Internet companies such as Google personalise information by developing their own algorithms to filter data according to the user and quickly present these statistics as requested. However, this causes problems such as the ‘Filter Bubble’. This refers to an information environment in which a person isolates oneself in a ‘bubble’ of ideas and values similar to one’s own, which is a result of tech companies analysing people’s past behaviour.
Therefore, I proposed two different approaches to solve this problem. Firstly, improving data literacy by promoting an understanding of algorithms. Secondly, the critical practice that incorporates randomness. I thought our own proactive action to obtain information in the midst of randomness could be one of the possible ways to change the current situation. Google Maps, which is the combination of GPS and algorithm, is unique in that it directly produces behavioural changes in our conduct in physical space. Therefore, I considered visualising what kind of algorithm is used to display Google Maps information to us using diagrams. The critical practice known as corporate randomness is influenced by situationists who advocate exploring cities and artist James Bridle’s conception of randomness as being generated in physical spaces divorced from technology. I devised a “random walk” using dice to traverse the city unsystematically, actively collecting information of personal interest during the arbitrary walks. Subsequently, a technique was devised to visualise this collected information using network diagrams. I walked around London, alternating every 15 minutes between Google Maps and dice rolling. I collected the data on Google Maps (information received passively), as well as the statistics I recorded of interest to me (information acquired actively). Both types of information were analysed quantitatively and qualitatively, respectively, and combined with flow and network diagrams to create a three dimensional model that resembles an architectural reproduction.
Upper Layer is a flow diagram showing how the Google Maps algorithm works and Bar chart. Through quantitative analysis, information displayed on the road is divided into six types (recommendation, recently viewed, profit, non-profit, high ranked, advertisement), and it shows what kind of algorithm is used to display the six types.
Bottom Layer a network diagram based on a qualitative analysis of the information actively acquired on the road. The data recorded along the way was classified into six categories (objects, architecture, design, phenomenon, nature, language) . I then made a statement about why I was interested in this aspect or phenomenon, from which I extracted keywords that were particularly noteworthy. The same or similar keywords are connected by lines.
Data Collection
Situationist International, which is also referred to in the critical context, says that the important thing is to ‘walk in the city’. Therefore, I decided to walk from whitechapel station, the eastmost station in zone 1 of London, to notting hill gate station, the westmost station in zone 1. This walk then vacillated between random walks using Google Maps and dice every 15 minutes to compare both the Google Maps algorithm and randomness methods.
Change the Route every 15 minutes
Red Line is the route when I used Google Maps, Black Line is the route when I used Dice. Blue dot is the point I took screenshots by iPad. Nineteen different screenshots were collected between 11:00 and 16:30. I used an ipad when changing the walking method from Whitechapel station to Google Maps and random walks every 15 minutes.
Take photos you are interested in
Collecting visual information using photographs. Philosopher Bruno Latour’s (2007) actor-network theory refers to the importance of treating people, objects and events equally, without distinction. My research is partially inspired by this theory. Furthermore, I believe that the random behaviour of people walking down the street is also a transient event, an object that has fallen, or a person they have met by chance,
and that various factors are intertwined to create the events of the city. In the kōgenghaku developed by architect Wajiro (1987), he advocates collecting the city’s events without dividing them into categories and then categorising them, rather than focusing on them from the outset. I have also decided to incorporate this perspective.
Data Analysis of Upper layer
(Flow diagram of Google Map algorithm
and Bar chart of information of Google Maps by places and time)
Flow diagram of Google Map algorithm
I found that all pages of Google Maps displayed different information depending on the user, whether they were logged in or not, and whether they were zoomed in or out. The next step was to open the Google Maps application and investigate how it is designed. In particular, I considered that information (orange part in this graph) could be divided into six main categories.(I inteviewed the enginner at Google Maps too.)
I decided to divide the information into six particular categories
I created the flow diagram it shows how these six informations are categorized.
By using flow chart of Google Maps algorithm I created like those, I created three dimentional architectual model flow chart below.
Bar charts of information of Google Maps by places and time
When I change the route by 15 minutes, I took the screenshot of Google Maps. After I walked, I combined each screenshot into a single map. It was found that the same location was either shown or not shown depending on the current location. Therefore, it was decided to split the analysis by time (every 15 minutes). In addition, the area analysed was limited to a radius of 1.5 km from our current location.
In order to find out which information was used for the recommendations, the analysis was carried out by comparing maps in the secret mode state at approximately the same time of day as when the data was collected (the content of the maps varied depending on the time of day). As the Google maps contain some information that is not used in this study, I purchased another set of London map data and plotted each of the six categories of placements.
I plotted the dots and changed the colours by six categories.
Quantitative research
It was then found that the type of category displayed varied depending on the region. As the time of day measured corresponded to the location, it was found that even though there was more information on recommendations from 11:00-12:00, there was more information shown to all Google Maps users after 15:00. I suspect that this might be caused by the fact that I often go to East London and therefore the GPS knowledge is more defined in East London.
I categorised these data into five different time periods to make comparisons easier to understand. It is acknowledged that there is some overlap of information in this classification as googlemaps data is collected every 15 minutes.
I created bar chart by those five timezone. the Colour nad position of each colour is related the flow chart.
Data Analysis of Bottom layer
Critical Focus Methodology that Anthropologist Banks (2018) mentions involves sharing information with participants on a micro level. The aim is to then shift focus to the macro-level aspects, including social and cultural contexts. In critical focus theory, the collected data is then divided into broad categories. Thus, I also divided the 101 photographs I took into six categories(objects, architecture, design, language, phenomenon, nature). Following this, I would analyse the visual data through photographs, using words in the form of text. Banks (2018) says As words are particularly important for qualitative analysis, I wrote sentences about why I was interested in the objects or phenomenon from the photographs I had taken and extracted keywords that were particularly noteworthy in the sentences.
The same time period that was classified into five categories in the previous google maps analysis, it was found that the type of information obtained was different depending on the region when classified.
I plotted keywords and categories on a map to make it easier to see what categories of information are most common in which vicinity.
A new network diagram was produced by combining a graph categorised by time of day with a network diagram with additional keywords, and then connecting the same or similar keywords with a line.
Framework of architecture
An attempt was made to visualise the algorithm and the practice in randomness using the collected data as a starting point. For the visualisation of the Google Maps algorithm, I use the Google Maps flow diagram(1) compiled in Primary Research in Research Methods and the information displayed on Google Maps(2) that was collected by walking around the city and analysed in quantitative research. The Randomness one uses the categories analysed in the qualitative research(3) and the network diagrams(4) classified by keywords from them.I conceived the idea of producing it using the ‘framework of architectural thought’ (Galilee, 2021).
Why architecture? Because Google Maps is a map and therefore has a high affinity with urban design and architecture. Diagrams are also often used in the building industry to design architecture. And because the structure of the internet is often referred to as ‘internet architecture’, which is a reference to cities, we thought it would be possible to combine cities, architecture and information. The architect Alexander said that by creating patterns in urban design and combining these patterns, it is possible to create an activated city. In particular, he said that one of these patterns, the ‘mosaic of subcultures’, is a pattern in which many small-scale subcultures are divided by non-residential boundaries, while allowing people to choose the subculture they want to live in, to experience many different ways of life, and to develop mutual help and common values in their individual environments. This is similar to the civic activism of Jacobs in New York when many hegemonic men engaged in resistance to redevelopment at their convenience. She said it is important to have a ‘collage city’, a city where various small and medium-sized communities are chaotically combined. In this work, I have tried to show how the vast amount of data collected from internet users, which D’Ignazio describes as controlled by algorithms produced by the so-called white male class (data feminisum), and the information that appears in physical space through the mapping service google maps, can be used to create a city that is both a place where people can walk randomly and coincidentally through the city, could be combined to create a new map (architecture).
ZINE
The architectural model of Master final project is designed to be easily navigable for viewers, with minimal explanatory details. To supplement this, a ZINE has been created in the form of an accordion-fold book that looks like a paper map.
The front surface of the ZINE provides detailed insights into each layer of the model, while the back side contains specific details of the data collection records that I gathered and mapped onto a London map.
