Leveling Up Game Analytics
This is a call for contributions to the book Leveling Up Game Analytics. The goal of this community-driven book is to assist the game industry with building and maturing current analytics practices, via dissemination of knowledge from the people and companies who have already adopted analytics practices and to provide a reference point for analytics work in games. Get the Call for Contributions as PDF here.Welcome!
The idea and motivation for building Leveling Up Game Analytics (LUGA) springs from the book Game Analytics: Maximizing the Value of Player Data (GAMD). The latter was published in the Spring 2013 as a result of about two years of work involving over 50 experts from industry and academia.
GAMD scratched the surface of a field that is evolving at prodigious rates, and there is thus much that we could not cover in that book, or which has happened since it was published. The goal of LUGA is to get some of the gaps covered and help the industry and the community advance the maturity of analytics practices across any game, any company and any platform. The goal of LUGA is to inform, to bridge the knowledge gaps and bring our experiences and techniques to the community.
Leveling Up Game Analytics will take the form of an anthology, i.e. a volume created by combining chapters (contributions) from multiple authors. All contributions will go through a review process, not only by the editors but also by peers.
Combined by the aim to release a traditional hardcopy book, LUGA will also integrate an online publishing format. In practice, this means that incoming chapters and contributions will be released on a running basis online via a dedicated website and potentially also via one of the major game sites. This allows the community to access contributions as fast as possible, enabling anyone to comment on chapters, initiating discussions, engaging the authors directly and providing feedback.
It also means that it is possible for authors to update their material right up until the point where a hardcopy version of the book is printed – and also following the publication of the hardcopy version.
Rather than using a thematic structure like in GAMD, LUGA will use a difficulty-based way of structuring the content. A topical structure is challenging to implement due to the degree of overlap between many game analytics topics – e.g. analytics used for user research typically involves data collection, analysis, visualization and reporting, and data for user research is often also used for marketing purposes. The experience from producing Game Analytics: Maximizing the Value of Player Data also speaks for a non-thematic structure.
The idea is that Leveling Up Game Analytics will be divided into 3 sections, labeled Level 1-3 respectively. Each section will have a sub-header borrowing terminology from RPGs, so Level 1 is “Initiate”, level 2 “Journeyman” and level 3 “Master”. A potential level 4, “God Mode” will be activated in case incredibly specialized or advanced contributions are submitted.
The goal of using the level terminology from RPGs is to provide a way of dividing the material that is intuitively understandable to anyone. Level 1 is for the absolute beginner in analytics, with zero prior knowledge, to level 3 where you can freely sling around algorithms, formula and expect readers to have a background in data mining, advanced cognitive theory or whatever stakeholder group you are writing for (e.g. marketing, design …).
The core idea behind structuring the content is based in Capability Maturity Models (CMM)s. A CMM is a development model, based in software development but enormously widely applied in all industrial sectors, which basically describes steps that relate to the degree of formality and optimization of processes. The first step describes a situation where development (or here, analytics) is performed in an ad hoc, informal and basic manner; all the way up to managed result metrics and active optimization of processes, tightly integrated laterally across all aspects of the organization.
Another good example of maturity is the standard model for Business Intelligence (BI) technologies. BI can be divided into four types: targeting the “what” (what happened), the “why” (why did it happen), “monitoring” (what is happening right now) to “prediction” (what will happen in the future). Across these models, the phase or level based partitioning is used to separate the simple/immature from the complex/mature/embedded. We will try to adopt this structure as well: The levels will reflect the relative complexity of the material covered, the degree of reader expertise required, and also the level of organizational analytics maturity required to field the knowledge in each section.
Eventually, as our field matures, we will hopefully see books that individually target different levels of complexity and themes, but this is as yet a bit down the road.
The editorial process of contributions is focused on ensuring a high quality of the content in the book and providing support to the authors.
Upon receiving of a contribution, an editor will be assigned to a submission. The editor will give the submission a read-over, and either provides some initial suggestions for revision to the author/authors, with the expectation that these are addressed quickly, or release the submission on the book’s website and forward the contribution to peer review.
Once a contribution has been cleared for peer-review, it will be sent to a minimum of two reviewers, who will provide additional feedback to the author/authors. Peers will be selected based on skills, knowledge and expertise. Reviewers’ feedback, in addition to any feedback from the assigned editor, will be returned to others. The author/authors are then given some time to revise their submission according to the feedback as necessary.
In order to streamline the process, the goal is for each contribution to be subjected to only one editorial review cycle and one peer-review cycle. Once the final version is in, it will be released to the books website and on any partner sites.
Throughout the entire process, author/authors will have access to the online version of their contribution and can update, change or revise it on a regular basis.
As yet there is no deal made with a publisher of the hardcopy version of LUGA, to supplement the online version (which will be kept online and freely available irrespective of any hardcopy publishing). The editorial team is exploring the possibilities, and considering the relative merits of using a traditional publisher vs. self-publishing with printing on demand. The editorial team is still considering this, and as always, suggestions are welcome.
· November 1st 2013: Invitations to submit are released and CFP distributed.
· April 1st, 2014: Abstract deadline (500 words max, including title and author name + brief bio, submitted to Anders Drachen (email@example.com). The abstracts are used to get an early idea about what content we can expect. Authors will be informed if their proposed topic is out of range for the book or needs modification.
To the extent possible and time permitting, new contributions will be accepted following this deadline, but we cannot guarantee these will make it into the first edition of the hardcopy book. They will be published on the companion website, however.
· July 1st, 12 PM EST, 2014: Deadline for all submissions. There (really) will be no extension of the deadline. All submissions will be put on the LUGA website for community access and –feedback, and can from then on be edited and updated on a running basis by the authors.
· September 1st, 2014: Deadline for reviews and editorial feedback, and notification of whether the submission has been accepted or not. Contributing authors may be asked to help with the review process.
· November 1st, 2014: Deadline for submitting revised and formatted chapters, including all final image files (information to follow). Formatting guidelines as determined by the publisher will be disseminated later. Revised chapters will be put online.
· January 1st, 2015: Intended publication date of the first edition of the hardcopy version of LUGA. Revisions will be published ongoing as the need and interest arises.
The LUGA website will be kept running to facilitate open access to the content material and to allow authors to keep updating their material as necessary.
Please note that the deadlines are important. Extensions will inevitably lead to problematic and time-consuming delays in the book process (we have seen this happen too many times). Late chapters or chapters that do not adhere to the formatting guidelines, will instead be brought forward to the 2nd edition of the hardcopy version of the book, but will continue to have their presence on the LUGA website.
Submission and formatting guidelines
The book will be constructed in chapters of no more than 8,000 words + illustrations/figures/tables. Any author is welcome to submit more than one chapter, but each can only be 8,000 words maximum, and chapters should be thematically different (i.e. no titles like “clustering for analytics – part 1” and “clustering for analytics – part 2”). Chapters can be aligned around similar topics, but must be independently readable and self-contained.
When writing a submission, consider the degree of reader knowledge, and aim the chapter after this.
The target audience for the book is industry, and the language style aligned to this audience, but apart from that the idea behind the book’s structure is that we should be able to write very specifically targeted pieces if we so desire.
All chapters must include the following components/formatting:
· Submissions must be in MS WORD and PDF format
· Submissions must use 12 point Times New Roman font, with headers and sub-headers marked with bold, italics or underlined (1st, 2nd and 3rd level). Standard 1” margins.
· Title must be 16 point Times New Roman font, centered on top the first page. Following the title the names of all authors.
· Right after the title and author names should be an abstract listing the key takeaways of the chapter in bullet point form. Please include 2-5 takeaways. Takeaways should be described using layman’s terminology to the extent possible.
· At the end of the chapter should be a bio of max. 150 words per author, plus a picture.
· All image files should be embedded in the file (eventually we will ask for these separately, in high-resolution JPG or TIFF. Please do not use low-resolution images).
· At the end of the chapter, before the bios, include a section called “next steps” with references to sources where readers can go to learn more about the topic/-s you are covering in the chapter. References can be to anything useful – software, blogposts, books, scientific writings, videos, etc.
· Language must be clear and concise.
· Chapters may not be longer than 5,000 words, plus captions for images/figures/tables, plus bios for authors.
· English (US or UK) are the only accepted languages.
· Arguments should not be made without backing evidence or argumentation. This is very important for the credibility of what you write. For example, you may think that a specific algorithm or method is superior to all others for doing something, but stating this without backing it up weakens the argument. When something is your opinion, say so.
· The submitted chapter should have a high quality and be essentially ready-to-print. While editors and peers will read and provide feedback on contributions, the best way to avoid errors is to make sure what you submit is correctly formatted and that the language is top-notch.
· You should only use in-text references sparingly – this is not an academic volume. References can be provided at the end of the chapter under “next steps”.
· Irrespective of the level you write for (1-5) you must define the key terms being used (there are a lot of divergent opinions about the key terms in the field).
· You are welcome to use text boxes, highlights or similar to break up the text, e.g. to add additional explanation to a term or method.
The editorial team stands by to assist with any questions or provide help with the submission guidelines.
Leveling Up Game Analytics will be a book developed by the community, and therefore rests on the goodwill of those willing to put their precious time into contributing to it.
We sincerely look forward to receiving your submission for the book.
Please do not hesitate to contact the editorial team with any questions, suggestions or inquiries.
Cheers, the editors
Anders Drachen, Game Analytics (firstname.lastname@example.org) [primary point of contact]
Magy Seif El-Nasr, PLAIT Lab, Northeastern University (email@example.com)
Alessandro Canossa, PLAIT Lab, Northeastern University (firstname.lastname@example.org)