Digital Culture and Communication

The Digital Culture and Communication section of ECREA

Jennifer Colombari: Digital data from non-digital city practices: A semiotic approach for understanding the meaning of a street

Jennifer Colombari, University of Bologna. jennifer.colombari2@unibo.it

 

The huge amount of data and information currently available thanks to the Web enables us to know our urban environment more deeply. In addition, a key role is played by companies and research centres, such as the Citizen Data Lab at the Amsterdam University of Applied Sciences, that collect data from citizens in a participatory way.

 

The Lab has been developing tools and methods for city analytics and it has tested them upon the Knowledge Mile, an area of Amsterdam which currently hosts the University Campus and many local initiatives, which has been considered one of the most problematic and ugly roads in the city for years. The collected data are usually analysed from a quantitative point of view to create infographics and other forms of data visualizations, that are used as a starting point for the discussion about the measurements results with stakeholders.

 

One of the greatest challenges is to examine the data more profoundly with a qualitative approach to investigate the citizens’ perception of the analysed area. Semiotics can contribute to interpret this data, by providing some analysis tools which are able to shed light on the basic elements that allow the emersion of the meaning of the studied situation. Through the semiotic analysis of data I have identified the effects of sense that characterize the Knowledge Mile, or a portion of them, trying to answer several questions such as: “how do people interpret the Knowledge Mile?” “What flaws and/or strengths do they perceive?” “Are the perceived problems related to spatial configuration or are they an identity matter?”

 

This study used a semiotic and qualitative case study approach to investigate the identity of the Wibautstraat, one of the two roads that make up the Knowledge Mile, combining the analysis of big corpora of digital data and the traditional semiotic field observation.

 

The analyzed corpus is composed by digital data from citizens and from social network. The data from citizens was collected with Measuring Amsterdam, a participatory mapping tool for citizen empowerment developed by the Citizen Data Lab and used during two events with the help of citizens (Groen, Meys 2015). The large amount of gathered measurements describes the road, reflecting the point of view of those who live in the neighbourhood daily. The first dataset is composed of 1570 measurements and divided in 4 domains: traffic, social, environment/safety and multimedia. The second one is composed of 55 data in the form of a detected problem described by a verbal text, a picture of this problem and a hypothesized solution.

 

However, the data collected by the Citizen Data Lab gave us only partial information about the Wibautstraat because they are influenced by the research questions and the instructions given to the participants. For example, the second event, was devoted to identifying only problems and the participants ignored the positive aspects of the area. Moreover, the data was collected in 2014 and 2015 and, in the meantime, something can be changed. To cope with this and get a more complete picture of the situation, it was decided to collect a corpus of data from Instagram, which has been proven to be a good source of positive interpretation about the area. The result is a set of digital data composed of 121 Instagram posts shared in the month of March and April 2017 and geo-located at Wibautstraat or with the hashtag #Wibautstraat.

 

All the verbal texts in the digital data have been analysed from a semantic point of view in order to identify the isotopes, that is the repetition of units of meaning which may occur through the same words or through different terms that express implicitly the same meaning (cfr. Greimas e Courtés 1979, Marmo 2015; Pozzato 2001). Thanks to the identification of semantic repetitions, it was possible to highlight the topics discussed in the texts and understand what people are talking about when they interpret and describe the Wibautstraat. The Instagram posts were analysed and categorized considering both the picture, the verbal comment and the chosen hashtags to show what people evaluate positively in the area.

 

The data analysis allowed to make the first interpretative hypotheses about the area. In the end, it was conducted a field observation with a ethnosemiotic approach. The attention was focused on the aspect of the area (architectural aspect, public spaces, urban furnishing) and on the behaviour of people (where do people go or stay? what do people do?).

 

Surprisingly, the results of the semiotic analysis and observation showed significant differences in people’s behaviour in different areas of the road. Therefore, it was possible to suppose a subdivision of the Wibautstraat into 4 parts, based on what the area offers and what people do: the “University campus”, the “living area”, the “temporary stay area” and the “cars area”. The identified road portion shown four different ways of interpreting and acting in an urban area and suggested a typology of citizen behaviour. Obviously, the typology of people is not the description of all the observed behaviours but an abstraction and generalization of the observed practices.

 

To sum up, this study has shown that the semiotic analysis of digital data is useful to “make the data speak” more about the urban experience of people. The analysis of the digital data from citizen has allowed me to identify the most crowded and lively areas of the road and the problems most often perceived by the citizens. The study of the Instagram dataset was helpful to pinpoint the positive aspects of the area. Finally, thanks to the field observation, I studied more in detail the identified macro-areas, assuming a further subdivision of the Wibautstraat, based on the characteristics of the road and the behaviour of people. These findings may help us to understand the urban experience of people in different portions of the road and they can represent a cause of reflection for decision-makers. For instance, the identified behavioural typology could be a starting point for the planning of local initiatives. From time to time, it can be decided whether to favor the present identity of each section of the road, for example by increasing the services for students in the campus, or to modifying some aspects of the road perceived negatively, in order to improve the quality of life of the area. It is interesting that, thanks to the analysis of the Citizen Data Lab data, the suggestions for solving the problems reflect citizens’ opinion. Finally, these findings can have important implications for citizen empowerment, since, in the case of Amsterdam, disseminating the results within the Knowledge Mile community can make citizen more aware of their behavior and their neighborhood problems.

 

 


REFERENCES

 

GROEN, M.; MEYS, W.

2015    “Measuring Amsterdam: A participatory mapping tool for citizen empowerment”, in Conference: Hybrid City III: Data to the people, Athens, 2015.

 

GREIMAS, A.J.; COURTES, J.

1979    Sémiotique. Dictionnaire raisonné de la théorie du langage, Hachette, Paris

 

MARMO, C.

2015    Segni linguaggi e testi. Semiotica per la comunicazione, Bononia University Press, Bologna.

 

POZZATO, M.P.

2001    Semiotica del testo. Metodi, autori, esempi, Carrocci Editore, Roma.

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