STUDIA UBB EPHEMERIDES, LIX, 1, 2014 (p. 75-102) THE STRUCTURE AND DYNAMICS OF MEME AGGREGATORS FLAVIA ŢĂRAN1 ABSTRACT. This research paper examines the way Netizens, web developers and web entrepreneurs relate to meme culture in the context of meme aggregator platforms, websites that serve as repositories and creation hubs for internet memes. The meme, the cultural equivalent of the biological gene and the trademark of internet popular culture, is showcased as the staple of an emergent economy, where memes are collected and disseminated at an incredible pace, the link becomes the substitute for a number of things (answers, examples, emotions) and the time spent in pursuing memes is being monetized. This papers sets off to determine the most popular meme aggregators of the moment, deconstruct them, identify the most common and popular features and create a taxonomy of said sites. In this context, we comprised a top 30 most popular meme aggregators within a complex scientific framework and applied a binary analysis grid constructed around technical features. Using formal concept analysis and subjective criteria we isolated four modules based on major actions (browsing, contributing, creating, uploading/submitting URLs) and several criteria clusters. We defined these clusters as units for understanding how certain technical features (or lack thereof) reflect on the way internet memes are consumed, aggregated, disseminated or created. This endeavor of constructing a taxonomy of meme aggregators based on architectural features is the first of its kind, offering a framework that can be adjusted and expanded in order keep up with web developers, web trends and meme culture. Key words: internet memes, meme aggregators, digital culture, Reddit, formal concept analysis. Introduction and context Internet memes can be perceived as valid indicators of the state of popular culture and staples of an emergent culture of convergence and dissemination. 1 MA “Babeș-Bolyai” University, Cluj-Napoca, Romania, flavia.taran@gmail.com FLAVIA ŢĂRAN In the context of current online social practices, where the content is gathered and spread at a very alert pace, meme aggregators (MAs) become the focal point for meme activity. The rising number of web platform constructed to meet these new consumptions habits, sustaining and popularizing this particular brand of culture are a rather novel research territory. Our understanding of how MAs work, the relation between the technical layer and the cultural layer is scarcely explored in today’s meme research. This inquiry in the structure and dynamics of meme aggregators is a pioneering effort and targets two major aspects: platform popularity (what are, currently, the most popular MA platforms) and technical implementation of features. This increasing prevalence of meme aggregator sites, as demonstrated by web ranking (alexa.com is the authority for web metrics) raises new and troubling questions about the part Netizens play in a popular culture decision making-process: what are the memes that people will share in the near future? The endeavors of web entrepreneurs to urge and mobilize people to participate can be reflected in the way meme aggregator platform are constructed and managed. Alexis Ohanian, co-founder of reddit.com, a largely popular news and entertainment site, also an aggregator of many things, among which memes, repeats in an almost mantra-fashion that “All links are created equal.” Considering this an axiom of the internet, our investigation sets to deconstruct popular meme aggregators and isolate the building blocks, creating a unique taxonomy. Given that websites are a commodity, we propose a not too narrow, not too wide approach when it comes to dissecting websites, and concentrate more on larger modules of features, than on very specific characteristics. This research sets the groundwork for a comprehensive visual representation of meme aggregator modules and criteria clusters implemented in the most popular platforms, explaining in detail how a MA platform is constructed. This research is designed within a theoretical framework of meme culture, the jump to the internet and importance in a postmodern society, shaping popular culture in a previously unimaginable fashion. Our conclusions are derived from a very intricate research strategy that combines large sets of data, collected with a screen scraper, successive rounds of automated and manual filtering, formal concept analysis for clustering criteria and a hands-on interaction with all the websites taken into consideration, for applying a complex analysis grid. 76 THE STRUCTURE AND DYNAMICS OF MEME AGGREGATORS Marshall McLuhan points out that the medium does not only shape the message, but also its content and, ultimately, its meaning, changing the way we communicate in a fundamental way. The meme aggregator is the new medium and mapping its inner workings creates a new level of understanding, for both the life cycles of memes and for the pro-active audiences. In this sense, the taxonomy we propose starts from the premise that meme aggregators are constructed with various amounts of technical know-how, and while some features are present in some high-ranked platforms, that does not necessarily mean that implementing those features will bring instant traffic to the website. We established that internet memes are converged (aggregated) and diverged (shared and re-posted) as a response to the needs of the audiences: today’s Netizens have broadband, Wi-Fi, smartphones, speak the vernacular tongue and fuel the meme creation engines. They need platforms where they can create, debate, decide, and from where to gather and share. As any other site on the internet, the meme aggregator is the result of a fusion, between the concept/money-making idea and the technical implementation. To be the owner of both the idea and the technical skills is the dream scenario. If this is not possible, capital and a team of developers are needed. The idea and the technical skills cannot and should not be separated, these two creating the major framework through which the platforms will be analyzed. It must be mentioned and taken into account that a terminological shift has propagated within meme aggregators and the broader internet. While, in scholarly terms, a meme is a very complex cultural phenomenon, the internet language has reduced it to a structured type of content: the image macro. Image macro memes (which make up the sole content on meme generator sites, discussed in detail in this research as a subgroup of MA platforms), describe images with witty captioned messages or catchphrases. While these can become memes, they must not be interpreted as the epitomes of meme culture. This misunderstanding is very visible in meme aggregator sites that have special section for “memes”, which might seem redundant, but reflect the current state of this terminological issue. Throughout this research paper we will not be using this meaning, but always refer to image macro memes to describe that type of content Meme aggregators are the artificial nurseries of internet memes, and while scholars have dedicated a great interest in studying memes, the need to see how they are raised and treated, what makes them circulate and end up on our Facebook wall becomes important, for both those involved in meme studies and, to some extent, for web entrepreneurs and audiences worldwide. 77 FLAVIA ŢĂRAN Theoretical Framework Discussions about memes usually start from the 1976 book The Selfish Gene, written by the now increasingly famous British evolutionary biologist Richard Dawkins. He introduced the concept of meme as an extension to his theory of gene replication in the case of cultural phenomena. Music, religion, catchphrases, fashion, the way we make pottery – all these cultural trademarks act similarly to genes, being the units that carry cultural ideas and behaviors. Memes are introduced as the cultural analogues to genes, memes are for culture what genes are for evolution, given that they self-replicate, mutate and undergo natural selection. Their ability to replicate, “to produce copies of themselves, and thereby spread and increase in numbers” (Heylighen, 1996) is, arguably, not necessarily beneficial for society (history can provide examples from religion, politics), but intrinsically in their nature. A meme is successful if it is imitated and refined, under the pressure of evolutionary adaptation and it is rendered dead if it stops spreading and evolving. In the late 1990s, mid 2000smemes became associated with internet culture. Cole Stryker, journalist and scholar with a keen interest in the image board 4chan, talks about internet memes as “cultural currency”, which became “synonymous with weird, cool, and silly web stuff” (2011, p. 23).In a 2010 interview for NPR, Richard Dawkins revealed that even though he was computer-literate at that time he introduced the meme, nobody, not even himself, could have predicted that the internet would become “the perfect ecology for memes”, describing it as “one, great, memetic ecosystem” (Do Youz Knowz What I Meme? Interview with Richard Dawkins, 2010). The jump to the internet meant the jump to another medium, and while the meme is a meme, regardless of it shape or form, becoming a new media object, as described by Lev Manovich in The Language of New Media, came with changes, some terminological (as described earlier with the image macro issue), some structural and behavioral. This memetic ecosystem Dawkins references is the meme pool, a “cultural soup” (Jenkins, Ford, & Green, 2013, p. 18) where memes grow and fight for attention. Stryker theorized a phenomenon he called the Meme Life Cycle (2011, p. 205), admitting that it is loosely defined and although it can be applied on a large scale, it is not universally valid. In his view, the life of a meme looks like this: (1) birth (the original source material is uploaded on the internet), (2) discovery (the material is manipulated/remixed within a underground/small/select community), (3) aggregation (the newly-born meme jumps to the broader internet, usually to a content aggregator, it is promoted, 78 THE STRUCTURE AND DYNAMICS OF MEME AGGREGATORS gets to the top, for a broader audience to see), (4) word of mouth (it takes to social media), (5) blog pickup (it is discover by culture blogs in an attempt to add context), (6) mainstream exposure (if the content is negative, it becomes a news story, if not, miscellaneous “wacky” internet content), (7) commercialization (rarely, it starts making money), and (8) death (it does not actually die, but becomes obsolete and no longer talked about). This life cycle outlines two directions of propagation. The horizontal propagation, within a single platform is a “variations on a theme” approach, until it is picked up by an aggregator and the vertical propagation starts, from platform to platform, growing in popularity. Horizontal and vertical propagation can function simultaneously, and on many levels, implying a rate of success that can rarely be explained or predicted. Belgian cyberneticist and meme enthusiast Francis Heylighen ventured in this grey area of meme probability, but his mathematical models produced inconclusive data, due to the fact that many assumptions had to undergo a simplification process, making very important indicators, like “specific social, psychological, linguistic and cultural factors that influence the propagation of a meme” impossible to incorporate (Heylighen & Chielens, 2008, p. 17). Heylighen mapped out several criteria, which, if met, could ensure a longer lifespan for memes (1993). These criteria and Stryker’s life cycle try to offer an understanding of how memes circulate, within meme aggregators and in the context of sharing content via social networks. At this rate of propagation, the main challenge for MAsis not, necessarily, to identify the emergent memes, but to create platforms which dispose of ways to “grow” memes locally, aggregating everything and giving the public the correct tools to sift through the meme pool and help surface-out the next internet sensations. On the internet, memes are pieces of free-flowing “interactive entertainment” (Stryker, 2011, p. 86), circulated by the power of the link. The insight of internet meme creation and circulation patterns is valuable for site developers. They created platforms that would cater to a complex experience, the universal platforms where people could browse, create and contribute. Throughout this paper we draw a clear distinction between creating and contributing: creating refers to the act of producing new content online, with the means offered by the platform (integrated picture editors, rage comics builders, image macro meme generators), while contributing refers to commenting and voting. 79 FLAVIA ŢĂRAN This shift from passive audiences to active participants has greatly changed the media industries. From Alvin Toffler’s prosumer (Toffle, 1980) to Henry Jenkins’ participatory culture approach (Jenkins, 2006)scholars describe a world where people browse and create, show casing their products, adding meaning and context through discussion and interaction. Branded entertainment greatly profits from this change, if the content and the contributions are read as a market study: what does the audience like/dislike, what is the audience interested right now. In Spreadable Media (2013) Jenkins et al. focus on the shift from distributing content to circulating it, “in ways which might not have been previously imagined” (p. 2).Marshal McLuhan points out that on several occasions that technological innovation and popular culture trends are interdependent. In this context meme aggregators can and must exist, becoming a prerequisite for the way people interact on their social networks. Jenkins’s readability covers both the aggregation and the sharing strategies which make it possible for memes to be re-aggregated and re-shared, remixed and, at one point or another, die due to lack of votes or shares. The need to aggregate internet meme comes from the vortex created by the participatory culture framework, where the barriers for artistic expression are low or none at all and where civil engagement mixes with the quest for the “lulz” (here behaving like a measuring unit for a meme’s success). The need to aggregate is a response to the needs of the audiences: to converge and to spread, a pulsating motion that keep the meme-sphere and the internet alive, where the consumers become “hunters and gatherers pulling together information from multiple sources to form a new synthesis” (Jenkins, 2006), this synthesis being the aggregator. On the internet, the meme is the poster child for popular culture, it is a text constructed from the various meanings appointed by the audiences (Fiske, 2000), which makes reading popular texts a multi-layered cultural experience, where a solid cultural background, competences and the correct discursive skills are required. Popular culture stopped wearing the stigma of inferior culture when the postmodern turn abolished the binary division between high and low/popular culture. Electronic media and remix culture, in the context of the postmodern aesthetics of popular culture formed the petri dish for meme culture. While the audiences’ incentives for create and circulate memes are personal – it gives meaning to one’s day to day life (Fiske, 2000)–, meme aggregator platforms create a commodification cycle, where feuds like 80 THE STRUCTURE AND DYNAMICS OF MEME AGGREGATORS “«You’re stealing our memes!» screams 4chan. «You’re profiting off our hard work!» cries Reddit.” (Stryker, 2011, p. 170) are not uncommon (we will not discuss copyright infringement and online legislation on meme aggregators, but it could be the subject of an extended paper). Websites like Know Your Meme and Encyclopedia Dramatica are often criticized for deconstructing, explaining and adding context to memes, arguing that the pleasure of the meme lies in the decrypting, using one’s personal popular culture reference arsenal. While platforms like 4chan are creation hubs that provide the cultural context, meme aggregators are perceived as nurseries, artificially created platforms that want to commodify the memes. A plea for Reddit: relevancy and inner workings In June of 2005, web developer Steve Huffman and internet entrepreneur Alexis Ohanian set out to build a new kind of website, where the readers would decide what content is relevant and worthy to be featured on the front page, rendering the position of editor obsolete. People would submit links and then vote, creating a democratic news bulletin board system called Reddit. Reddit is a community creating engine for different areas of interest, rather than a single community, manageable through subreddits. Each subreddit is a distinct community, with its own purpose, rules, standards, readership and leadership, something of a free information market, where the creator of a subreddit becomes its moderator. Ohanian described the Reddit venture as hard to manage within the given architecture of the platform: “When you’re trying to build a community from scratch, you need a simple system to encourage participation” (Ohanian, 2013). They implemented an array of features that would determine people to spend time on the site: rewards for active redditors (karma points, trophies), comment section (adding context and humor), freedom to create (almost) any subreddit, friend lists and more. Reddit is open source, so anyone can contribute with features, translations or fix bugs. All the secreate a platform where people want to spend time, the alexa.com rank standing proof: 59 global rank and 24 US rank (April 2014). As a meme aggregator site, Stryker considers Reddit interesting and important for three reasons. (1) “It acts like a gateway between 4chan and the rest of the internet.” 4chan’s content is ephemeral and unedited, sometimes unpleasant and on the edge of legality, so redditors take upon themselves to 81 FLAVIA ŢĂRAN sift through 4chan. (2) “It’s a place where the mainstream media has recently gone to routinely scrape through content for news”. This is a direct reference to what we stated earlier, that platform like Reddit, with their two-directional voting systems, can be read like a market study (what are people most interested at this moment, news wise). (3) “It facilitates meme creation that rewards users in a way that 4chan doesn’t”, rewards that can take various forms. In some aspects, Reddit behaves like the anti-4chan. While both are anonymous, Reddit enforces some standards and a reddiquette, something unheard of on 4chan (no trolling and attacks, no personal information leaks, no insults, constructive criticism). Reddit is a platform situated halfway between the genuine meme creation hubs, like 4chan, and the mainstream media, enforcing its authority as a highly important social news and entertainment platform, with a crucial role in meme creation, aggregation and popularization. Its architectural features and user-driven democratic style of functioning render Reddit and the meme subreddit as one of the most important and interesting place on the internet to study memes in their natural habitat, recommending it as the perfect starting point for this reseach. Research Design We are witnessing an emergent type of economy, that of sharing content via meme aggregator sites, an economy based on this loosely defined currency of the “lulz” and where the memes embody the cultural capital. Creating an abstract taxonomy of the platforms that host content that carries, intrinsically or not, the very sought after “lulz” can emphasize our current knowledge of popular culture and how it circulates, what makes internet users prefer certain platforms (in an “all links are created equal” virtual world) and, maybe, become a reference point for those who are ready for a venture in the business of aggregating and monetizing content. Data regarding how meme aggregators work and behave is very limited to none, Netizens are rarely told upfront where the content comes from (given that many platform tend to appropriate the content they aggregate, applying watermarks) or in what way the content is curated and arranged, or what are the users actually giving up (personal data-wise) for being a living part of the community that will decide what people will share in the next period of time. 82 THE STRUCTURE AND DYNAMICS OF MEME AGGREGATORS Some architectural feature of the platforms that take upon themselves to suggest, structure, popularize and later monetize internet memes are closely related to the manner in which the content is spread, appreciated or remixed. These features consist the starting point for creating a taxonomy of meme aggregators characteristics, circumscribing them in a manner that will suite virtually any such platform on the internet. Creating this classification is the main goal of this research, and in doing so we (1) identified the most popular meme aggregator, (2) isolated a set of criteria that characterize such platforms and (3) made a classification of meme aggregators based on said criteria. In this sense, this research paper endeavors to answer the following questions: (RQ1) Which are the most popular and relevant meme aggregators? (RQ2) What are the main and most common features of meme aggregators? (RQ3) To what extent can people browsing meme aggregators decide what content should get more attention? (RQ4) Which architectural features are more appealing to internet users? Methodology In an aforementioned section on Reddit we presented the relevancy of this particular platform, how the content is structured and edited, and by whom. Acknowledging reddit.com as an important aggregator, the subreddit /r/memes has been selectedas the starting point for this research. Furthermore, it must be reiterated that a conceptual change in the meaning of the term “meme” has occurred over time. While all content can become memetic, in many virtual places this term solely describes image macro-type memes. The research interest is on internet memes, and while it cannot be denied what the internet understands through “memes”, this must be taken into account when interpreting the results. Having established this terminological issue, we proceeded with a screen scraper (automated data collection tool, Helium Scraper version 2.4.0.2) that collected the URLs of 500 meme thumbnail trending on /r/meme in March 2014. Using the same software we created a script that would automatically insert each URL in the Google Images search engine. This retrieved similar images from around the internet and web results for pages 83 FLAVIA ŢĂRAN that include matching pictures2, automatically omitting if an entry appeared in repeated forms on the same page, eliminating duplicate entries. If this automated filtering would not have existed, the final platform tally could have been partial to meme generators (a site typology explained in more detail in the analysis section), which usually have a large number of entries on the same image macro, on multiple webpages. It must be also mentioned that in the cases of memes based on famous or iconic images (screen captures from movie, portraits, logos et cetera), which might have appeared on nonaggregator sites, these results were eliminated in a threshold filtering and a manual filtering, detailed below. After introducing the 500 URLs in the image search engine we retrieved a database of over 26,000 entries. Consecutive series of refining and filtering condensed the previous database to a factor of 63%, the final webpage count being 9,616 unique websites, with different occurrences indicators, showing the number of times those sites were listed as featuring memes (for example reddit.com had an indicator of 762, while almost 70% of the sites had an indicator of 1). From top 80 to top 52, and to the final 30 At this point, we considered the occurrence threshold to be 30, further shrinking the work database to 80 websites, from the total of over 9,600. The next step was a manual screening process, to exclude top sites that could not be circumscribed as meme aggregators (video sharing sites, social network sites). At this point, the work database contained 52 platforms. Taking into consideration that certain anomalies could have occurred in the image search process, given that some meme aggregators host their content externally and are not indexed by search engines, thus not showing up in the database with their real occurrence indicator, we decided on a normalization process that would include a quantifiable indicator of their relevancy, namely their internet ranks. Alexa.com is considered the authority in the field of web metrics and traffic indicators, providing a daily updated rank that shows an estimate of the site’s popularity. This is calculated using as prime indicators the average daily views of the site and page views in the last three months. 2 For more information on how Google Images search by URL functions, you can consult the Google support entry on this topic. support.google.com/websearch/answer/1325808?p=ws_images_searchbyimagetooltip&rd=1 84 THE STRUCTURE AND DYNAMICS OF MEME AGGREGATORS The Alexa rank for the top 52 platforms by number of occurrences (spanning from 762 to 31) were retrieved using the same screen scraper. Top 52 was rearranged according to those ranks and given new ID numbers accordingly (from 1, the best ranked to 52). These 52 most important platforms had, at this point, two ID numbers (occurrence ID and alexa.com ID), and in order to normalize the top, we calculated the average of the two IDs and then arranged them in ascending order3. After this final operation, we created a top 30 most relevant meme aggregators, which would now be subjected to a new level of analysis. The analysis grid We isolated a collection of criteria (technical features) that would largely suite any such platform, constructing a binary analysis grid (1 if the characteristic in met by the platform, 0 otherwise). These features were grouped in, what we considered to be, six key focus points, building blocks of meme aggregator platforms, describing major actions like: (1) Browsing: features concerning how the content can be navigated; (2) Content: what form of content is being aggregated (images, image macros, GIFs, videos); (3) Contributions: comments, voting systems for both comments and content; (4) Authentication: what must a user give in order to become a part of the decision making process; (5) Account and community shaping: features that go beyond those of solely aggregating content, referring to the platforms that provide the means for users to interact with other users, establishing social connections and also proposing a loyalty bond with the platform. (6) Creation: content creating means implemented on the platform (recaption module for image macros, picture editor or any other specific meme builder). 3 Here is an example, to better understand the process. In top 52, the site cheezburger.com had an occurrence number of 88, which made it have an occurrence ID of 22 (it is the 22nd site if using the number of occurrences as ordering criteria). According to alexa.com, it had a global rank of 1,007 (the 1,007th popular site on the internet), giving it a rank ID of 4 (the 4thsite if using the Alexa rank as ordering criteria). The average of the two IDs is 13 (22 and 4). If using this average ID as ordering criteria, cheezburger.com holds the 9th place in our final meme aggregator top. 85 FLAVIA ŢĂRAN These are the six criteria on which the taxonomy is based, condensed later in four modules. We interrogated the 30 meme aggregators, one of the early results being a clear divide on the basis of two needs, creation and browsing: ten creation oriented platforms (meme generators) and twenty browsing oriented (these do not dismiss the creation process, but it is not the main feature). Formal concept analysis (FCA). Lattice Miner Formal concept analysis (FCA) is part of the interdisciplinary filed of information studies and a branch of applied mathematics, with a practical use for data analysis and knowledge processing. The result of FCA is a concept hierarchy derived from a collection of objects and their attributes/properties (Ganter & Wille, 1999). We will not submerge in the mathematics of FCA, but briefly explain how it is used as a data analysis tool. The basic data type for FCA is called a formal context, visualized as a table, the rows are objects (in the case of this research, the sites) and the columns are the attributes/properties (here the technical features of the sites). Between the objects and attributes a binary relation must exist (in the form of ones and zeros, for example), but not every object-attribute pair needs to be related (creating a partial order). The formal context is transformed into a concept lattice, a mathematical structure. The visualization method for a finite Figure 1: A Hasse diagram4 with a three element set {x, y, z}. partially ordered set is the Hasse diagram (Figure 1). Pairs of formal concepts can be partially ordered by the relations between their sets of objects and attributes, with an end result of sub-concepts and super-concepts, forming a concept hierarchy, formally called a concept lattice or Galois lattice. In order to visualize and explore these lattices we used Lattice Miner, a tool that would construct and draw lattices. However, if a 4 Image retrieved from Wikipedia Commons. http://commons.wikimedia.org/wiki/File:Hasse_diagram_of_powerset_of_3.png (April 22, 2014) 86 THE STRUCTURE AND DYNAMICS OF MEME AGGREGATORS large dataset with many relations must be manipulated, this kind of visualization becomes unreasonable to display, this being the main argument for which the initial set of technical features was broken down into six subsets, creating a number of smaller conceptual landscapes. Using Lattice Miner to isolate re-occurring features, we formalized criteria clusters, a syntagm that will be often used throughout the paper, which represents nothing more than a lattice sub-concept, with complementary fine tuning if needed. We nested and arranged these sub-concepts, creating a tree diagram, the taxonomy of criteria clusters for meme aggregator sites, with examples for every cluster. A taxonomy of meme aggregators could be arranged if the criteria clusters would be further grouped. However, this approach would create a very specific taxonomy of architectures, which we predict could describe a minute number of platforms for every block of features, rendering this theoretical model unusable for a large number of meme aggregators. Limitations and advantages When working with automated data collection tools and large datasets, anomalies and errors can occur, and sometimes they are hard to trace and eliminate. Even though we closely and sometimes manually screened, filtered, normalized, made corrections and adjustment to the dataset, a small error margin is expected. Furthermore, we greatly relied on the Google Images search engine, even though it is known that some platforms host their content externally and that content is not always indexed by search engines, explaining our effort to normalize our findings using somewhat objective and impartial data (alexa.com) in order to create our list of most relevant meme aggregators. The top 30 created to serve as a sample for this experimental research was created on the basis of our needs and critical decisions, and it should not be taken as the absolute top of meme aggregators. When creating the taxonomy, the main focus was to create criteria clusters that are both not too general and not too specific, so that the end result would apply not only on one platform, but on a larger number. With this in mind, we decided on a more characteristics/modules-based approach, rather than on a clear architectural mapping of sites, considering that, maybe, some website are not the results of punctilious planning, but of some compromises, or are cost related. 87 FLAVIA ŢĂRAN However, because we used automated data collection and analysis tools we manages to work with large datasets in a more objective manner, in an attempt to create a larger picture of what is happening on the web and in the realm of memes. Furthermore, using formal concept analysis tools we managed to create comprehensive conceptual landscapes for describing meme aggregators. Analysis The visual representation of the taxonomy of criteria clusters for meme aggregators (Figure 2) utilizes, in a compact and methodical way, the six criteria pillars outlined in a previous section, showcasing a balancing act between intentional site features and amateurish endeavors of monetizing memes, content and code, browsing and creating. The last level of the tree diagram offers examples of sites that illustrate a certain set of criteria, but the examples are not singular (a platform can illustrate several sets of characteristics). This is the result of our not too narrow, not too wide approach on clustering the criteria. If the criteria would be grouped in a too specific, the result would be a narrow description of a singular platform, while a two loose grouping would leave a lot of space for interpretation. Factoring all these in our analysis, we created a taxonomy of meme aggregator characteristics, rather than a taxonomy of meme aggregator sites, allowing adjunctions to this framework. The six pillars were condensed in four modules (as visualized in Figure 2), and while all four can be found in several sites, meme aggregators can exist with only some of them, with possible compromises in thefunctionality sector, as we will highlight in the sections below. These modules reflect specific actions that one can engage when on a meme aggregator: (1) browse, (2) contribute, (3) create and (4) upload or submit URLs. Combinations of these modules denote flexibility and a keen interest of the web developers to give the users the correct tools and features to engage with the content. The following analysis dissects some of the criteria clusters, branch by branch, in an effort to explain what makes a platform more enticing that another. 88 THE STRUCTURE AND DYNAMICS OF MEME AGGREGATORS Figure 2: The Taxonomy of meme aggregators (criteria clusters approach) 89 FLAVIA ŢĂRAN Table 1: Description of the criteria clusters from Figure 2 Criteria cluster Blog-Type Description The content is arranged in reverse chronological order, provided by one/several moderators. One cannot create or contribute; it behaves much like a blog, where the content can be browsed and interaction equals commenting. Autopilot It runs autonomous, automatically aggregating content from one/several sites; no moderation and interaction with the content is limited or none. All Inclusive Diverse content forms (images, image macros, videos, GIFs) for a complete meme intake. Slice of the Meme-Sphere Provides only some forms of memes. Scientific Memes are aggregated, researched and explained (in a scientific manner). False Aggregates various content, with a popular meme/funny category; not a meme aggregator per se, but a content aggregator with a popular meme section. Ethnic Memes in other languages, with content specific to a certain nation/ethnic group; a specific cultural background is sometimes needed. Community Building Tools for 2nd level interaction: private messaging, chat, following activity, creating a profile; loyalty towards the platform is being repaid: karma, trophies, achievements. Utilitarian Account The optional/mandatory account serves solely as an activity dashboard, monitoring votes, comments, content. Userocracy The users are given the tools to up/down vote, like/dislike content, comment and up/down vote the comments; the best memes and the most popular opinions rise to the top. Free Userocracy Creating and contributing is anonymous/no account; prone to cyber-attacks, which can result in artificial vote pumping. Conditioned An account is needed in order to create and contribute Userocracy Partial Userocracy Users can vote, one/two directional system(may or may not be conditioned to create an account). Aggregate & Create Main focus on aggregating and browsing, but features basic tools for creating content (usually an image macro builder). Picture Editor Includes a more or less complex picture editor (crop, color correction). Rage Comic Builder Includes a builder for rage comic-type memes. Straightforward Content can be uploaded/submitted via URL; no builders of editors. Meme Generators Specialized in creating image macro-type memes; not very browsing friendly, the landing page usually feature image macro templates, watermarks are added, authentication not usually needed, interaction with the content (vote, comments) limited or none. 90 THE STRUCTURE AND DYNAMICS OF MEME AGGREGATORS The Relative Popularity Criteria Indicator (RPCI) The top 30 most relevant meme aggregator sites was constructed using a rather complex algorithm, data collected automatically, manual filtering and a normalization process using objective metrics provided by alexa.com. Considering this process thorough and the end result relevant, we produced a relative popularity indicator for cluster criteria. The goal of this indicator is to add context to someof the criteria clusters. We consider the indicator relative because the popularity of a certain platform is not necessarily the result of a set of implemented features. The RPCI is an average of the ID numbers belonging to the platforms in the example boxes. The smaller the RPCI, the more popular the criteria cluster is, being represented by high ranked platforms with high occurrence numbers for popular memes (see Table 2). Given the intrinsic relative nature of the indicator, it will only be used to create context for binary divisions of criteria (All Inclusive vs. Slice of the Meme-sphere, Userocracy vs. Partial Userocracy). The scarcely used throughout the paper and the need to create such an indicator can be explained by the need to contextualize the popularity of certain platform with a metric unit. Table 2: Relative Popularity Criteria Indicator (RPCI) Criteria cluster RPCI Blog-Type 24.5 Autopilot 27* All Inclusive 7.3 Slice of the Meme-Sphere 15 Scientific 7* False 10* Ethnic 22 Community Building 10.1 Utilitarian Account 20.2 * the average is the rank of a single platform Criteria cluster Userocracy Free Userocracy Conditioned Userocracy Partial Userocracy Aggregate & Create MA Picture Editor Rage Comic Builder Straightforward MA RPCI 7.4 5* 7.8 21.25 10.7 9.6 15.5 19.75 Of content and forms (Browsing, content related features branch) In order for a meme aggregator to be profitable, people must spend time on the platform, creating or consuming, time converted in advertising revenue. The Internet Zeitgeist is not sensitive to the form of the meme – image, image macro, video, GIF or text –, but the Netizens and the devices used by them are. If comparing the RPCIs of the cluster criteria for content 91 FLAVIA ŢĂRAN forms, the All Inclusive MA, with its variety of meme forms appears to be more popular than the Slice of the meme-sphere MA (7.2<15). A complete meme-intake experience would include memes of all forms, shapes and sizes, and in the context of platform which “discriminate” on the basis of form (due to lack of interest or technical know-how) could be considered a shortcoming of the platform. 9GAG, a very popular MA platform, has evolved over time so that it can cater to any type of content. 9gag.com was initially image-oriented, then script to support GIFs was added, and it later launched 9gag.tv (with video links on 9gag.com), creating a well-rounded experience, to name one example. When the criteria clusters referencing a platform’s content were too specific to formalize and integrate in the aforementioned criteria cluster, we created what seem to be exception (illustrated with a singular entry), like knowyourmeme.com and imgfave.com. These, however, are not anomalies or exceptions, but two very distinct cases of platform, where not only the form, but the also the structure are considered relevant. Even though so far we have not identified a platform similar to knowyourmeme.com, in content, architecture, structure and inner workings (submitting content procedure for example), the entry remains open for additions. Imgfave.com, a very structured image repository, nudged its way to our final platform count due to rather popular sub-sections/community with funny content and GIFs, earning the title of False MA, but an MA nonetheless. Browsing and mobility (not featured in Figure 2) The decision not to feature these browsing and mobility patterns (explained in detail in Table 3) comes as a result of the not too narrow, not too wide take on website features. While it is important for a user to browse through the content in a comfortable manner, this is too closely related to the forms of content and the way they are stored (Reddit is a link aggregator, so it will always link externally, thus making browsing slowly on the desktop version, while the mobile application behaves in a very different manner). Even though these features are too specific for the criteria cluster taxonomy, they need to be mentioned as characteristics of meme aggregator sites. The mobility option within a platform can reflect the form, even the content of some memes. For example, some have created memes that would work only if the content would be scrolled, with the punch line at the end of the scrolling process. This type of content would die if featured in a wall of thumbnails. Browsing-sensitive content is a new reality of internet memes, so browsing options can make the difference in a meme’s life. 92 THE STRUCTURE AND DYNAMICS OF MEME AGGREGATORS Table 3: Browsing and mobility patterns* Pattern Description superficial & Two ways of browsing the content: superficially meme-by-meme scanning thumbnails of browsing through every browsing meme, previous-next. meme-by-meme Scrolling through memes (infinite scroll or browsing numbered pages) and previous-next browsing (a more thorough approach). slow browsing Each entry is a separate page/external link, resulting in a click &back button browsing, inherently slow. examples funnyjunk.com memeguy.com 9gag.com imgfave.com dailyfailcenter.com reddit.com knowyourmeme.com tickld.com 1cak.com * the examples are from the 20 browsing oriented platforms, minus the two Exclusively browsing ones The trade-off (Contributing branch) This is the branch where the staple barter of the internet happens: personal data for access. When creating an account, the amount of personal data asked of users can vary. It is very common for Sign Up forms to include Facebook, Twitter or other social media integration, usually as an option to entering your e-mail address (see Table 4). The trade-off translates into access to the decision-making table: what will the most popular memes be, what will people share on their social networks in the near future. This trade-off can be more or less favorable for the user. Table 4: Data on sign up features* Feature Facebook integration Twitter integration Google+ integration Yahoo! integration E-mail address E-mail and at least one social network integration Only e-mail address (no other integration) Username and password Only Facebook integration More information (birthdate, sex) No sign up required From which are meme generators % 33.3% 16.6% 16.6% 3.3% 46.6% 30% 16.6% 13.3% quickmeme.com 10% 36% 63.6% *calculated from the total of 30 platforms 93 FLAVIA ŢĂRAN We must consider the next two levels of human interaction within platforms that (may or may not) require sign up. The 1st level of interaction refers to co-commenting on the same post or replying to a comment, a form of interaction visible and open to everyone. The 2nd level of interaction is closely tied to community-building features implemented on the platform (create a profile, chat or send private messages to other users, create a friend list) and the features for creating a loyalty bond with the platform (karma points, trophies, awards, badges). In this sense, we evaluated the authentication process in two ways: the one that leads to community shaping and a deeper connection with the platform, and the one that leads to a utilitarian account (this account is used as an activity dashboard). Community building can determine users to spend more time on the platform, engaging in both meme consumption and creation, while socializing with other meme enthusiasts. Platform like FunnyJunk and Reddit have large followings due to these 2nd level interaction features, transforming them in genuine creation and debate hubs. The decision-making process (Contributing branch) People accessing meme aggregator sites do it for several reasons: to browse (with the possibility of sharing memes on their social networks), engage with the content and with other users (through comments and votes), or to create new content. Contributing with comments and votes is the most mobilizing and often most clear and quantifiable aspect when describing meme aggregator sites. The comments add context and humor to the meme, and if the comments, as well as the posts can be up/down, the most popular content and the most popular opinions will always rise to the top, even spawning new memes. This creates a democratic-like system within the meme aggregators: the userocracy. The users are in control, while their power and willingness to be a part of this process shape, in a fundamental way, the life of internet memes. The Partial Userocracy is an oxymoron: if the operations are limited (only voting features implemented), then it defies the meaning of the userocracy. Regardless, within this complete/incomplete binary division, preferences can be formalized (RPCI 7.4 < 21.5) and reveal important features of MAs, shaping the bigger picture. We must emphasize that these number are relative and not necessarily a result of these criteria clusters: sites are rebuilt, some architectural features become the norm, so we cannot interpret the relation between some features and popularity, but we can speculate and re-arrange the criteria to create broader contexts for popular sites. 94 THE STRUCTURE AND DYNAMICS OF MEME AGGREGATORS The creating & uploading branch The human is often lost in the process of contributing with content to a MA platform. While commenting is nominal to some extent, the meme as a volatile cultural product and the bond with the original creator can easily be severed. Appropriation happens when a platform (automatically or not) adds a watermark to the content or does not offer the original source, if there is one. This can have serious repercussions (a number of web comics and photographers have sued aggregators for copyright infringement), but for the regular user, this is not usually the issue. In this scenario, some meme aggregator sites try to embellish the experience one has on the platform by offering creative tools on the go. The Aggregate & Create sites may put to the user’s disposal image-macro builders, picture editor with a variable number of functions or rage comic builders. This enhances the experience and can determine people to spend more time on the platform, creating new content. The Straightforward MA is the platform where one can only upload content or provide the URL. This can reflect on the time spent on the platform and on the ratio of novel and exciting content to second-hand memes (RPCI 10.7< 19.75). Even more so, when uploading original content on MAs or when remixing visual content, the author is asked to provide a title for the creation, a bate to attract people into clicking. When the content is uprooted and reaggregated, the title, which may contain a catchphrase or the punch line can be lost. Having the tools for binding the text and the image in the upload/submit form could be considered an advantage, for both the creator and for the life of the meme. The Meme Generators The Meme Generator platform behaves in a very distinctive way. Even though we see the MG as a separate part of the meme aggregator family, the aggregation is a minute part, a side effect of the creation process. The meme generator is a platform that offers a single form of content: the image macro meme and it aggregates templates. Netizens can add new captions to already existing templates or provide their personal visual content. What the meme generator platform has to offer is a large database of visual content and a module for adding text, upper and lower caption, usually with the default Impact font. 95 FLAVIA ŢĂRAN A possible life cycle of an image macro meme could be the following: somebody add an image with a witty caption on a MA site, the image is stripped of its original caption and remixed, but still using the original caption as a pattern, the template is uploaded on a MG site where people try to produce the most enticing and humorous remixes, these are picked up by MAs (completing a circle), the new image macro is studied by Know Your Meme, waiting for a status: Confirmed or Dead Pool. From a functional standpoint, MGs are more rudimental than MAs, using very little or none of the features from the browsing and contributing modules, being specialized in few things: uploading/submitting URLs and adding captions. We extracted the next reoccurring characteristics (some explained in more detail and with examples in Table 5), in order to create a better understanding of these platforms:  not very contributing oriented (the comment section is a rarity);  not very browsing-friendly;  sign up is rarely required, especially when it comes to recaptioning memes (may be required for uploading templates);  voting system and sorting by popularity options may exist (Democratic MG);  some platform may explain the origin of the template and the pattern the caption should follow (Explanatory MG);  some platforms are stripped from any other functionalities and only serve as a template database with a re-captioning feature (Pure MG). Table 5: Meme Generator characteristics and examples Characteristic Ethnic Explanatory Democratic “Pure” 96 Explanations Examples Captions mostly in other languages; haciendomemes.com; some image macro templates and text memegenerator.es are specific to a certain ethnic group/ country. The caption pattern is explained, so haciendomemes.com; makeameme.org; that the memes are consistent. memegenerator.net. Feature a voting system, also more diylol.com; memecrunch.com; browsing friendly. memegen.com; memegenerator.net; troll.me. Sole purpose to create memes (no haciendomeme.com; livememe.com; comments, votes, account). makeameme.org; memegenerator.es. THE STRUCTURE AND DYNAMICS OF MEME AGGREGATORS Meme generator sites are tools used to produce content that will usually end up on a meme aggregator because, in some cases, the MA does not have a built-in re-caption feature or the user is not aware of that feature. Regardless, meme generators are a subsection of meme aggregator sites, with own rules and audiences, keepers of a very specific brand of internet memes. We refrain from a clear statistical overview for this section of the taxonomy due to the small size of our sample (only ten platforms), and even though we feature them as highly specialized meme aggregators, their architectural features are much more intricate and need a proper analysis framework, different from the MA one we created for this research. An extended paper on the structure and dynamics of meme generators could look into the specifics of the technical layer of such platforms and how they are used in the context of the “complete meme aggregator site”, which features all four modules. Discussions and conclusions The clustering criteria approach, subjective as it might seem, brought us closer to understanding the structure and dynamic of meme aggregator sites, closer than a narrow but more precise description of architectural styles. Our taxonomy of characteristics is modular, providing a framework ready for adjustments and adjunctions. The broader discussion regarding this taxonomy is closely related to the two layers of every new media object: the technical layer and the cultural layer. The cultural production (the actual memes, but also the opinions and catchphrases born in the comment sections, the votes that propel or drown the memes) can only happen if the web developer implements features to encourage these online behaviors. Meme aggregators are part of the industry – IT and cultural –, capital is invested, used for development or studies, in order to minimize the gap between the moneymaking idea and the actual implementation, gaps profoundly visible on sites with a lower rank, trapped in the vicious circle of popularity and revenue gained through popularity. Given that websites can change and improve in functionality, the examples chosen to illustrate our criteria cluster taxonomy are not set in stone and can become obsolete at any moment in time. Pundits would argue about the relevance of this rather ephemeral taxonomy, but we know that apart from being a tool for identifying the most popular and sought after characteristics, modules and meme aggregator sites, it raises new and troubling questions about our browsing and consumption habits, web presence and comfort 97 FLAVIA ŢĂRAN patterns (feeling at large on a specific platform, creating and nurturing a social network associated with a meme aggregator), only to name a few of the research opportunities this paper opens. Furthermore, the algorithm created to determine the most popular and relevant meme aggregator sites of the moment (complete list plus Alexa ranks in the Annex section, Table 6), can be improved and extended for other types of visual content. The final tally of the most popular 30 meme aggregator and meme generators sites is the result of automated and manual processing, and while the endeavor to create such a top using an automated and self-made tool could have left space for errors and anomalies to infiltrate, this is the first such classification ever made, based on a research inquiry. Our modular taxonomy defines meme aggregators as web platform where people can ca do one, all, or a combination of the following: browse memes, contribute (with votes and comments), create (with the means offered by the platform) and upload content/submit URLs (original creations or not). These four actions assure meme creation and aggregation, and empower people to be part of popular culture. These actions can be broken down into criteria clusters, but going all the way to the molecular level, to the exact features and the specifics would render this model unusable. And so, to answer RQ2, the most common features of meme aggregator sites reference (1) content and content forms, (2) browsing patterns and mobility, (3) sign up implementation, (4) commenting and voting features, (5) creating opportunities. These are the building block we isolated in our analysis of meme aggregators, even though not all are implemented on all platforms, so this knowledge can be used to identify a platform’s shortcoming. To answer the third research question, regarding the extent to which users can comment and vote, we identified that this brand of contribution entails a trade-off: data for access. While the type and amount of data one must trade depends on what the web developer/web entrepreneur wished to accomplish, on 30% of platforms one can choose from creating an account by providing an e-mail address or by logging in with another account (Facebook, Twitter, Google+ and others). However, MAs built on complete anonymity, apart from most of the meme generators, can exist, funnyjunk.com being the prime example, and a rather popular one (Alexa rank 2,321). But to answer the questions, the userocracy and the partial userocracy are the extents to which users can contribute, providing that the platform has the required features implemented. 98 THE STRUCTURE AND DYNAMICS OF MEME AGGREGATORS While site popularity can be quantified using proper metrics, like time and number of pages viewed (the way alexa.com is approaching this), quantifying the popularity of certain architectures of meme aggregators is impossible with the data we gathered. This impossibility is explained, again, by the potential gaps between the cultural and the technical layer. The Relative Popularity Criteria Indicator is a rather weak metric because it is based on small samples and indicators of site popularity, so the popularity of the site and the popularity of the criteria cluster cannot be separated, that is why the RPCI is not used as a prime indicator in this research, but as a context constructing one. In this case, we cannot pinpoint the most popular meme aggregator site architectures, but what we can do is to see what modules are implemented on high-ranked sites and draw individual conclusions (an extended version of this paper would include questionnaires for MA users and contributors). Rehashing an idea emphasized throughout this paper, the problem with meme aggregators is that they are, like the majority of websites, created as revenue making machines, and for this to happen they need to create interest. Even though some MAs could seem very nurturing for popular culture and interested in mobilizing people into having a hands-on meme experience, at the end of the day, the comments, votes, content uploaded or created is money. But aside from this, understanding the structure and dynamic of meme aggregators in an abstract manner, leaving aside the lines of code and like buttons and embracing it as a Habermasian public sphere for all that is memetic, not only adds meaning to our lives (in the words of Fiske), but constructs a radiography of how we relate to internet content, out internet communities, critical thinking and memes as a means to understand and shape society. To conclude, this paper on the inner workings of meme aggregator has brought into perspective the technicalities of creating such a platform, the features people have grown accustomed in their meme intake and an innovative way of creating a top of the most popular MA sites. 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New York: Bantam. 101 FLAVIA ŢĂRAN Annex Table 6: Top 30 meme aggregators ID 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30 Occurrence ID* 762 383 146 459 271 118 227 192 83 167 355 123 261 77 134 48 57 248 138 40 63 104 316 127 64 34 114 49 34 37 alexa.com rank** 62 1,237 51 5,503 2,124 280 2,383 4,135 1,007 10,801 26,442 11,111 43,826 13,139 30,716 1,007 1,610 109,818 70,106 1,157 14,108 75,552 706,923 238,416 50,957 1,300 310,868 28,095 8,280 14,151 Website reddit.com quickmeme.com imgur.com memegenerator.net funnyjunk.com 9gag.com knowyourmeme.com memecenter.com cheezburger.com imgfave.com memecrunch.com imgflip.com troll.me makeameme.org risovach.ru memebase.cheezburger.com tickld.com memeguy.com diylol.com livememe.com dailyfailcenter.com memegen.com thefunniestpictures.com haciendomemes.com memecreator.org themetapicture.com redditpics.com memegenerator.es cuantocabron.com 1cak.com Main action browse browse browse create browse browse browse browse browse browse create browse create create browse browse browse browse create create browse create browse create create browse browse create browse browse *Number of times the website was listed as featuring memes, after the Google Image Search step. ** Data collected from alexa.com in March 2014 102