Consumption of Metapatterns
A CDT Model for the Understanding of Patterns in New Media
This paper focuses on digitally mediatizated patterns and on the impact their representations might make on users. Hypothesis: new media merge communication-technology with users’ networking and social conduct and, consequently, they constitute metapatterns framing society and social networks. Platforms and contents are vehicles for messages and data for the purpose of identification via interfaces; and platforms with uploaded/formed universal or personal contents might as well generate user-experience. Consequently, we need to find the main directions among new media phenomena in order to interpret digital mediatization and its impact on contents and user experience. This paper illustrates the new media metapatterns of convergence, divergence and transvergence and frames them through a CDT model that can be used to map both the dynamics and the consumption patterns of new media development.
New media devices/tools, platforms and interfaces rewire social-cultural and network-communication. The result is or is not a user experience. This paper focuses on the digitally mediatized patterns and their representations with some impact on users. Our goal is to depict the main trends in patterns of communication, that is, to explore the mainstream operations/activities of digital mediatization. This paper target the study of constituents and patterns of new media. The main question is what attributes of new media reflect patterns of social communication? What synergies depict digital media? How can user experience account for it? According to my hypothesis new media merge communication-technology with users’ networking and social conduct, and, constitute metapatterns over society and social networks. Media supersize the social into the hype(rsocial). A model that incorporates the mainstream dynamic of new media gives us a chance to study patterns of digital mediatization and it will interpret complex user experience phenomena via compact patterns.
Historical Background and Trend
Digital and global media use personal communication as an interplay (Adler et al, 2012) for identity needs, social needs and practical needs, but the fourth type of needs − like its physical analogies − in this context are illusions: environmental and communication noise are virtual. Digital and global media are at least as far away from interpersonal communication as conservative media. The keywords of conservative media are one-way communication, mass, audience.
Theoretical models of communication and conservative media based on these earlier concepts: inter alia classical model of communication with information source, message, transmitter, signal, channel, noise, receiver (Shannon & Weaver, 1949) information transmitted model (Lasswell, 1948), ritual view of communication (Carey 1975), propaganda theory (Elliott, 1972) and reception/coding-decoding (Holub 1984; Hall, 1980). These phenomena and impact are also omnipresent in new media — but with interaction and real time activity.
It assumes a frontal stage/scenario between media and people. In order to process a discourse on new media we need to update some keywords and to set up categories of interpretative communication and media. “Verbal and non-verbal communication”, “channels”, “asymmetry in communication” have lost their former meanings in the global network of the media and user generated content phenomenon. Now the impact of media comes from an interaction via mediatization, virtualization and augmentation.
New media have been rapidly becoming mainstream media around the world. Many kinds of platforms and interfaces facilitate communication with contents and sharing files/links. Conservative media consumption has been converting for digital platforms and devices. 100 years ago the audience spent only a few hours a week consuming media. In 2020 this will be nearly 90-100 hours per week (WAN, 2008).
Media change in the global and online environment fluently. It has come around with digital media, with interactivity, and, especially, with networks, links, navigation, platforms and interfaces. New media have merged earlier media formats with digital binary coding and have developed different platforms trafficking contents. The human factor is involved in this via inter/activity constituted by interplay, audience function, media consumption and patterns of information and communication architecture.
Links and patterns give explanations of how these are organized and, practically, how we use them. First we reach connect to (wider or limited) interactive platforms and via platforms we get access to contents and process them through our networks. The important question is the function of user experience. To communicate via new media is to be peer-reviewing one another which results in a mutual multifaceted authentication-via-collaboration. This is the co-production of our/selves via algorithms, interfaces and platforms. This is our “rhythm” according to which we operate with/in new media.
If the dynamics cannot be recognized if you get handicapped/ a blockage or a/the structure is not recognized, the user may get confused. User’s attention, her/his inter/activity, her/his digitalized lifestyle may determine patterns of interactivity and the choices of platforms and viceversa.
Online existence and a multitasking lifestyle might go beyond human expectations. Contents and networks of contents organize user’s work, consumption, entertainment and everyday life via platforms and interfaces. Companies have been laboring for users’ attention offline and online, respectively. Contents also transmit messages and data to audiences, spectators and users across conservative media channels and digital platforms. The context has finally become digitalized: the majority of global written, recorded and digitalized cultural contents are available online via various networks interactive platforms. Its visible result has been media convergence, where media technology, devices, platforms and online multitasking commute.
Platforms and interfaces host virtual/augmented contents. The question is how data and messages traffic within digital networks and platforms, how users communicate with digitalized messages? Contents are organized (panelled and packaged) for platforms and for interface orchestration − that is, for trafficking − purposes. Patterns of data and messages constitute contents via textual, visual or/and audio content panels or via mixed types in convergence. These mean links for identities to connect to global or local networks with their platforms and emerging/emergent interfaces — generate/reproduce other contents.
“Mass” frames of content, like the Google search engine, Facebook, Twitter are based on user generated content. These are the converged and mainstream links to familiar, reliable, frequently used tools to search, entertain and groom. Convergence repacks and redirects contents in virtual destinations: this is the logistics of data processing on different platforms with homogenized or variant patterns in new media. We are living in a convergence culture (Jenkins, 2006).
What does convergence mean exactly in this case, especially with multitasking? “With convergence, we ask, are people now using more than one medium simultaneously, that is to say, are they "multitasking?" Is that a way of squeezing more mediatized participation into the same time slot?” (Enoch & Johnson, 2010; p. 127). The answer is found in the question: convergence does not imply a reduced use of alternative media on account of simultaneous usage. “People use different platforms at different times in different places for different purposes” (Enoch & Johnson, 2010; p. 136). Users have choices of platforms and sources while searching in the age of new information and communication technology.
They demand and they are curious to explore niche solutions, individual and personalized tools and they can experiment with new platforms, genres, open sources, and with various other online devices/tools/solutions. If convergence is a well-known logistic feature of new media what logic is at work in this field? We may also want to depict the ones outside domains of convergence yet keeping on coming out of/in new media trends.
An Introduction to the CDT Model
How does impact operate between technological trends and social-cultural change? Which correlation explains mutual interactions? Theories of technical and media determinism (Innis, 1950; McLuhan 1962; Ebersole, 1995) assume that innovations in general technology and communication technology are implicated behind social and cultural change. If we use media, so do media use us — including our activities, attention, identities, messages, and so on.
Trends in the media intersect, typically, in distribution of contents via platforms, real time search engines, social networks, focusing on user feedback. Trafficking online contents, messages and data may be processed through alternative and mainly or party independent communication networks besides mass media. This phenomenon features in the theory of media determinism. New media platforms and interfaces rewire social-cultural, personal and conservative media communication in the age of the digitalization.
In what ways would media environments and emerging forms of the media change and what phenomena and trends could generate this? Which one of them shapes new media determinism in researches concerning communication socially and technologically? Which directions mean mainstream and which are crossroads?
The CDT-model model of new media provides the means with which the relationship among platforms and patterns of online contents can be examined. The next hypothesis has shaped: platforms and contents have common patterns. These patterns are those of convergence and divergence/transvergence in new media, and produce a model with three directions: mainstream approach and distancing − digital devices like tools, platforms, interfaces and user activities/using/loyalty. And it also means merging these with redesign/rethinking these in the form of innovation or by underground habits.
From the Hype Cycle to the CDT Model
Many kinds of platforms and interfaces facilitate communication with contents and sharing files/links/contacts with contents. Hype trends have determined these patterns. Gartner's Hype Cycle Special Report summarizes and illustrates the common pattern of over-enthusiasm, disillusionment and eventual realism that accompanies each new technology and innovation to strategic planning from 1995 (Fig. 1).
The chart points out the dynamic change in media and communication industry in synergy with information technology. Devices (e.g. media tablets), platforms (e.g. clouds), interfaces (e.g. different applications for smart tools) is forming the new ways for human connections and communications, like human augmentation, virtual worlds, gesture recognition softwares and so on. Real human experience becomes a virtual and augmented experience. People are users in this phenomenon. They use platforms, interfaces and digitalized contents to exist and to communicate their existence. Online existence and a multitasking lifestyle reach beyond human expectations.
Contents and networks of contents organize tropes of identity and everyday life. Companies have been labouring for users’ attention offline and online, respectively. In fact the contents have been digitalized, therefore the majority of global written, recorded and digitalized cultural contents are available online via various networks interactive platforms that provide the/a context(s)-online. Weight of digital media in these hypes assumes other types of new media dynamic undoubtedly. Convergence tends to be working to peak within the framework of interactivity. Ups and downs sustain exploratory, experimenting, wilding, not-competitive services. Everything depends on the details: several tools and services remain invisible for hype cycle reports.
CDT: Convergence, Divergence, Transvergence
Users are connected to a global network with its platforms and emerging/emergent interfaces. A platform is an inventory of contents. Interfaces represent and facilitate interaction — between users and various platforms, and, also among platforms. Contents are organized (panelled and packaged) for platforms and for interface orchestration − that is, for trafficking − purposes. Patterns of data and messages constitute contents via textual, visual or/and audio content panels or via mixed types. Focusing on network functionality and new media consumption a content finds its way to the user via platforms and interfaces.
Popular frames of content are e.g. Google search engine, Facebook, Twitter based on user generated data and messages. Facebook hits 1 billion users online in 2012. “The popularity (...) is due in large part to their viral nature.” (Steinman & Hawkins, 2010). If a platform reaches a tipping point it is turning into a mass medium. Global digital media feature (e.g. iPad, Adobe software) convergence: mass consumption is one of their primary digital media characteristics. Convergence repacks and redirects contents so as to deliver/ arrange them to their proper destination or place. Convergence is the logistics of data processing. Platforms are their forums of/for exchange and (re)direction.
Association for mass media models, for instance the spiral of silence (Noelle-Neumann, 1974) we find parallel patterns in social-cultural communication: some people become dominant in generating opinions and messages. “They” implicates a minority and the “mass” does not cover most topics. The difference is that online media give temporary, however archival footprints to reach more users real time (not only show time and repeat programs).
Information/entertainment volumes were selected by active users/opinion leaders via relevance in digitalization. Creators are professionals or amateurs (e.g. bloggers), and, also synthetizers. Controllability and self-regulation provide a framework — not only an institutional background. The results are homogenization (e.g. similar first page on smart phones — Fig. 2.) to develop mainstream devices (e.g. smartphone) and challenging platform independence.
Finally convergence and its impact on human online activity on mainstream platforms is fundamental but it is not an exclusive phenomenon in new media. Several new online services come out day by day. One of the most dynamic areas has been the downloading applications for smart phones and media tablets: Apple App Store surpasses 40 billion downloads at the beginning of 2013 (Apple, 2013). Or there is another field: global systems (e.g. Groupon, Wikipedia) also set up a claim for local, professional, special, individual tools.
Modified patterns indicate other new services and applications (e.g. Qwiki, Ustream, Poken), give alternative usage with open sources (e.g. OpenOffice), and do not provide total control over platforms (e.g. brands in social media) any longer. Users search and find new virtual experiences adjacent to everyday life and for fun. Result: digital developments also show signs of divergence and transvergence.
Divergence generates alternative or special platforms and interfaces. Applications (e.g. GPS to reach ATM’s), mash up social platforms (e.g. 23andMe social media platform with DNA logic), several startup companies (e.g. prezi.com flexible zooming against Power Point static and linear slides) specializing in digital services mark and represent divergence.
Further hundreds of thousands of new applications and innovations are specializing in digital services featuring divergence. Most of them are visible enveloped in media noise and some of them get wider publicity.
The widest popularity means final convergence that has updated earlier convergences. Divergence is essential: it provides alternative answers for paradigms of media convergence. It is twofold dynamic: one of the driving forces is business and development industry, the other is desire for novelty by users.
Transvergence of media sets up an intersection of convergence and divergence focusing on contemporary and future media. The idea of transvergence comes from media art terminology (c.f. Novak, 2011) to let media research embrace science, technology, culture and art.
New media platforms, interfaces and contents open the door to collaborate and to filter supplies collectively (c. f. Anderson 2006). Users, developers, companies and “geeks” can co-operate and invent because of interactivity, that is, because of the substance of new media.
Collaboration is a possibility — without any commitment. However if a collaboration is successful the public produces engagement individually and collectively. In other words transvergence combines platforms, interfaces, contents and genres — where process and participation become essential.
The globally famous game, “Angry birds” is a transvergent media platform for interactivity and collaboration with users, companies − their networks included −, contents and offline/online tools. The curriculum service, the crossmarketing with IKEA promotion/interior, fashion design via one Angry birds element are extensions of the original media platform (Figure 3).
Patterns of content depend on platforms and on their interfaces — and vice versa. However, this summary has also depicted metapatterns in new media trends that define updating processes.
The metapatterns in new media are: convergence, divergence; and transvergence. They comprise the CDT model for new media. These metapatterns determine the evolution of media and represent technical, social and cultural change.
Fifteen billion devices will be connected to the internet in the coming years with smart devices — a steep, quick rise (McDougall, 2011). Metapatterns can help to figure coming trends: divergence will be wider, convergence will generate new special features, transvergence will integrate them.
The ways of the media have been changing: users and companies have generated content with reference to, and, in interaction with, a global context. Patterns of contents depend on platforms and on their interfaces — and vice versa. However, this paper has also demonstrated metapatterns in new media trends that mark updating processes. Convergence, divergence and transvergence are metapatterns in new media. They determine the evolution of media and represent technical, social and cultural changes.
The next question is the rate of offline and online presence and activity within digital networking: if a user communicates with networks for more than 90-100 hours: how are new platforms, contents, genres changing and what attitudes constitute a multitasking lifestyle and behaviour. Metapatterns can help to figure coming trends: divergence will increase, convergence will generate platform and content globalization and transvergence will integrate/mix/select them.
Interpretations of the CDT model of new media provide explanations for phenomena of remixed media. In new media various mediums and users are being linked. It is a networking of media tools, channels, genres, users and user-experiences within a digitalized context. New media connect, merge and cannibalize former ways of communication and produce a complex system as CDT patterns. This is implied in the concept of ‘hypermediatization’, remixed mediatization that generates the semantics and pragmatics of digital media.
The fundamental principles of human communication have not changed — their ways and patterns, simply, imply an alternative logic (like in case of Facebook — this is pure convergence). Patterns of platforms and user experience intersect in design, architecture, traffic and context. Users upload platforms with contents and they also meet with difficulties: the pattern matching a platform may, possibly, not be compatible with the pattern of the content if the post office rejects my pack of information I intend to send by pos[t](ing). This results in a compromise and in a shared pattern which is, by its nature, also, an interface, or, it may result in a novel generation of platforms and in retooled contents. Up- and downloading retools contents and generates interfaces: tables of contents.
- Adler, R. B., Rosenfeld, L. B., & Proctor, R. F. (2012). Interplay: The Process of Interpersonal Communication. 12th ed. Oxford University Press.
- Anderson, C. (2006). The Long Tail. Why the Future of Business Is Selling Less of More. Hyperion.
- Apple (2013). App Store Tops 40 Billion Downloads with Almost Half in 2012. Press Release. http://www.apple.com/pr/library/2013/01/07App-Store-Tops-40-Billion-Downloads-with-Almost-Half-in-2012.html. Accessed Mar 2014.
- Carey, J. (1975). A Cultural Approach to Communication. Communication. Vol. 2. Pp. 1-22.
- Ebersole, S. E. (1995). Mediadeterminism in Cyberspace. http://faculty.colostate-pueblo.edu/samuel.ebersole/mdic/index.html. Accessed Jan 2013.
- Elliott, P. (1972). The Making of a Television Series — a Case Study in the Production of Culture. Constable.
- Enoch, G. & Johnson, K. (2010). Cracking the Cross-Media Code. Journal of Advertising Research. Vol. 50. Issue 2. Pp. 125-136.
- Hall, S. (1980). Coding and Encoding in the Television Discourse. In Hall, S. et al. (Eds). Culture, Media, Language. Hutchinson. Pp. 197-208.
- Holub, R. C. (1984). Reception Theory. A Critical Introduction. Methuen.
- Innis, H. (1950). Empire and Communication. Clarendon Press.
- Jenkins, H. (2006). Convergence Culture. Where Old and New Media Collide. New York University Press.
- Lasswell, H. D. (1948). The Structure and Function of Communication in Society. In Bryson, L. (Ed.). The Communication of Ideas. Harper. Pp. 32-51.
- McDougall, P. (2011). Intel Sees 15 Billion Devices On The Cloud By 2015. http://www.informationweek.com/desktop/intel-sees-15-billion-devices-on-the-cloud-by-2015/d/d-id/1097695. Accessed Apr 2014.
- McLuhan, M. (1962). The Gutenberg Galaxy: The Making of Typographic Man. Toronto University Press.
- Noelle-Neumann, E. (1974). The spiral of silence: a theory of public opinion. Journal of Communication. Vol. 24. Issue 2. Pp. 43-51.
- Novak, M. (2011). Transvergence, Specificity, and Civilization. Lecture — MAT, University of California. http://www.mat.ucsb.edu/595M/?p=416. Accessed Mar 2014.
- Shannon, C. & Weaver, W. (1949). The Mathematical Theory of Communication. University of Illinois Press.
- Steinman, M. L. & Hawkins, M. (2010). When Marketing Through Social Media, Legal Risks Can Go Viral. Intellectual Property and Technology Law Journal. Vol. 22. Issue 8. Pp.1-9.
- WAN (2008). Worl Digital Media Trends Report. http://www.wan-ifra.org/.