Contributions and Connections

What counts as academic influence on Twitter.

April 6, 2015

Those who work within the academy become very skilled at judging the stuff of reputations. Where has the person’s work been published, what claims of priority in discovery have they established, how often have they  been cited, how and where reviewed, what prizes won, what institutional ties earned, what organizations led?  - Willinsky, 2010, p. 297


In the academy, reputations and influence measures speak to status and standing. They circulate signals of capacity and credibility by boiling down complex indicators: the journals we publish in, the school(s) we’re affiliated with, our citation counts and h-indexes, our last grants, our ranks in the academic hierarchy. These proxies for quality combine prestige, metrics, and recognizability into a mercurial mix that can be circulated and understood across disciplines and ideological lines, but never quite reduced to its component parts.

Part of academic training, as Willinsky suggests, is the cultivation of identities who grasp, internalize, and bolster this circulation of influence. This helps us make sense of each other, sure, but it also has effects. Our conference, grant, and academic publishing systems are buttressed by Impact Factors and influence metrics, which reinforce the known and familiar even in the face of potentially more effective or inclusive forms of dissemination and knowledge-building.

Enter Twitter. As more and more academics take to Twitter and other networked platforms to connect and share their work and ideas, a new sphere of influence is opening. And it is beginning to infiltrate academia itself. Twitter is often framed as a more effective way to get fired than hired, but networked scholarly participation can be a powerful site of new contacts and resources and conversations for a scholar, as well as new conventions (hello #hashtags!) and new public audiences for research. Increased citations, media gigs, collaborative research opportunities, invited talks and keynotes, and a variety of other academically-valued material effects can stem from active and sustained networked engagement.

This creates tensions. Open networked scholarship is, by definition, open to those who choose to participate; it demands only the construction, performance and curation of public scholarly identities as a price of admission. But these are not the credentialed terms of entry sanctioned by what Willinsky refers to as the academy’s “stuff of reputations.” Academia’s complex prestige hierarchy is reliant on gatekeeping and competition. Forms of influence based in open participatory practices are by definition illegible – and even illegitimate – within that system.

So, if nobody needs to go through a gatekeeping institution to contribute to knowledge anymore, is networked scholarship a free-for-all? Or does it have its own implicit indicators for credibility and influence and reputations? Do scholars who live and work immersed in networks as well as academia read and circulate networked influence signals that the academy is, as yet, unable to make sense of?

Turns out they do. Last year, I conducted an in-depth, participatory, ethnographic study of scholars who actively use Twitter in addition to their institutional scholarly endeavours. Here’s some of what I found out about how influence and credibility circulate in academic Twitter.

1.   The conversation is what counts.  A concept of “The Conversation” – meaning discussions of import both in their particular fields and across higher ed – circulates widely amongst active Twitter scholars. All participants in the study were engaged in curating and contributing resources to a broader conversation in their field or area of interest. It was capacity for contribution to this larger conversation that counted most in participants’ assessments of others’ influence.

2.   Assessments of influence in networks are individually-centered, rather than institutionally-centered. This may be an interim or transitional feature of networked scholarly influence, while the platforms and their place in scholarship emerge and mature, but while the signals on which actively-networked scholars base their judgements are still quick proxies for quality, they are proxies interpreted against individual understandings of “The Conversation,” rather than generic and hierarchical ideals of scholarly role.

3.   Metrics matter, but not that much. Participants in the study tended to assess size of account – over 10,000 followers, in particular – as a general signal of influence, but perception of capacity for contribution was far more important to scholars’ assessments of who they would follow, and why. Number of tweets –understood to indicate longevity and thus likelihood of ongoing contribution – mattered more in participants’ estimation of an account’s influence and value than number of followers.

4.   Commonalities are key. The perception of a scholar’s credibility and capacity for contribution is created and amplified by common interests, disciplines, and share ties and peers. Participants were most likely to assess accounts as credible and likely to make a contribution if they were followed by users the participant already knew and respected. Professional and personal commonalities were also central to perceptions of others’ capacity to contribute, but less visible in assessments of credibility.

5.   Institutional signals and affiliations aren’t that important. Except in the case of one profile with an Oxford university affiliation, institutional status signals were not accorded significant value in assessments of networked influence. Though all participants were institutionally-affiliated and well aware of the prestige of academic ranks, journal titles, and institutional brands, these were not interpreted as intersecting meaningfully with capacity to contribute to the networked conversation. In fact, profiles that emphasized institutional status were understood by a number of participants as signaling their lack of interest in participatory engagement.

6.   Automated signals indicate low influence. Automated daily tweets and link aggregators such as paper.li were seen as indicators of low engagement and low networked influence, in part because these services are seen as violating implicit social contracts of active, personal curation and direct citation within academic Twitter.

What these findings suggest, all together, is that scholars assess the networked profiles and behaviors of peers through a logic of influence that is – at least as yet – neither codified nor especially numeric. Instead, while academic Twitter’s concept of influence recognizes status, standing, and scale, it appears to focus primarily on contribution. This suggests that tools like Klout which claim to quantify networked impact and influence may be of limited use for scholars seeking out interesting peers to follow on Twitter.

Whether networked influence remains a separate sphere or gets pressed into service as a sedimented, rationalized academic signal remains to be seen – for the moment, however, it is interesting to observe a sphere of scholarly exchange in which content and relational connections play a greater role in the evaluation of influence than hierarchies and the status quo.

Bonnie Stewart is an educator and social media researcher fascinated by who we are when we're online. Bonnie has spent the last 15 years exploring the intersections of knowledge and technologies, and currently researches the implications of networks for scholarship, attention, care and vulnerability. Published in Salon.com, The Guardian UK, and Inside Higher Ed, Bonnie teaches technologies, literacies, communications, and adult learning at the University of Prince Edward Island. She does her best thinking aloud, on Twitter, as @bonstewart.

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