Data Publics: Urban Protest, Analytics and the Courts

Anthony McCosker, Timothy Graham

Abstract


This article reflects on part of a three-year battle over the redevelopment of an iconic Melbourne music venue, the Palace-Metro Nightclub (the Palace), involving the tactical use of Facebook Page data at trial. We were invited by the Save the Palace group, Melbourne City Council and the National Trust of Australia to provide Facebook Page data analysis as evidence of the social value of the venue at an appeals trial heard at the Victorian Civil Administration Tribunal (VCAT) in 2016. We take a reflexive ethnographic approach here to explore the data production, collection and analysis processes as these represent and constitute a “data public”.

Although the developers won the appeal and were able to re-develop the site, the court accepted the validity of social media data as evidence of the building’s social value (Jinshan Investment Group Pty Ltd v Melbourne CC [2016] VCAT 626, 117; see also Victorian Planning Reports). Through the case, we elaborate on the concept of data publics by considering the “affordising” (Pollock) processes at play when extracting, analysing and visualising social media data. Affordising refers to the designed, deliberate and incidental effects of datafication and highlights the need to attend to the capacities for data collection and processing as they produce particular analytical outcomes. These processes foreground the compositional character of data publics, and the unevenness of data literacies (McCosker “Data Literacies”; Gray et al.) as a factor of the interpersonal and institutional capacity to read and mobilise data for social outcomes.

We begin by reconsidering the often-assumed connection between social media data and their publics. Taking onboard theoretical accounts of publics as problem-oriented (Dewey) and dynamically constituted (Kelty), we conceptualise data publics through the key elements of a) consequentiality, b) sufficient connection over time, c) affective or emotional qualities of connection and interaction with the events. We note that while social data analytics may be a powerful tool for public protest, it equally affords use against public interests and introduces risks in relation to a lack of transparency, access or adequate data literacy.

Urban Protest and Data Publics 

There are many examples globally of the use of social media to engage publics in battles over urban development or similar issues (e.g. Fredericks and Foth). Some have asked how social media might be better used by neighborhood organisations to mobilise protest and save historic buildings, cultural landmarks or urban sites (Johnson and Halegoua). And we can only note here the wealth of research literature on social movements, protest and social media. To emphasise Gerbaudo’s point, drawing on Mattoni, we “need to account for how exactly the use of these media reshapes the ‘repertoire of communication’ of contemporary movements and affects the experience of participants” (2). For us, this also means better understanding the role that social data plays in both aiding and reshaping urban protest or arming third sector groups with evidence useful in social institutions such as the courts.

New modes of digital engagement enable forms of distributed digital citizenship, which Meikle sees as the creative political relationships that form through exercising rights and responsibilities. Associated with these practices is the transition from sanctioned, simple discursive forms of social protest in petitions, to new indicators of social engagement in more nuanced social media data and the more interactive forms of online petition platforms like change.org or GetUp (Halpin et al.). These technical forms code publics in specific ways that have implications for contemporary protest action. That is, they provide the operational systems and instructions that shape social actions and relationships for protest purposes (McCosker and Milne).

All protest and social movements are underwritten by explicit or implicit concepts of participatory publics as these are shaped, enhanced, or threatened by communication technologies. But participatory protest publics are uneven, and as Kelty asks: “What about all the people who are neither protesters nor Twitter users? In the broadest possible sense this ‘General Public’ cannot be said to exist as an actual entity, but only as a kind of virtual entity” (27). Kelty is pointing to the porous boundary between a general public and an organised public, or formal enterprise, as a reminder that we cannot take for granted representations of a public, or the public as a given, in relation to Like or follower data for instance.

If carefully gauged, the concept of data publics can be useful. To start with, the notions of publics and publicness are notoriously slippery. Baym and boyd explore the differences between these two terms, and the way social media reconfigures what “public” is. Does a Comment or a Like on a Facebook Page connect an individual sufficiently to an issues-public? As far back as the 1930s, John Dewey was seeking a pragmatic approach to similar questions regarding human association and the pluralistic space of “the public”. For Dewey, “the machine age has so enormously expanded, multiplied, intensified and complicated the scope of the indirect consequences [of human association] that the resultant public cannot identify itself” (157). To what extent, then, can we use data to constitute a public in relation to social protest in the age of data analytics?

There are numerous well formulated approaches to studying publics in relation to social media and social networks. Social network analysis (SNA) determines publics, or communities, through links, ties and clustering, by measuring and mapping those connections and to an extent assuming that they constitute some form of sociality. Networked publics (Ito, 6) are understood as an outcome of social media platforms and practices in the use of new digital media authoring and distribution tools or platforms and the particular actions, relationships or modes of communication they afford, to use James Gibson’s sense of that term. “Publics can be reactors, (re)makers and (re)distributors, engaging in shared culture and knowledge through discourse and social exchange as well as through acts of media reception” (Ito 6). Hashtags, for example, facilitate connectivity and visibility and aid in the formation and “coordination of ad hoc issue publics” (Bruns and Burgess 3). Gray et al., following Ruppert, argue that “data publics are constituted by dynamic, heterogeneous arrangements of actors mobilised around data infrastructures, sometimes figuring as part of them, sometimes emerging as their effect”. The individuals of data publics are neither subjugated by the logics and metrics of digital platforms and data structures, nor simply sovereign agents empowered by the expressive potential of aggregated data (Gray et al.).

Data publics are more than just aggregates of individual data points or connections. They are inherently unstable, dynamic (despite static analysis and visualisations), or vibrant, and ephemeral. We emphasise three key elements of active data publics. First, to be more than an aggregate of individual items, a data public needs to be consequential (in Dewey’s sense of issues or problem-oriented). Second, sufficient connection is visible over time. Third, affective or emotional activity is apparent in relation to events that lend coherence to the public and its prevailing sentiment. To these, we add critical attention to the affordising processes – or the deliberate and incidental effects of datafication and analysis, in the capacities for data collection and processing in order to produce particular analytical outcomes, and the data literacies these require. We return to the latter after elaborating on the Save the Palace case.

Visualising Publics: Highlighting Engagement and Intensity

The Palace theatre was built in 1912 and served as a venue for theatre, cinema, live performance, musical acts and as a nightclub. In 2014 the Heritage Council decided not to include the Palace on Victoria’s heritage register and hence opened the door for developers, but Melbourne City Council and the National Trust of Australia opposed the redevelopment on the grounds of the building’s social significance as a music venue. Similarly, the Save the Palace group saw the proposed redevelopment as affecting the capacity of Melbourne CBD to host medium size live performances, and therefore impacting deeply on the social fabric of the local music scene. The Save the Palace group, chaired by Rebecca Leslie and Michael Raymond, maintained a 36,000+ strong Facebook Page and mobilised local members through regular public street protests, and participated in court proceedings in 2015 and February 2016 with Melbourne City Council and National Trust Australia. 

Joining the protesters in the lead up to the 2016 appeals trial, we aimed to use social media engagement data to measure, analyse and present evidence of the extent and intensity of a sustained protest public. The evidence we submitted had to satisfy VCAT’s need to establish the social value of the building and the significance of its redevelopment, and to explain: a) how social media works; b) the meaning of the number of Facebook Likes on the Save The Palace Page and the timing of those Likes, highlighting how the reach and Likes pick up at significant events; and c) whether or not a representative sample of Comments are supportive of the group and the Palace Theatre (McCosker “Statement”). As noted in the case (Jinshan, 117), where courts have traditionally relied on one simple measure for contemporary social value – the petition – our aim was to make use of the richer measures available through social media data, to better represent sustained engagement with the issues over time.

Visualising a protest public in this way raises two significant problems for a workable concept of data publics. The first involves the “affordising” (Pollock) work of both the platform and our data analysis. This concerns the role played by data access and platform affordances for data capture, along with methodological choices made to best realise or draw out the affordances of the data for our purposes. The second concerns the issue of digital and data literacies in both the social acts that help to constitute a data public in the first place, and the capacity to read and write public data to represent those activities meaningfully. That is, Facebook and our analysis constitutes a data public in certain ways that includes potentially opaque decisions or processes. And citizens (protesters or casual Facebook commenters alike) along with social institutions (like the courts) have certain uneven capacity to effectively produce or read public protest-oriented data. The risk here, which we return to in the final section, lies in the potential for misrepresentation of publics through data, exclusions of access and ownership of data, and the uneven digital literacies at each stage of data production, analysis and sensemaking.

Facebook captures data about individuals in intricate detail. Its data capture strategies are geared toward targeting for the purposes of marketing, although only a small subset of the data is publicly available through the Facebook Application Programming Interface (API), which is a kind of data “gateway”. The visible page data tells only part of the story. The total Page Likes in February 2016 was 36,828, representing a sizeable number of followers, mainly located in Melbourne but including 45 countries in total and 38 different languages. We extracted a data set of 268,211 engagements with the Page between February 2013 and August 2015. This included 45,393 post Likes and 9,139 Comments. Our strategy was to demarcate a structurally defined “community” (in the SNA sense of that term as delineating clusters of people, activities and links within a broader network), by visualising the interactions of Facebook users with Posts over time, and then examine elements of intensity of engagement. In other words, we “affordised” the network data using SNA techniques to most clearly convey the social value of the networked public.

We used a combination of API access and Facebook’s native Insights data and analytics to extract use-data from that Page between June 2013 and December 2015. Analysis of a two-mode or bipartite network consisting of users and Posts was compiled using vosonSML, a package in the R programming language created at Australian National University (Graham and Ackland) and visualised with Gephi software. In this network, the nodes (or vertices) represent Facebook users and Facebook Posts submitted on the Page, and ties (or edges) between nodes represent whether a user has commented on and/or liked a post. For example, a user U might have liked Post A and commented on Post B. Additionally, a weight value is assigned for the Comments ties, indicating how many times a user commented on a particular post (note that users can only like Posts once). We took these actions as demonstrating sufficient connection over time in relation to an issue of common concern.

Network Diagram

Figure 1: Network visualisation of activity on the Save the Palace Facebook Page, June 2013 to December 2015. The colour of the nodes denotes which ‘community’ cluster they belong to (computed via the Infomap algorithm) and nodes are sized by out-degree (number of Likes/Comments made by users to Posts). The graph layout is computed via the Force Atlas 2 algorithm.

Community detection was performed on the network using the Infomap algorithm (Rosvall and Bergstrom), which is suited to large-scale weighted and directed networks (Henman et al.). This analysis reveals two large and two smaller clusters or groups represented by colour differences (Fig. 1). Broadly, this suggests the presence of several clusters amongst a sustained network engaging with the page over the three years. Beyond this, a range of other colours denoting smaller clusters indicates a diversity of activity and actors co-participating in the network as part of a broader community.

The positioning of nodes within the network is not random – the visualisation is generated by the Force Atlas 2 algorithm (Jacomy et al.) that spatially sorts the nodes through processes of attraction and repulsion according to the observed patterns of connectivity. As we would expect, the two-dimensional spatial arrangement of nodes conforms to the community clustering, helping us to visualise the network in the form of a networked public, and build a narrative interpretation of “what is going on” in this online social space.

Social value for VCAT was loosely defined as a sense of connection, sentiment and attachment to the venue. While we could illustrate the extent of the active connections of those engaging with the Page, the network map does not in itself reveal much about the sentiment, or the emotional attachment to the Save the Palace cause. This kind of affect can be understood as “the energy that drives, neutralizes, or entraps networked publics” (Papacharissi 7), and its measure presents a particular challenge, but also interest, for understanding a data public. It is often measured through sentiment analysis of content, but we targeted reach and engagement events – particular moments that indicated intense interaction with the Page and associated events.

Save the Palace Facebook Page: Organic post reach November—December 2014

Figure 2: Save the Palace Facebook Page: Organic post reach November—December 2014

The affective connection and orientation could be demonstrated through two dimensions of post “reach”: average reach across the lifespan of the Page, and specific “reach-events”. Average reach illustrates the sustained engagement with the Page over time. Average un-paid reach for Posts with links (primarily news and legal updates), was 12,015 or 33% of the total follower base – a figure well above the standard for Community Page reach at that time. Reach-events indicated particular points of intensity and illustrates the Page’s ability to resonate publicly. Figure 2 points to one such event in November 2015, when news circulated that the developers were defying stop-work orders and demolishing parts of The Palace. The 100k reach indicated intense and widespread activity – Likes, Shares, Comments – in a short timeframe. We examined Comment activity in relation to specific reach events to qualify this reach event and illustrate the sense of outrage directed toward the developers, and expressions of solidarity toward those attempting to stop the redevelopment.      

Affordising Data Publics and the Transformative Work of Analytics

Each stage of deriving evidence of social value through Page data, from building public visibility and online activity to analysis and presentation at VCAT, was affected by the affordising work of the protesters involved (particularly the Page Admins), civil society groups, platform features and data structures and our choices in analysis and presentation. 

The notion of affordising is useful here because, as Pollock defines the term, it draws attention to the transformative work of metrics, analytics, platform features and other devices that re-package social activity through modes of datafication and analysis. The Save the Palace group mobilised in a particular way so as to channel their activities, make them visible and archival, to capture the resonant effects of their public protest through a platform that would best make that public visible to itself. The growth of the interest in the Facebook Page feeds back on itself reflexively as more people encounter it and participate. Contrary to critiques of “clicktivism”, these acts combine digital-material events and activities that were to become consequential for the public protest – such as the engagement activities around the November 2015 event described in Figure 2.

In addition, presenting the research in court introduced particular hurdles, in finding “the meaningful data” appropriate to the needs of the case, “visualizing social data for social purposes”, and the need to be “evocative as well as accurate” (Donath, 16). The visualisation and presentation of the data needed to afford a valid and meaningful expression of the social significance the Palace. Which layout algorithm to use? What scale do we want to use? Which community detection algorithm and colour scheme for nodes? These choices involve challenges regarding legibility of visualisations of public data (McCosker and Wilken; Kennedy et al.).

The transformative actions at play in these tactics of public data analysis can inform other instances of data-driven protest or social participation, but also leave room for misuse. The interests of developers, for example, could equally be served by monitoring protesters’ actions through the same data, or by targeting disagreement or ambiguity in the data. Similarly, moves by Facebook to restrict access to Page data will disproportionately affect those without the means to pay for access. These tactics call for further work in ethical principles of open data, standardisation and data literacies for the courts and those who would benefit from use of their own public data in this way.

Conclusions

We have argued through the case of the Save the Palace protest that in order to make use of public social media data to define a data public, multiple levels of data literacy, access and affordising are required. Rather than assuming that public data simply constitutes a data public, we have emphasised: a) the consequentiality of the movement; b) sufficient connection over time; and c) affective or emotional qualities of connection and interaction with public events. This includes the activities of the core members of the Save the Palace protest group, and the tens of thousands who engaged in some way with the Page. It also involves Facebook’s data affordances as these allow for the extraction of public data, alongside our choices in analysis and visualisation, and the court’s capacity and openness to accept all of this as indicative of the social value (connections, sentiment, attachment) it sought for the case. 

The Senior Member and Member presiding over the case had little knowledge of Facebook or other social media platforms, did not use them, and hence themselves had limited capacity to recognise the social and cultural nuances of activities that took place through the Facebook Page. This does not exclude the use of the data but made it more difficult to present a picture of the relevance and consequence of the data for understanding the social value evident in the contested building. While the court’s acceptance of the analysis as evidence is a significant starting point, further work is required to ensure openness, standardisation and ethical treatment of public data within public institutions like the courts. 

References

Bruns, A., and J. Burgess. “The Use of Twitter Hashtags in the Formation of Ad Hoc Publics.” 6th European Consortium for Political Research General Conference, University of Iceland, Reykjavík, 25-27 August 2011. 1 Aug. 2018 <http://eprints.qut.edu.au/46515/>.

Baym, N.K., and d. boyd. “Socially Mediated Publicness: An Introduction.” Journal of Broadcasting & Electronic Media 56.3 (2012): 320-329.

Dewey, J. The Public and Its Problems: An Essay in Political Inquiry. Athens, Ohio: Swallow P, 2016 [1927].

Donath, J. The Social Machine: Designs for Living Online. Cambridge: MIT P, 2014.

Fredericks, J., and M. Foth. “Augmenting Public Participation: Enhancing Planning Outcomes through the Use of Social Media and Web 2.0.” Australian Planner 50.3 (2013): 244-256.

Gerbaudo, P. Tweets and the Streets: Social Media and Contemporary Activism. New York: Pluto P, 2012.

Gibson, J.J. The Ecological Approach to Visual Perception. Boston: Houghton Mifflin Harcourt, 1979.

Graham, T., and R. Ackland. “SocialMediaLab: Tools for Collecting Social Media Data and Generating Networks for Analysis.” CRAN (The Comprehensive R Archive Network). 2018. 1 Aug. 2018 <https://cran.r- project.org/web/packages/SocialMediaLab/SocialMediaLab.pdf>.

Gray J., C. Gerlitz, and L. Bounegru. “Data Infrastructure Literacy.” Big Data & Society 5.2 (2018). 1 Aug. 2018 <https://doi.org/10.1177/2053951718786316>.

Halpin, T., A. Vromen, M. Vaughan, and M. Raissi. “Online Petitioning and Politics: The Development of Change.org in Australia.” Australian Journal of Political Science (2018). 1 Aug. 2018 <https://doi.org/10.1080/10361146.2018.1499010>.

Henman, P., R. Ackland, and T. Graham. “Community Structure in e-Government Hyperlink Networks.” Proceedings of the 14th European Conference on e-Government (ECEG ’14), 12-13 June 2014, Brasov, Romania.

Ito, M. “Introduction.” Networked Publics. Ed. K. Varnelis. Cambridge, MA.: MIT P, 2008. 1-14.

Jacomy M., T. Venturini, S. Heymann, and M. Bastian. “ForceAtlas2, a Continuous Graph Layout Algorithm for Handy Network Visualization Designed for the Gephi Software.” PLoS ONE 9.6 (2014): e98679. 1 Aug. 2018 <https://doi.org/10.1371/journal.pone.0098679>.

Jinshan Investment Group Pty Ltd v Melbourne CC [2016] VCAT 626, 117. 2016. 1 Aug. 2018 <https://bit.ly/2JGRnde>.

Johnson, B., and G. Halegoua. “Can Social Media Save a Neighbourhood Organization?” Planning, Practice & Research 30.3 (2015): 248-269.

Kennedy, H., R.L. Hill, G. Aiello, and W. Allen. “The Work That Visualisation Conventions Do.” Information, Communication & Society, 19.6 (2016): 715-735.

Mattoni, A. Media Practices and Protest Politics: How Precarious Workers Mobilise. Burlington, VT: Ashgate, 2012.

McCosker, A. “Data Literacies for the Postdemographic Social Media Self.” First Monday 22.10 (2017). 1 Aug. 2018 <http://firstmonday.org/ojs/index.php/fm/article/view/7307/6550>.

McCosker, A. “Statement of Evidence: Palace Theatre Facebook Page Analysis.” Submitted to the Victorian Civil Administration Tribunal, 7 Dec. 2015. 1 Aug. 2018 <https://www.academia.edu/37130238/Evidence_Statement_Save_the_Palace_Facebook_Page_Analysis_VCAT_2015_>.

McCosker, A., and M. Esther. "Coding Labour." Cultural Studies Review 20.1 (2014): 4-29.

McCosker, A., and R. Wilken. “Rethinking ‘Big Data’ as Visual Knowledge: The Sublime and the Diagrammatic in Data Visualisation.” Visual Studies 29.2 (2014): 155-164.

Meikle, G. Social Media: Communication, Sharing and Visibility. New York: Routledge, 2016.

Papacharissi, Z. Affective Publics: Sentiment, Technology, and Politics. Oxford: Oxford UP, 2015.

Pollock, N. “Ranking Devices: The Socio-Materiality of Ratings.” Materiality and Organizing: Social Interaction in a Technological World. Eds. P.M. Leonardi, Bonnie A. Nardi, and J. Kallinikos. Oxford: Oxford UP, 2012. 91-114.

Rosvall, M., and C.T. Bergstrom. “Maps of Random Walks on Complex Networks Reveal Community Structure.” Proceedings of the National Academy of Sciences of the United States of America 105.4 (2008): 1118-1123.

Ruppert E. “Doing the Transparent State: Open Government Data as Performance Indicators.” A World of Indicators: The Making of Governmental Knowledge through Quantification. Eds. R. Rottenburg S.E. Merry, S.J. Park, et al. Cambridge: Cambridge UP, 2015. 1–18.

Smith, N., and T. Graham. “Mapping the Anti-Vaccination Movement on Facebook.” Information, Communication & Society (2017). 1 Aug. 2018 <https://doi.org/10.1080/1369118X.2017.1418406>.

Victorian Planning Reports. “Editorial Comment.” VCAT 3.16 (2016). 1 Aug. 2018 <https://www.vprs.com.au/394-past-editorials/vcat/1595-vcat-volume-3-no-16>.


Keywords


Data analytics; publics; social media; protest; social movements; VCAT



Copyright (c) 2018 Anthony McCosker, Timothy Graham

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