Team:

Nataliya Tkachenko, Xinyang Xie (Yang), Peta Mitchell, Maarten Groen, Adrian Bertoli, Khwezi Magwaza, Naomi Bueno de Mesquita, Joe Shaw, Alexander van Someren, Tim Leunissen, Michele Mauri, Philip Schuette, Donato Ricci, Sabine Niederer (facilitator).

1. Background

“[Cities] are not like suburbs, only denser. They differ from towns and suburbs in basic ways, and one of these is that cities are, by definition, full of strangers.” Jacobs, Jane. The Death and Life of Great American Cities. 1961 [insert page nr].

Lyn Lofland (1998) defines the “parochial realm” or “parochial order” as being “characterized by a sense of commonality among acquaintances and neighbors who are involved in interpersonal networks that are located within ‘communities’” (p. 10). Where the private realm is the “world of the household and friend and kin networks; the parochial realm is the world of the neighborhood, workplace, or acquaintance networks; and the public realm is the world of strangers and the ‘street’” (p. 10). Lofland, Lyn. The Public Realm: Exploring the City’s Quintessential Social Territory. New York: de Gruyter, 1998.

Martijn de Waal on parochial realms and urban media: “This raises the following questions: how do urban media enable us to shape these different domains in new ways? How does the emergence of a new technology shift the balance between parochial and public domains? Does the emergence of new technologies reinforce the parochial domain, and do new technologies make it easier for city dwellers to withdraw to their own ‘turf ’? Or can they actually reinforce the public domain, which is dominated by mutual interchange?” (City as Interface, chap. 1)

Hybridizing urban space

“Urban spaces are becoming hybridized (de Souza e Silva, 2006), meaning they are composed through a combination of physical and digital practices. For each individual, the urban environment is constructed through perceptions of nearby information and people; the experience of net locality translates what we understand as near, and how we understand the co-presence of other individuals. Noting someone’s presence in a location-based mobile game, or tracking somebody’s located updates on a LBSN alters one’s perceptions of the composition and boundaries of the environment.” (Gordon and de Souza e Silva, 2011, p. 14)

Gordon, Eric, and Adriana de Souza e Silva. Net Locality: Why Location Matters in a Networked World. Chichester: Wiley Blackwell, 2011.

2. Research questions:

How do geosocial media platforms (such as Foursquare, Twitter, Flickr, Meet-up, and Geocaching) remediate urban space? Can they be considered to constitute overlapping parochial or public domains? And can mapping/geovisualising geosocial media platforms help us to answer these questions?

Net locality (location awareness based on mobile technologies) makes different parochial realms meet and overlap in time and space. How is this played out in the same physical urban space?

3. Methodology

Retrieve Amsterdam-specific posts/meetups/pins on (secondary) social media and plot on a map.

Data:

Pinterest: Term ‘Amsterdam’ in “place” boards = list of 781 boards, pulling first 100 pins per board, total of 31479 pins (8274 geolocated)

Meetup - 489 events in 258 locations from 172 community's over a 4 month period.

Twitter: keyword Amsterdam over a 10-day period (13–22 June), resulting in 4930 geotagged tweets in the Amsterdam area

Geocaching: 700 of geocaches in Amsterdam (geocaching.nl)

Analyze first the type of Amsterdam the platform presents, and secondly identify stacks of parochial spaces (within and cross platform); the more overlapping parochial spaces, the more public this space is.

Strategy: find stacks of coded spaces; the more parochial groups, the more public?

Amsterdam geo bounding box

Northwest point: 52.4266, 4.762

South east point: 52.3192, 5.056

4. Data Layers/geosocial media platforms:

Layered map link.

Flickr: http://cdb.io/VloTIA (in a separate map due to cartodb free account restrictions)

a) Meetup [update please]

Sample: last month’s events (350)

events, groups, members (nr), member interest,

events & attendees, groups, locations, members, member interests, group categories

Maps:

- Plot categories and group names to map

Multiple categories at one location

Pinterest

Pinterest - full presentation https://docs.google.com/presentation/d/1BLh0qt0X4Y659hUIzE5NUZNgAKarB4JW6kbJxDh_iDk/edit#slide=id.p

Method:

Query - list of all ‘Amsterdam’ themed “place” boards, pictures and metadata, user profile.

Data - list of 781 boards, first 100 pins per board

“place board : created specifically for vacation planning, and travel inspiration - “place pins and boards are designed to combine the beautiful imagery of a travel magazine with the utility of a map online - Pinterest blog”

Interesting to note: in 2013 Pinterest had more than 750 million destination pins

Pinterest map, colour coded according to ‘child friendly’, ‘hidden gems’ and ‘hotspots’: http://cdb.io/1o6JOFX

Here is a map with the above categories plus ‘interior design’:

http://cdb.io/1o6MdAF

Final map with the above categories, including a level colour coded ‘local’ vs. ‘non-local’

http://cdb.io/1rsOo85

Most pinned places

http://cdb.io/1xqAWSF

Map of layers/categories WITHOUT local:

http://cdb.io/1mQMwOF

Map of layers, relabeled starting with child friendly:

http://cdb.io/1zcUKL7

Scraping information:

>>> visualisation to illustrate all included

Number of boards: 871

Number of pins: 31479

Number of geo located pins: 8274

This means that 11% of the pins that we’ve used have a geo location attached to them (and we have 8274 in 243 boards that we will be using pins that we’re going to use).

Local vs Others

>>> Map to illustrate included

67 of the boards are in Amsterdam (27.6%)

Note: Most pinned locations

we also used the geo located data to count the number of pins at each location and discovered that 424 boards pinned at same coordinates - this turned out to be cord. which foursquare used to identify the term ‘Amsterdam”

Languages

>>> Map to illustrate included

196 of the pinners are pinning in English (80%)

26 of the pinners are pinning ing dutch (10.6%) other languages = French, German , Spanish and Portuguese

interestingly 62% of pinners in Amsterdam are pinning in English (with only 20% of the pinners in Amsterdam pinning in Dutch)

Content Analysis

We used a editorial analysis of the content in the 243 geo located boards to categorise content of boards (using this category list) , we also noted reference to another location (international or in the Netherlands) and profession of pinner where stated.

- food/drink, sightseeing,

We began to see according and started to see some groupings of people o l

Meet-up

Rank locations from number of groups

Looking at specific communities, such as the Amsterdam Expat Community. Where do they meet?

Summary approach:

Crossreferening the goal specific meetup communities with their meetup locations over the last couple of months in Amsterdam. This could result in a map juxtaposition of the frequency of meetupgroups referencing a certain location and purpose of the meeting.

This would enable a map with a neutral medium color/no color indicating non-specific and non-public aka private space. Lighter color might indicate specific/parochial spaces (high parochial specificity). Darker color would indicate many groups referencing this location indicating possible public spaces.

The final aim is to build the ‘spatial landscape’ of Amsterdam in relation to its accessibility: which part of the city are more open to more diverse public groups - and which are more restrictive/closed/’parochial’.

API possibilites: Retrieve all events from last month and the upcoming three months. For each event we can retrieve the group that organized the event. Each group has information such as categories.

Upcoming events: 490 from 170 groups

http://www.meetup.com/meetup_api/console/?path=%2F2%2Fcategories

Relevant API urls:

Retrieve all events: http://www.meetup.com/meetup_api/docs/2/open_events/

Group information: http://www.meetup.com/meetup_api/docs/2/groups/

Member information: http://www.meetup.com/meetup_api/docs/2/members/

Pinterest Place boards

Like, Comment, Repin: User Interaction on Pinterest (http://arxiv.org/pdf/1405.1752v1.pdf) -a paper describing Pinterest’s users activity-

Pinned it! A Large Scale Study of the Pinterest Network (http://precog.iiitd.edu.in/Publications_files/Pinterest-IKDD.pdf) -a study on Pinterest demographic)

unofficial API/scraping
http://pinterestapi.co.uk/

http://snipplr.com/view.php?codeview&id=64496

image scraping is possible with zzllrr ( https://chrome.google.com/webstore/detail/bulk-download-imageszig/gfjhimhkjmipphnaminnnnjpnlneeplk?hl=en) but not long lat

more than 944 boards related to Amsterdam (each boards contains a description and geolocated pictures)

user profiling (self description, connection to other SM, boards)

Pinboard titles are coloured coded according to ‘subject’.

Profiles highlighted in red in Google Docs correspond to board dedicated to child friendly city (in several languages)

Pinboard hightled in orange correspond to descriptive terms: hidden (gems), unique, discover.

Pinboards highlighted in blue are hotspots, popular, top (spot),

Play

Inspired by psychogeography, geocaching could be seen as an encountering of new and authentic ways of experiencing the city. Narratives of place are created and played out in the urban environment. We compared different platforms of urban play (Figure running, Ingress, tourality, urbanopoly). Some games are focused on the individual experience, others on the collective, in which the crowd-sourcing or competition element is key.

Ingress: augmented reality game

Figure running: body as pencil to draw on the city. performative and narrative.

Tourality: LB hunt game. Reaching geographic spots in different challenges

Urbanopoly: location based game with the purpose to crowdsource Urban data

Geocaching

- Geocaching in Amsterdam

https://www.geocaching.com/map/default.aspx?ll=52.37101,4.90011#?ll=52.38147,4.92617&z=13

- Geocaching Amsterdam: https://www.geocaching.com/map/default.aspx?ll=52.37101,4.90011#?ll=52.37099,4.90007&z=14