Japanese Visual Media Graph

Here we are, finally done with our series on Tiny Use Case 2, so let’s do a quick TL;DR summary of what happened in the four preceding blogposts (1, 2, 3, 4):

• • In part one we wanted to find a claim to test from Hiroki Azuma’s seminal book Otaku: Japan’s database animals (2009, Japanese original published in 2001) with the help of the JVMG database
  • We settled on the point captured in “As a result, many of the otaku characters created in recent years [the late nineties to two thousand] are connected to many characters across individual works, rather than emerging from a single author or a work.” (p 49)
  • And formulated two hypotheses based on this idea of characters becoming increasingly derivative of each other, later finalized in the following form:
    1. The portion of new characters with shared traits should increase over time.
    2. The portion of shared traits among new characters should increase over time.
  • Then in part two we introduced some of the specificities of the two datasets (The Visual Novel Database (VNDB) and Anime Characters Database (ACDB)) we were going to use for our analysis, and explained the operationalization of our concepts on the data.
  • For better comparability we decided on splitting the ACDB data into two datasets, one for visual novel characters and another for (mostly anime) other characters.
  • We identified a temporal trend in all three datasets with number of characters and average number of traits both peaking around the early 2010s and then declining. Assuming that the number of traits used to describe characters is a good proxy value for the amount of attention being paid to the data, we concluded that our datasets are most likely not complete, especially for the second half of the 2010s.
  • In part three we reported on the series of regression analyses we conducted to identify the best models explaining the change in the number of characters with shared traits in each of the three datasets, and found that our first hypothesis was not substantiated by our results. Furthermore, we found no adequate regression model for testing our second hypothesis.
  • Finally, in part four we first examined the validity of our results.
  • Then, we examined the theoretical implications of our findings on Azuma’s argument. We concluded that our results suggest considering the possibility that the production side of Japanese anime and manga has always been “database-like” in its mode of operation. This, however, would not invalidate Azuma’s main line of argument in relation to consumption and postmodernity in Japan. Nevertheless, amending his line of reasoning in relation to the production side of the argument would help foreground his potential theoretical debt to the work of Toshio Okada.

We saw in an earlier post that the third phase of each Tiny Use Case revolves around evaluation. Thus, it is time for us to evaluate what we have learned during the course of TUC 2, and what remains open for further exploration.

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It has been quite a journey getting to this fourth part in our series on Tiny Use Case 2. We started out by introducing Hiroki Azuma’s discourse defining work, Otaku: Japan’s Database Animals, and picking out a claim that would be worth examining on the JVMG database. Next we introduced the two datasets (The Visual Novel Database (VNDB) and Anime Characters Database (ACDB)) we were employing for our analysis, and examined some key descriptive statistics. Finally, in part three we employed the toolkit of regression analysis to see whether our two hypotheses are confirmed or contradicted by the data at our disposal. Our hypotheses were:

1. 1. The portion of new characters with shared traits should increase over time.
   2. The portion of shared traits among new characters should increase over time.

We found that our first hypothesis was not substantiated by our regression analyses. And we found no adequate regression model for testing our second hypothesis.

Now, in this fourth part of the series we will first assess our approach and the validity of our results. Then we will consider what implications our findings could have for Azuma’s original argument and the wider theoretical discourse on anime and manga.

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Following the first part of this series, where we introduced Hiroki Azuma’s seminal book Otaku: Japan’s Database Animals, and identified the point (“many of the otaku characters created in recent years are connected to many characters across individual works” (p 49)) we are testing on the JVMG database; in part two we discussed the two datasets (The Visual Novel Database (VNDB) and Anime Characters Database (ACDB)) we are working with and the operationalization of our concepts on these datasets. Furthermore, we examined some key descriptive statistics , and based on what we saw, we reformulated our initial two hypotheses to be the following:

1. 1. The portion of new characters with shared traits should increase over time.
   2. The portion of shared traits among new characters should increase over time.

In this third and final part of the series we will apply the toolkit of regression analysis to try and understand the relationships – we saw in part two – in our data better, and hopefully get closer to testing out hypotheses. Regression analysis revolves around trying to estimate the relationship between the dependent variable (for which we would like to explain the observed changes in its values) and the independent variables (also called explanatory variables, since we aim to use them to explain the changes in the dependent variable’s values). If there are multiple possible relationships between the independent variables and the dependent variable, for example due to the large number of possible explanatory variables we could include in our model, the process of regression analysis involves comparing the different possible models and selecting the best performing one.

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In the first part of this series we introduced Hiroki Azuma’s seminal book Otaku: Japan’s Database Animals, and identified a point to try and test on the JVMG database, namely that “many of the otaku characters created in recent years are connected to many characters across individual works” (p 49). This led to the formulation of the following two hypotheses.

1. 1. The number of new characters with shared traits should increase over time.
   2. The number of shared traits among new characters should increase over time.

How do we go about actually testing these hypotheses on the available data? Well, we would need to be able to somehow assign appearance dates to each character, otherwise we won’t be able to look at changes over time, and we also have to be able to define what characters with shared traits mean in the context of our data. So let’s take a look at the data we have to work with.

For this TUC we decided to use the data from The Visual Novel Database (VNDB) and Anime Characters Database (ACDB), as these databases both have a significant number of characters and a relatively large number and detailed level of traits describing them. There are, however, important differences between the two datasets. VNDB only focuses on visual novels, whereas ACDB collects data on a wide range of characters from various media (although predominantly focusing on visual novels and anime). Furthermore, VNDB has a very rich and rigorously structured – nevertheless open to extension by users – ontology of traits, which, however, lacks a core set of featured traits that would be expected to be available in relation to all characters. In contrast ACDB features a hybrid system for describing characters, which on the one hand supports a closed ontology for eight flagship traits that are part of each character’s fact sheet, and on the other hand provides the opportunity for a free form tagging of characters with user created labels.

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Hiroki Azuma’s Dōbutsu ka suru posutomodan: otaku kara mita nihon shakai (Animalizing postmodern: Japanese society as seen from otaku), published by Kōdansha in 2001, has been one of the most influential treatises on not only Japanese otaku (the word roughly translates to avid fans of anime, manga, games, etc., similar in meaning to geek in the English language domain), but also on the production and consumption paradigm defining Japanese anime, manga, light novels and games in late modernity. The books impact on the discourse around otaku and the just enumerated domains is truly international thanks in part to the English translation, which was published in 2009 as Otaku: Japan’s database animals (introduction and translation by Jonathan E. Abel & Shion Kono, University Of Minnesota Press, all quotes in the following are from this English edition).

With almost twenty years since the original publication in Japanese and more than ten years since the English translation was released, the concepts and frameworks outlined by Azuma have become almost taken for granted cornerstones of this scholarly discourse. However, even though Azuma’s line of argument contains a number of potentially testable statements, to the best of our knowledge these have so far not been subjected to any large-scale empirical test, as they are most often only invoked in relation to various case studies. The aim of this Tiny Use Case was to identify a testable major point from Azuma’s seminal work, and to test it with the help of the database assembled within the framework of the JVMG project.

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Part I of this blogpost left us with the question of whether there is a specificity to visual novel game characters. Part II concluded with an invitation to compare two specific design elements, tareme and tsurime in light of the player’s position during the gaming experience and the data available on the VNDB repository. In this third and final part we will summarize the analysis of data pertaining to tareme and tsurime leads us.

First, we need to remind ourselves that the exchange of gazes between the player and the character is one of the defining elements of a visual novel game’s experience. A visual novel game is played in a first-person perspective: the prose is written in the first person and character sprites are generally depicted as looking at the player.

This digression has been necessary to highlight the importance that the first person and the gaze have in generating the experience, and in turn re-highlight the potential importance of eyes in the construction of the characters. This brings us once more to tareme and tsurime and what kind of demeanor they communicate. According to their description on VNDB.org, tareme suggests a gentler and caring demeanor, opposed to tsurime, which suggests a demeanor that is more distant and generally non-friendly.

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Is there a specific ‘visual novel game character’ or are they simply a subset or a video game adaptation of anime/manga characters? This is the question we were left with at the end of part I. While the question is obviously too large for one tiny use case, it is still possible to gather some insights into what constitutes a visual novel game character. It might not yet be possible to do a large-scale comparison with anime and manga characters, it is very possible to garner precious insights through the examination of vndb.org data about visual novel game characters.  

First, let us look at the numbers of vndb.org: the site catalogues 91240 visual novel characters via a system of 2140 traits. These characters come from a grand total of 27951 distinct visual novel game titles. The Visual Novel Database’s trait system is a rich apparatus with which fans can catalogue characters in visual novels on the basis of specific categories. There are trait trees pertaining to a character’s hair, a character’s eyes, their body shape, their clothes, personal items, personality, their role in the game’s narrative, what they do and what is done to them, with separate trees for sexual activity.

To employ such a system in a meaningful manner, we first decided to consider the position of the player as they play through a visual novel game. During the course of the game, the player is (usually) first introduced to each of the game’s characters, and then presented with the first of many choices to steer the gameplay experience towards one character or another. Intimacy is gradually built through discovery of a character’s personal narrative, which articulates conventional design elements known to fans and producers into the game’s specific narrative context. By knowing the character more and more, the player can make decisions that are more in accord with a specific character.

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The first Tiny Use Case undertaken within the JVMG was about Japanese visual novel games and their characters. Japanese Visual Novel Games are prose-heavy interactive experiences whose main goal is to win the affections of one or more characters. Visual novel games feature situations and interaction proper of Japanese anime and manga, which the player navigates by choosing which path to take through the narrative at specific points. These points are presented as choices between multiple options, each of which will steer the player towards one character or another, or even towards a failure state. The player progress towards a character’s affection through a series of narrative events, until physical intimacy is reached. When intimacy gets physical, it is usually represented in pornographic fashion, with situations proper of pornographic manga and anime.

Japanese Visual novel games present an interesting research object in the form of character design elements: are these characters simply anime/manga characters deployed into an interactive framework with pornography along the way or is there some specificity to characters in visual novel games? How can we employ the JVMG data efforts to garner insights into the distinctiveness (or lack thereof [2]) of characters in visual novel games? Can we test this against knowledge from both the researcher and scholars in the field?

The importance of characters to the game experience is, by itself, not something distinctive. For all intents and purposes a character can exist as manga, anime and within a video game without any media having ‘precedence’ over the other. One example is Uzumaki Naruto from the eponymous franchise: while the manga has come out before the animated adaptation, there is no substantial difference between Uzumaki Naruto within the manga or within the anime.

Certain characters can also exist before media adaptation, an example of which is Hello Kitty. Characters in visual novel game are design according to specific practices which call for the usage and re-usage of shared conventionalized elements. A visual novel game character can be immediately compared to another by highlighting the commonalities in character design they possess. This is beyond authors quoting one another, and is more akin to a common system shared by content creators and also content consumers.

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Following the success of our project launching workshop in July 2019, the work on processing community databases started in earnest (you can read about the technical details of the process in relation to ontology creation and data transformation). By November 2019, we were ready to start examining the data and our infrastructure through the lens of exploratory research.

We decided to adopt the Tiny Use Case workflow methodology to have a number of short-term research projects that would be substantial enough to generate meaningful and interesting results in their own right, but would be compact enough to provide an ongoing stream of feedback on issues with the database, the project infrastructure, and researcher needs. Since each Tiny Use Case is only 3-4 months long, it provides us with an excellent tool for assessing our progress and for uncovering newer issues, as each TUC has a different focus and somewhat different requirements.

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After taking a six month break due to an internship, I restarted my work as a student assistant for the Japanese Visual Media Graph project in April 2020. 

Currently, my main occupation is in the field of data quality control. After getting lots of data from different fan communities, the quality of said data needs to be checked against other sources to make sure there aren’t any errors adopted into the project’s database. To get started with this task, it was decided to first check several small data samples from different providers to enable an easier determination of the duration, effort, and expectable problems and results that a wider data quality control would entail. 

I received the first two data samples from two different fan sites, both containing twenty entries of anime with several properties for me to check; those properties were, for example, the Japanese and English titles of the anime, the producing studio’s name in Japanese and English, the release date of the first episode, and the overall episode count or the completeness of a series. The properties in the samples depended on the usage of properties by the fan communities the data came from, and my task was to check if the entries were correct or if they contained some errors. To prove something, I had to find a source of ground truth for it, which would occasionally prove to be some kind of a challenge. Of course, the anime on DVD would actually be the best source of ground truth, but since the resources for this simply didn’t exist, I relied on other sources. A valid source of ground truth would, for example, be the opening or ending sequence of an anime, preferably found on YouTube or a legal streaming source like Netflix or Crunchyroll. An image of the DVD-case of an anime would also be a usable source for ground truth. 

I worked with the data in an excel sheet, marking the correctness of the respective properties accordingly and adding screenshots and links to my sources of ground truth.

I encountered a noticeable difference in finding ground truth for the different properties. Finding proof for the Japanese or English anime titles almost never posed a problem; they usually could be found in the opening sequences or on DVD-cases. The year of first release could also be usually seen in the opening or ending sequences. The exact date was however sometimes quite difficult to proof. While I tried to use the Japanese Amazon Prime at first, it proved to be not reliable enough. Most of the time I could only return to the Media Arts Database to find proof for an exact date of release.

The names of the producing studios could usually be found easily inside the opening and ending sequence of the respective anime; however I sometimes encountered the problem that the studio didn’t write its own name in katakana, like provided by the fan-based data. While I usually could validate that it was indeed the correct studio, the spelling couldn’t be found in any official source for ground truth. I always marked those occurrences as “correct but strange” and left it open for further decisions.

A complicated property was the completeness of an anime. Whether or not this is a usable or provable property remains to be discussed.

After having checked those first two data samples, I can state that there was a lot of correct data, but also errors of different types. How to deal with them is also currently a point of discussion. The next samples from new sources will surely bring even more new experiences and insights.