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INKE 2018 & Academics on Social Media

INKE 2018 Beyond Open: Implementing Social Scholarship
Published February 25, 2018 by Kim O'Donnell

What does it mean for scholars to work in the “open”? How do they connect with their communities, publish their work, and what issues should they be aware of? How can libraries support and foster the open exchange of knowledge? These and many other questions were addressed at Beyond Open: Implementing Social Scholarship, a gathering in Victoria, BC hosted by INKE (Implementing New Knowledge Networks).

The main gathering was a day of lightning talks, a featured panel with longer papers, and featured speakers. View the full program. The day was full, and having everyone attend the same stream ensured that all participants could be a part of the same conversations. These conversations were organized around broad topics, allowing for plenty of voices; presenters talked about the publicness of archives; spaces where open scholarship occurs; open infrastructure for humanities and social science research; the interdisciplinarity of open social scholarship; communities of practice; and open scholarship on campus. Featured speakers dug more deeply into practices of and barriers to open knowledge sharing for research and teaching, open access publishing, and the possibilities and pitfalls of scaling the production of knowledge. INKE has made recordings of the featured speakers available.

At this gathering, I gave a lightning talk on academic requests for help on social media. I wanted to think through the way academics (myself included) call on our academic and non-academic communities for help in our academic research or teaching. How do we frame this collective thinking? How do we reciprocate this generosity? How do we account for this labour? To think through this more closely, I explored two ways I sometimes see these requests for help framed: as a form of crowdsourcing, and as a call out to the hivemind. My theory is that these different frameworks for collective thinking and work can help us to think more carefully and critically about collective intellectual labour in our communities.

The first term, crowdsource, has what I think are recognizably positive markers of collective labour. Crowdsourcing is when a group of individuals (usually volunteer) contribute to a project. Crowdsourcing research suggests that there is no one expert on a subject, but that knowledge comes from many diverse communities and people. This is an especially important context when it comes to traditionally marginalized voices both inside and outside the academy, who can educate privileged scholars and contribute to knowledge production for everyone. However, these positive aspects are not without their complexities. Social media is a public forum, and for some racialized, gendered, and/or sexualized identities, especially those without institutional protection, that public forum can be dangerous, exhausting, and traumatizing.

The second term, hivemind, comes from the behaviour of insects (like bees) and it suggests shared thinking in a more homogeneous way. All the workers in a hive are united to a common goal, and while the implied lack of individuality might seem negative, it turns out that the hive is actually a dynamic place. In fact, “hivemind” seems to describe the way academics already do research - building on the ideas of others - but with the important difference that academic ideas aren’t any more privileged than anyone else’s. I think this difference offers a concrete ethical challenge to academics turning to their social media communities for help: to be as much a part of the hivemind as the rest of the community. If, as academics, we are truly learning from and with our communities, we should also be deferring to them - which might mean shifting or even abandoning lines of research or teaching.

I think that both terms offer us ways to frame inclusive and accountable community-based, -driven, and -supported research and teaching, and I think academics should consider the implications of both crowdsourcing and the hivemind when we turn to our communities for support. Above all, I think we should turn to our communities, keeping privilege and the ethics of labour in mind. And I’m grateful to the generous community at INKE for the opportunity to share and learn with them there.



Brabham, Daren C. Crowdsourcing. MIT Press, 2013.

Chander, Anupam and Madhavi Sunder. "The Romance of the Public Domain." California Law Review, vol. 92, no. 5, 2004, pp. 1331-1374.

Gaggioli, Andrea. “The ‘Hive Mind’ Is Near.” Cyberpsychology, Behavior and Social Networking, vol. 20, no. 5, 2017, pp. 341–342.

Aron, Jacob. "Why Using the Hive Mind Is Nearly Always Best." New Scientist, vol. 214, no. 2868, 2012, p. 22.

Lindgren, Simon. “Crowdsourcing Knowledge: Interdiscursive flows from Wikipedia into scholarly research.” Culture Unbound. Journal of Current Cultural Research, vol. 6, 2014, pp. 609-627.

McPherson, Megan, et al. “New practices in doing academic development: Twitter as an informal learning space.”  International Journal for Academic Development, vol. 20, no. 2, 2015, pp. 126-136.

Prucher, J. “Group Mind.” The Oxford Dictionary of Science Fiction. Oxford University Press, 2006.

-----. “Hive Mind.” The Oxford Dictionary of Science Fiction. Oxford University Press, 2006.

Ross, Claire. “Social media for digital humanities and community engagement.” Digital Humanities in Practice, edited by Claire Warwick et al., Facet Publishing, 2012.

Seeley, Thomas D. Honeybee Democracy. Princeton University Press, 2010.

Terras, Melissa, et al. “Crowdsourcing in the Digital Humanities.” A New Companion to Digital Humanities, edited by S. Schreibman et al., Wiley-Blackwell, 2016.

Veletsianos, George. Social Media in Academia: Networked Scholars. Routledge, 2016.


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