In this short paper we introduce graffiti in public restrooms – also known as latrinalia – as a promising object of research. We present an application that uses crowdsourcing techniques to upload and transcribe images of latrinalia on a public web site. This article describes the basic design and functions of the application, presents the status quo of the current dataset, and also gives an outlook on the next steps and future work

Burghardt, Manuel

Hertlein, Franziska

Hinterleitner, Bastian

Lehenmeier, Constantin

Spröd, Thomas

University of Regensburg Publication Server

160                                Session 2: Object Description and Metadata Standards   A Crowdsourced Approach for the Documentation and Transcription of Graffiti in Public Restrooms Manuel Burghardt, Franziska Hertlein, Bastian Hinterleitner, Constantin Lehenmeier, Thomas Spröd Media Informatics Group University of Regensburg manuel.burghardt@ur.de, {franziska.hertlein, bastian.hinterleitner,  constantin.lehenmeier, thomas.sproed}@stud.uni-regensburg.de   Abstract  In this short paper we introduce graffiti in public restrooms – also known as latrinalia – as a promising object of research. We present an application that uses crowdsourcing techniques to upload and transcribe images of latrinalia on a public web site. This article describes the basic design and functions of the application, presents the status quo of the current dataset, and also gives an outlook on the next steps and future work.  Keywords: Graffiti, Latrinalia, Crowdsourcing, Media analysis, Digital hu-manities    1 Introduction Graffiti, which generally denote writings or drawings in a public place, have long been the object of study in various disciplines, e.g. sociology (Lach-mann, 1988) and geography (Ley & Cybriwsky, 1974). Such public writings        In: F. Pehar/C. Schlögl/C. Wolff (Eds.). Re:inventing Information Science in the  Networked Society. Proceedings of the 14th International Symposium on Information Science (ISI 2015), Zadar, Croatia, 19th—21st May 2015. Glückstadt: Verlag Werner  Hülsbusch, pp. 160—164.   A Crowdsourced Approach for the Documentation and Transcription ...    161  are, however, by no means a novel phenomenon, but can be traced back as far as to ancient Pompeii (cf. Hunink, 2011). One specific subtype of graffiti can be found in public restrooms, and is hence referred to as latrinalia, a term proposed by folklorist Alan Dundes (1965). Latrinalia are an interesting object of study, as they occur in a setting that is partly private but at the same time also partly public (Haslam, 2012: 114.). In his article “Toilet Graffiti”, Haslam (2012) gives an overview of research on latrinalia. While most of the existing research is focused on gender aspects, this type of written, semi-public information might also be discussed from a human information beha-vior perspective, as described by Spink & Currier (2006). In order to promote more research on latrinalia, that may also include socio-linguistic and geo-graphical research questions, we present a web-based tool that can be used to upload images of latrinalia and at the same time produce machine-readable transcriptions, to make the data accessible for automatic analyses. The ap-proach may be classified as crowdsourcing (cf. Howe, 2006) and is inspired by the digital humanities project “Dictionary of Words in the Wild”1, which allows users to upload images of public textuality, e.g. of signs or commer-cials.     2 Architecture and implementation details We designed our application as a responsive web service that adapts its lay-out to mobile phones, tablets or more traditional desktop screens.2 The appli-cation utilizes a number of freely available JavaScript libraries, e.g. jQuery3, Exif 4, Underscore5 and Modernizr6. All textual data is stored in an SQL data-base. The images are stored on the public image hosting service Imgur7.                                                   1 http://lexigraphi.ca/ (all URLs referenced in this article were last visited on January 6, 2015) 2 The application is publicly available at http://www.latrinalia.de/. 3 Note: Provides DOM traversal and manipulations, available at http://jquery.com/ 4 Note: Extracts metainformation from images, available at https://github.com/blueimp/ JavaScript-Load-Image 5 Note: Helps to manage templates, available at http://underscorejs.org/ 6 Note: Ensures cross-browser compatibility, available at http://modernizr.com/ 7 http://imgur.com/ 162                                Session 2: Object Description and Metadata Standards   Uploading images When users want to upload an image, they have to provide a short title and select whether the image was found in a male, female or unisex restroom. The users may also provide a transcription of the image during the upload process. If they do not provide a transcription, the image may be transcribed by other users, once it has been published. Users are also asked to select one of the following graffiti types for their image: writing, painting, sticker, or installation. In addition, users may select one or more existing tags (e.g. poli-tics, insult, conversation, sex, sports, etc.) or create a new tag to describe the content of an image. The graffiti types as well as the tags suggested by the system are the result of a preliminary content analysis (cf. Krippendorff, 2013) approach, in which 190 images were classified by four independent coders. Finally, users are asked to (optionally) provide a location for their latrinalia graffiti. The application is able to detect geolocation information from the image metadata or via the users’ IP. Viewing and transcribing images  Any uploaded image is presented on the home page of latrinalia.de. By clicking on an image, users have access to all associated metadata provided by the uploader, but also to comments and ratings of other users (cf. fig. 1). Users may view the latest or best rated images, look for images without a transcription, or search for images with specific keywords, tags, type, sex or location.    Figure 1. Screenshot of an uploaded and transcribed latrinalia image.  A Crowdsourced Approach for the Documentation and Transcription ...    163  Social networking and gamification elements In order to motivate users to contribute to the platform, we provide basic so-cial networking features (personal timeline, following of other users, etc.) and some basic gamification elements: Users are rewarded with an increased rank (levels) and a number of achievements when they upload images, post comments, rate images of other users, transcribe images, etc.    3 Status quo of the dataset    and research potential The application is live since March 2014. Since then, 162 images were up-loaded and transcribed, and a total of 242 tags were provided. Among the most frequent tags are many of the predefined tags, e.g. saying (count: 47), politics (33), quote (15), insult (8), philosophy (8), but also a number of user generated tags that may describe a location, e.g. Regensburg (10), or that may refer to a specific category of insider humor, such as the made-up word vermolst (25). After the application of German and English stop words lists, frequent terms that occur in the transcriptions include political concepts, e.g. “Nazis” (4) and “Freiheit / freedom” (3), religious terms such as “Gott / god” (3), but also more generic concepts such as “Liebe / love” (3).  The data gathered in our application can be used as an image archive for qualitative research on latrinalia. It may be used to answer a broad range of research questions, e.g.: • How does the language of male and female latrinalia differ? • Are there regional characteristics for the topics of latrinalia? • Is there a relation between the type of latrinalia and its content / topic?    4 Future directions and next steps As the application has been evaluated successfully with regard to its perfor-mance and usability for almost 12 months, we are planning to promote the tool more actively on our local university campus, but also via other media 164                                Session 2: Object Description and Metadata Standards   channels, to attract more potential contributors, and to grow a larger database of latrinalia images and transcriptions. The application might also be used in combination with a commercial crowdsourcing platform, such as Amazon Mechanical Turk 8 or CrowdFlower 9. In order to make the database more ac-cessible for researchers, we plan to implement an analysis dashboard that provides basic statistics and analyses for the latrinalia data.    References  Dundes, A. (1965). Here I Sit – A Study of American Latrinalia. Kroeber Anthropo-logical Society Papers, 91–105. Haslam, N. (2012). Psychology in the Bathroom. Palgrave. Howe, J. (June, 2006). The Rise of Crowdsourcing. Wired Online Magazine. http://archive.wired.com/wired/archive/14.06/crowds.html <5.1.2015>. Hunink, V. (2011). Glücklich ist dieser Ort! 1000 Graffiti aus Pompeji. Reclam. Krippendorff, K. (2013). Content Analysis: An Introduction to Its Methodology (3rd ed.). Los Angeles: Sage Publications. Lachmann, R. (1988). Graffiti as Career and Ideology. American Journal of Socio-logy, 94 (2), 229–250. Ley, D. & Cybriwsky, R. (1974). Urban Graffiti as Territorial Markers. Annals of the Association of American Geographers, 64 (4), 491–505.  Spink, A. & Currier, J. (2006). Towards an evolutionary perspective for human  information behavior: An exploratory study. Journal of Documentation, 62 (2), 171–193.                                                 8 https://www.mturk.com/mturk/welcome 9 http://www.crowdflower.com/ 

A Crowdsourced Approach for the Documentation and Transcription of Graffiti in Public Restrooms

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A Crowdsourced Approach for the Documentation and Transcription of Graffiti in Public Restrooms

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