travelling merchant, reaches a small settlement adjacent to a gigantic mine. The mine is operated by the Mother Earth military, the soldiers being identifiable by small “ME” (plus a winged globe icon) logos on parts of their uniform. The workers in the mine are prisoners of war from Epoch, more clearly marked by large “E”s on their clothing or bare backs.

Epoch prisoners of war guarded by Mother Earth soldiers. Panel from Sarah vol. 1, p. 36 by Katsuhiro Ōtomo and Takumi Nagayasu.

There is a discernible divide between the soldiers overseeing their high-tech mine, and the local populace who farm the land using few machines and live in primitive-looking brick buildings. It is a science-fiction trope that we know from e.g. Star Wars: the common folk are simply trying to get by while there’s a war raging around them which they have not the slightest stake in (but which some of them, of course, ultimately get caught up in). The only link between them is the character Toki, a young man who comes from a farming family but has joined the military. Unlike his stepsister Lucia, Toki hates Epoch and blames them for devastating the earth. Lucia retorts by reminding him of Mother Earth’s constitution, which says war is bad and that “we shall live in harmony with mother earth and preserve its treasures”. Toki dismisses this as idealism that one cannot live by.

The local ‘neutral’ civilian population. Panel from Sarah vol. 1, p. 31 by Katsuhiro Ōtomo and Takumi Nagayasu.

But when Toki and Lucia discover the secret purpose of the mine, the military wants to see both of them dead. The ensuing brutal raid, in which both a soldier and Toki’s and Lucia’s grandfather are shot, epitomises the divide between military and civilians. (In later volumes, we even see tanks firing into crowds.)

Clearly, nation-building has failed in Sarah. The only ones who identify with the nations of Epoch and Mother Earth are soldiers, whereas the civilians don’t seem to have any national identity whatsoever. With the sole (and only temporary) exception of Toki, the soldiers appear not to belong to the folk who settle at the mine. The military rather seems like an occupying force from a distant country, only there to exploit the natural resources and possibly gone again soon.

This should not come as a surprise, as none of Anderson’s nation-forming devices are visible in this manga: no print-capitalist products (except for a pornographic magazine), no ‘naturalised’ rulers, no education, no maps, no census, no museums. And as in many other science-fiction stories, everyone seems to speak the same mother tongue (despite signs of some racial diversity), so that no separate language communities could form within the overall population.

Index to all “[theory] – in comics?” posts on this weblog

Book chapter on Akira and Ghost in the Shell (the anime) published

The Routledge Companion to Cyberpunk Culture, edited by Anna McFarlane, Graham J. Murphy, and Lars Schmeink, has been published last month. This book contains a chapter co-authored by Lars Schmeink and myself, titled “Akira and Ghost in the Shell (Case Study)”, on pp. 162-168. Rather than discussing the manga, this short text focusses on the theatrical anime versions (Ōtomo 1988, Oshii 1995) and their relation to cyberpunk. (For Akira the manga and cyberpunk, see my earlier journal article in Arts.)

The Routledge Companion to Cyberpunk Culture contains many more chapters of which some deal with comics and anime and might be of interest to readers of this weblog. Follow the link to the publisher’s website for a table of contents. While the printed book is a bit on the pricey side, consider recommending it to your library for acquisition, borrowing it via interlibrary loan, or purchasing the e-book version.

Multivariate statistics: how to measure similarity between comics (or anything, really) based on several characteristics

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).

1 variable

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.

2 variables

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.

Anyway, now we have 4 pairs of values, (8/7), (3/8), (6/3) and (7/2), which we could plot on a x and y axis, like this:

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.

3 variables

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.

4 variables

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.

dialogue in Katsuhiro Ōtomo’s Akira (A1, left) vs. dialogue in Miko Yasu’s Hakozume (M1, right)

25 variables

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.

Akira Code 7 Alert

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.

Kanji-kana ratio for stylometry?

I ended my blogpost on hiragana frequency as a stylometric indicator with the remark that, rather than the frequency distribution of different hiragana in the text, the ratio of kana to kanji is used as one of several key characteristics in actual stylometric analysis of Japanese texts. I was curious to find out if this number alone could tell us something about the 4 manga text samples in question (2 randomly selected scenes from Katsuhiro Ōtomo’s Akira and 2 series from Morning magazine, Miko Yasu’s Hakozume and Rito Asami’s Ichikei no karasu – in the following text referred to as A1, A2, M1 and M2, respectively). My intuition was that the results wouldn’t be meaningful because the samples were too small, but let’s see:

This time I chose a sample size of 200 characters (hiragana, katakana, and kanji) per text.

Among the first 200 characters in A1 (i.e. Akira vol. 5, p. 16), there are 113 hiragana, 42 katakana and 45 kanji. This results in a kanji-kana ratio of 45 : (113 + 42) = 0.29.

In A2 (Akira vol. 3, pp. 125 ff.), the first 200 characters comprise of 126 hiragana, 34 katakana, and 40 kanji, i.e. the kanji-kana ratio is 0.25.

In M1, there are 122 hiragana, 9 katakana, and 69 kanji, resulting in a kanji-kana ratio of 0.52.

In M2, there are 117 hiragana, 0 katakana, and 83 kanji, resulting in a kanji-kana ratio of 0.71!

6 hiragana, 2 katakana, 3 kanji in A2 (Akira vol. 3, p. 125).

Thus this time the authorship attribution seems to have worked: the two Ōtomo samples have an almost identical score, whereas those of the two Morning samples are completely different. Interestingly, this result contradicts the interpretation from the earlier blogpost in which I had suggested that the scientists in Akira and the lawyers in Karasu have similar ways of talking. The difference in the kanji-kana ratio between Akira and the two Morning manga, though, is explained not only through the more frequent use of kanji in the latter, but also through the vast differences in katakana usage (note that only characters in proper word balloons, i.e. dialogue, are counted, not sound effects).

Ōtomo uses katakana for two different purposes: in A1 mainly to reproduce the names of the foreign researchers, and in A2 to stretch syllables otherwise written in hiragana at the end of words, e.g. なにィ nanii (“whaaat?”) or 何だァ nandaa (“what is iiit?”). Therefore the similarity of the character use in the two Akira samples is superficial only and the pure numbers somewhat misleading. On the other hand, it makes sense that an action-packed scene such as A2 contains less than half as many kanji as the courtroom dialogue in M2; in A2 there are more simple, colloquial words for which the hiragana spelling is more common, e.g. くそう kusou (“shit!”) or うるせェ urusee (“quiet!”), whereas technical terms such as 被告人 hikokunin (“defendant”) in M2 are more clearly and commonly expressed in kanji.

In the end, the old rule applies: only with a large number of sample texts, with a large size of each sample, and through a combination of several different metrics can such stylometric approaches possibly succeed.

Hiragana for stylometry?

The other day I’ve been made aware that some things I’ve said in an earlier blogpost, “Author dictionaries and lexical analysis for comics”, might be misleading. So let’s be clear: if you would like to find something out about the writing style of an author or text, it’s not the best idea to look at the frequently used nouns, kanji, or other units of high semantic content. Those are more useful for analysing the content, i.e. the topic(s), of texts. In stylometry, units with low semantic content, such as function words (the, a, it, etc.), are more attractive objects of study, as they can be used almost independently of the topic and often present writers with a choice of which word to use when. In other words, the same writer tends to use the same function words and may be identified by them. (In practice, though, a combination of different characteristics is used for analysis – see the Stylometry article at Wikipedia and the references there.)

In order to automatically separate function words from content words in a digital text, part-of-speech tagging software may be employed. For Japanese, there is e.g. Kuromoji. But isn’t there a simpler way? Can’t we make use of the kanji–kana distinction used in the aforementioned earlier blogpost? If we identified kanji as the semantically rich(er) units, wouldn’t it be sufficient to focus on the kana for stylometric analysis? Maybe, maybe not. The results would probably be poorer, due to two main reasons:

  1. Every content word (noun, verb, adjective), even if usually written in kanji, may also be written in kana. For instance, 分かる (to understand) is more frequently spelled in hiragana only, わかる. So when we gather kana from a text, we might end up with unwanted content words.
  2. In flection suffixes, hiragana are dependent on the preceding kanji, and thus ultimately on the content of the text. For instance, a text on musical performance might contain many instances of the verb 引く hiku (to play an instrument), so one can expect the hiragana か ka, ki, ku, ke and こ ko to occur more frequently than in other texts, as they are used for inflecting 引く.

That being said, why don’t we put this kana analysis method to the test anyway? Let’s take the example from Akira vol. 5, p. 16 again in which the scientists are talking (初めまして。スタンリー・シモンズ博士です etc.). We’ll focus on hiragana and ignore katakana, as they tend to be used for nouns too. Starting from those two panels, I manually counted these and the following hiragana until I reached 100. Here are the 5 most frequent hiragana in this set:

  • de: 8
  • i: 7
  • shi: 7
  • te: 7
  • no: 6

That means, if this was a sufficiently large sample, in any other piece of text by Ōtomo, or at least within Akira, roughly 8% of its hiragana should be de, 7% should be i, etc. So I randomly picked another scene from Akira (vol. 3, p. 125 ff) and looked at the first 100 hiragana there. The 5 most frequently used hiragana from the previous example are used less often here, with the exception of i:

de, su, u, ru, se, da

  • de: 3
  • i: 8
  • shi: 1
  • te: 2
  • no: 3

In these pages in vol. 3, we find mainly other hiragana such as tsu (9 times – including small tsu), ga (6 times), o (5 times) and su (5 times) to be the most frequently used. That, however, doesn’t tell us anything yet about the similarity of these two pieces of text (which I’m going to call “Akira 1″ and “Akira 2″ from here on). We need to add a third example, and for this purpose I’m going to use 100 hiragana from Miko Yasu’s Hakozume from the recently reviewed Morning magazine. If our method is successful, the differences between Hakozume and each of the two Akira scenes should be larger than those between Akira 1 and Akira 2. With frequency values for approximately 50 distinct hiragana we now have 3 × ~50 data points on which we could unleash the whole range of advanced statistical methods. But we’ll keep things simple by simply adding up the differences in frequencies: Hakozume contains only 6 instances of de, i.e. 2 less than Akira 1; Hakozume uses 3 times i as opposed to the 7 in Akira 1, i.e. 4 less; Hakozume contains 6 instances of shi less than Akira 1; etc. Here’s the table of frequencies of de, i, shi, te and no in Hakozume:

a, no, na, n, de, a, no, ga…

  • de: 6
  • i: 3
  • shi: 1
  • te: 6
  • no: 8

The combined difference between Hakozume and Akira 1 for these 5 hiragana would be 2+4+6+1+2 = 15. For all ~50 different hiragana, the sum is 96.

This looks like a large number, and indeed, when we calculate the difference between Akira 1 and Akira 2 in this way, the result is 82. This means, the two Akira chunks are more similar in their usage of hiragana than Hakozume and Akira 1.

However, we’re not done yet. We still need to compare Hakozume to Akira 2. The result of this comparison may come as a surprise: the sum of differences is also 82! So Akira 2 is as similar to Hakozume as it is to Akira 1. If our goal was to find out whether a given piece of text is taken from Akira or not, our method would fail if we used Akira 2 as our base text with which to compare all others.

ha, no, ki, ka, ra, ho, do, de, ki, wo…

Just to make sure, I took another 100 hiragana from a different random manga in the same issue of Morning, Rito Asami’s Ichikei no karasu. I’ll refer to Ichikei no karasu as Morning 2 from now on, and to Hakozume as Morning 1. The results of the comparisons are even ‘worse’: while the sum of differences between Morning 2 and Akira 2 is 98 – i.e. vastly different – the difference between Morning 2 and Akira 1 is only 74, i.e. very similar.

Frequency of all hiragana in each of the four 100-hiragana samples

In a way, the results do make sense though. We’re looking at dialogue, after all, and the way scientists (in Akira 1) speak is closer to that of lawyers (in Morning 2) than that of insurgent thugs (in Akira 2). And apparently, the conversation between the two policewomen (in Morning 1) is not quite unlike the latter.

As ever so often we could now blame the unsatisfactory results on the small sample size – if we had used chunks of 1000 hiragana instead of 100, surely our attribution attempts would have been more successful? We’ll never find out (unless we obtain a complete digital copy of Akira and extract the hiragana automatically). Another way to improve results would be to tweak the methodology: using data mining algorithms, more elaborate metrics such as co-occurrence of several hiragana could be employed. In actual stylometric research, hiragana seem to be used in yet another metric – the ratio of all hiragana to all other characters (kanji, katakana, rōmaji).

Article “Has Akira Always Been a Cyberpunk Comic?” published

Earlier this year I gave a talk at MSU Comics Forum, and now a journal article based on that talk has already been published:

Has Akira Always Been a Cyberpunk Comic?
Arts 7(3),

Here’s the abstract again:

Between the late 1980s and early 1990s, interest in the cyberpunk genre peaked in the Western world, perhaps most evidently when Terminator 2: Judgment Day became the highest-grossing film of 1991. It has been argued that the translation of Katsuhiro Ōtomo’s manga Akira into several European languages at just that time (into English beginning in 1988, into French, Italian, and Spanish beginning in 1990, and into German beginning in 1991) was no coincidence. In hindsight, cyberpunk tropes are easily identified in Akira to the extent that it is nowadays widely regarded as a classic cyberpunk comic. But has this always been the case? When Akira was first published in America and Europe, did readers see it as part of a wave of cyberpunk fiction? Did they draw the connections to previous works of the cyberpunk genre across different media that today seem obvious? In this paper, magazine reviews of Akira in English and German from the time when it first came out in these languages will be analysed in order to gauge the past readers’ genre awareness. The attribution of the cyberpunk label to Akira competed with others such as the post-apocalyptic, or science fiction in general. Alternatively, Akira was sometimes regarded as an exceptional, novel work that transcended genre boundaries. In contrast, reviewers of the Akira anime adaptation, which was released at roughly the same time as the manga in the West (1989 in Germany and the United States), more readily drew comparisons to other cyberpunk films such as Blade Runner.

Read the article online for free at

Fun fact: this is my 10th publication (not counting reviews, translations, and articles related to my library ‘day job’)! Find them all here:

Upcoming talk: Has Akira always been a cyberpunk comic?

In less than a month, I’m going to participate in a panel on cyberpunk comics at Michigan State University Comics Forum. Here’s the abstract for my paper, which is closely connected to my PhD research:

Between the late 1980s and early 1990s, interest in the cyberpunk genre peaked in the Western world, perhaps most evidently when Terminator 2: Judgment Day became the highest-grossing film of 1991. It has been argued that the translation of Katsuhiro Ōtomo’s manga Akira into several European languages at just that time (from 1988 in English, from 1991 in French, German, Italian and Spanish) was no coincidence. In hindsight, cyberpunk tropes are easily identified in Akira to the extent that it is nowadays widely regarded as a classic cyberpunk comic. But has this always been the case? When Akira was first published in America and Europe, did readers see it as part of a wave of cyberpunk fiction? Did they draw the connections to previous works of the cyberpunk genre across different media that today seem obvious? In this paper, magazine reviews of Akira in English and German from the time when it first came out in these languages are analysed in order to gauge the past readers’ genre awareness. The attribution of the cyberpunk label to Akira competed with others such as the post-apocalyptic, or science fiction in general. Alternatively, Akira was sometimes regarded as an exceptional, novel work that transcended genre boundaries. In contrast, reviewers of the Akira anime adaptation, which was released at roughly the same time as the manga in the West (1989 in Germany and the United States), more readily drew comparisons to other cyberpunk films such as Blade Runner.