To Gideon Rosenblatt and David Amerland
The metamorphoses of the written word and the media they exist and evolve within are ubiquitous and require us to rethink the way we conceive and craft content. If we want to use text to its fullest potential and not “drive a Boeing 747 on a highway” or “use the computer as a paper simulator rather than as a window to the great new shared world of the human culture (as Ted Nelson ingeniously put it in an interview Machine That Changed The World, The; Interview with Ted Nelson, 1990) we are to add to our understanding of texts the perspectives of semantic networks and algorithms.
The Semantic Networks We Think By
Right now, I can think of at least three ways to share with you the semantic networks that emerge in in my mind when thinking about the Web and its all-important relation to the processes of writing nowadays.
The first one has to do with a rabbit. The second – with a falling stone, and the third is connected to Barthes.
Don’t think of a rabbit.
Alice in Wonderland. Tim Burton’s read of Alice in Wonderland and Johnny Depp as the Mad Hatter. What else? The Matrix, and again that rabbit thought: “follow the white rabbit” on a screen and a rabbit tattoo.
The stone of the rabbit inevitably created ripples (spoiler: a blast of connected semantic networks) in my mind. Just as Gianni Rodari beautifully described in his Grammar of Fantasy.
The Falling Stone
Take the word stone as an example. When it falls into the mind, it drags words after it, bumps into words, or avoids them. In short, it comes into contract with them in different ways:
These are the easiest associations. A word collides with another one through gravity. This is hardly sufficient to ignite sparks (but one can never know)
Meanwhile the word falls in other directions, sinks into a past world and lets sunken existences emerge.
cit. Grammar of Fantasy, p. 5
Speaking of ripples and emerging meaning Barthes is a treat to resort to when text, understanding and meaning are being scrutinized.
Exploring a diverse range of ideas in the field of text analysis, Barthes brings the mezmerizing view of texts as tapestries of multiple writings, drawn from many cultures, born in a dialogue and enacted only in their reader’s mind.
The text redistributes language [. . .]. One of the paths of this deconstruction-reconstruction is to permute texts, scraps of texts that have existed or exist around and finally within the text being considered: any text is an intertext; other texts are present in it, at varying levels, in more or less recognisable forms: the texts of the previous and surrounding culture.
Cit. Roland Barthes, “Theory of the Text,” in Robert Young, ed., Untying the Text (Boston: Routledge & Kegan Paul, 1981), pp. 31-47.
Even this tiny glimpse into the vast work and thought space of the French philosopher, linguist, critic, and semiotician, provides a ground for exploring text on the web from the perspective of a multifaceted entity which meaning emerges only in a collision with the recipient’s mind, or in tha paradigm of this article, with the semantic networks the recipient thinks by.
This dissemination and further multiplication of associations is very well described in the video below. The video was generously provided by Angel Marchev. It is an Instruction for the course “Theory of Management: Cybernetics and System Theory” with authors: Angel Marchev 1.0 and Angel Marchev 2.0; Text: Angel Marchev 2.0; Animation: Michaela Komitova)
[The video is in Bulgarian, but there are English subtitle available, tun them on :)]
A set of associations to help and foster understanding, semantic networks are what algorithms are built to use as pathways of associated objects as to “make sense” of things and process information. Now let’s look at understanding and meaning from the perspective of algorithms.
The Semantic Networks Algorithms Tame Text By
On an average day, people around the world come into contact with hundreds of algorithms embedded into the software that operates communications, utilities and transport infrastructure, and powers all kinds of digital devices used for work, play and consumption. These algorithms have disruptive and transformative effect, reconfiguring how systems operate, enacting new forms of algorithmic governance and enabling new forms of capital accumulation.
The reason we need to pay attention to semantic networks and the algorithms made to understand them, is the increasingly important role machines play in the writing practices. Take the 4 elements of writing Terje Hillesund describes in Digital Text Cycles: From Medieval Manuscripts to Modern Markup:
- Writing (authoring)
- Reading (consumption)
As I wrote in Linked Data for Libraries: Our New Librarians:
In the digital world of constant connectivity, the main forces of oblivion translate into lack of visibility and poor information retrieval techniques. That said, the “war with the forces of oblivion” will take not only trained and devoted librarians but also some algorithms, capable of fetching relevant results quickly and efficiently.
Woven out of electric words, a digital text is also a tapestry of semantic networks, that algorithms can follow to decipher what the text is about and what meaning does it contain.
I know many web writers are still reluctant to embrace the idea of thinking about the fields of information retrieval, extraction, knowledge management and other things, recently finding their way in the public space under the umbrellas of AI and Machine learning, but for sure it pays off. And it really is time to talk about Knowledge Representation when approaching any web writing project. For “whatever its form, text is everywhere and it must be dealt with by people and programs” (cit. Taming Text, p. 14)
The Semantic Networks We Write By
The way I approach web writing, knowing that the Semantic Web* is my medium, is:
- Incorporate Information retrieval and extraction in my understanding of the text within the greater context of the web and the seemingly smaller context of the domain it emerges in
- Recognise the existence of both human-to-human and algorithm-to-algorithm interchange
- Think in terms of building semantic networks, or, put simply, weaving webs of relevant words
- Respect the environment I create content in, its interconnectedness and the Web of Trust we are all heading to.
*Semantic Web technologies slowly but steadily are changing the way we write, read and manage texts. This change goes hand in hand with the transformation of the environment we live and communicate in. For me the Semantic Web informs a deeper perspective of the way I connect with audiences together with the way I serve them through writing. Simplified, the Semantic Web is a web of semantic networks for agents to process information on our behalf. Very simplified, think links, linked that connect data, links that carry meaning themselves. For more, check my article: Semantic Web, Relationships and a Piece of Conceptual art
Also, if you are willing to expand your awareness of neural networks, language, communications and machines, head to David Amerland’s post A quick introduction to Machine Learning and also Gideon Rosenblatt’s magnificent find and write up on how language emerges in our brains: Mind Reading Research Sees What You Mean
Towards a Broader Perspective of Web Writing
This last paragraph I want to leave you with is an example of a living text, a semantic network colliding with another one.
It was born in the interaction with Hassan Soubhi, a student at my course Content Writing in the Semantic Web. He asked me:
Does the expression Semantic Web refer only to written text? Can we take the word Text to mean all forms of content on the web? This is not just about written text; it also includes videos, images, etc. The meaning is sought within all these forms.
The question went right into the heart of the relationship between the Semantic Web and us as content weavers.
To go into more detail, in the vision Sir Tim Berners-Lee has for the Semantic Web – it is a web where personal assistants understand all kinds of information – be that our calendars with appointments, our notes, our voice, asking them: Do I have something to do tomorrow.
To get in the very practical side of all that Semantic Web talk, nn example of videos being used for a dance school comes to mind. With the help of Semantic Web technologies, videos were “read” by machines and various moves were categorised and made available to those who search for them. The case study is pretty interesting: Using the Semantic Web to Enhance the Teaching of Dance.
That said, it’s time to leave you … imagining. Imagining the possible futures of web writing and content creation in a world where you ask a machine to process your videos, recognise the things you need and classify them for you to be able to access them whenever and wherever you will need them.
A world where the semantic networks we write by will be the semantic networks algorithms learn and serve us by.
Call to adventure: I finally got to creating a website for the book I am writing: The Brave New Text it is. The website is slowly finding its way into reality, and I would love to merge semantic networks on it. Come join me there and also please, drop me a line around the web if you feel the need to discuss all things text in the light of the web and the interconnectedness.