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Mining Back: Re-curating Social Media Content for Social Good 

Poster for the Civic Participation in the Datafied Society conference taken from the conference website.
Poster for the Civic Participation in the Datafied Society taken from the Data Justice conference website.

Ozlem Demirkol Tonnesen,  Anna Feigenbaum,  José Blázquez presented on our AHRC project methodology at the Data Justice Conference. Contributing to the conference theme Civic Participation in the Datafied Society we explore how social media content can be re-curated for social good.  

https://datajusticelab.org/data-justice-2021/ 

Slide about the three pillars of the Mining back methodological framework, also explained in the text
Slide from the conference presentation outlining our methodological framework

Read our abstract here: 

Social media platforms archive much of the contemporary cultural, social and political artefacts that are created by the public in response to all the mundane and unique aspects of life. Instagram, for instance, is one of world’s largest visual archives, yet our ability to engage with it to learn about ourselves and our world remains tightly controlled and largely directed by the for-profit interests of the few. Set by corporate agendas, these platforms’ policies govern the terms of access to collect data while the platform’s algorithms curate the way in which content is seen or experienced by the users to keep them on the platform.  

After the Cambridge Analytica scandal, under the name of increased security, platforms like Facebook and its subsidiary Instagram further privatised and commercialised access to their data, establishing elite networks and services for research collaboration, such as Facebook’s Social Science Onewith its central hub at Harvard University that exists to “unlock commercial information for public good in privacy protective ways” (https://socialscience.one).  

While these collaborations mobilise the phrase ‘social good,’ the solutions of interest are commercially driven and directed around business priorities. Moreover, their mechanisms for collaboration reproduce data divides that concentrate power “amongst corporate firms, dominant in the West, and unequally distributed along racial and gender lines” (Feigenbaum and Alamalhodaei 2020, p.68). This elites-focused access likewise furthers what Andrejevic (2014) refers to as the “asymmetric relationship between those who collect, store and mine large quantities of data and those whom data collection targets (p. 1673).”  

In a difficult context in which privacy, ownership and data justice collide with economic interests and business opportunities, we stress the moral responsibility that social media platforms have towards the preservation and wide accessibility of productive cultural and social representations of digital citizenship, and the appropriate actions that organisations and researchers can take to fill that gap.  

On this basis, what methods are left to ‘mine back’ data for social value? How public archives can be built and re-claimed? In this paper, we reflected on some of the innovative, ethically driven solutions for working with social media data offered by other researchers and organisations before introducing our own project methodology for ‘mining back’ to archive and ‘re-curate social media content for social good.’ Designed as a response to asymmetrical relations of power in data-driven research, our approach provides a framework for re-curating publicly shared content from social media via collaborations with public stakeholders and content creators. 

This methodology highlights the importance of defining new social relationships for content beyond the confines of platform algorithms to further facilitate the study, preservation, and understanding of these sociocultural representations. We argue that collaborative re-curation of content can create new, participatory, and socially engaging infrastructures for data exploration and knowledge exchange. 

References

Andrejevic, M 2014, ‘Big Data, Big Questions| The Big Data Divide’, International Journal of Communication, vol. 8, pp. 1673-1689. 

Feigenbaum, A & Alamalhodaei, A 2020, The Data Storytelling Workbook. Routledge, London. 

Research Assistant

I am a PhD candidate researching the ways digital cultures inform the expressive styles of political talk. I love exploring how reality is narrated online and I am moonlighting as a research assistant in two projects on social media and public health.

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