Science communications and Twitter - preaching to the choir or singing from the rooftops?
A survey of scientists on Twitter
The following is an extract of the discussion from the peer-reviewed article Scientists on Twitter: Preaching to the choir or singing from the rooftops? published in the journal FACETS 2018; 3: 682–694; DOI: 10.1139/facets-2018-0002
Academic scientists on Twitter start by preaching to the choir but can eventually sing from the rooftops. Twitter is partly an echo chamber for academic scientists where, on average, tweeting academic scientists have more followers who are scientists than who are non-scientists.
This pattern is particularly marked for academic scientists who have fewer than 1000 followers: these academics are primarily followed by other scientists. However, beyond this threshold, the tweets of academic scientists can reach a more varied audience, composed primarily of non-scientists. Twitter then has the potential to function as an outreach tool.
Fig. 1. Conceptual depiction of inreach and outreach for Twitter communication by academic faculty. Left: If Twitter functions as an inreach tool, tweeting scientists might primarily reach only other scientists and perhaps, over time (arrow), some applied conservation and management science organizations. Right: If Twitter functions as an outreach tool, tweeting scientists might first reach other scientists, but over time (arrow) they will eventually attract members of the media, members of the public who are not scientists, and decision-makers (not necessarily in that order) as followers.
The extent to which Twitter allows academic scientists to reach broad audiences has, until now, been unclear. Indeed, the intended audience of many tweeting scientists is often limited to fellow researchers (Priem and Costello 2010; Collins et al. 2016), and disciplinary silos exist in social media, with little mixing across subject-specific networks of scientists (Ke et al. 2017).
However, the audiences of academics can be much more varied. Darling et al. (2013), for example, found that the followers of that paper’s four co-authors included academic, government, and non-governmental organization (NGO) scientists, students, and journalists. A survey of live tweeting from an international conservation congress similarly found that tweets from that conference reached a non-attending audience that was far more diverse than the conference participants (Bombaci et al. 2016).
Our results support these findings and show that audience heterogeneity rises over time, as the number of followers increases. Having more followers does not only mean a more diverse audience, but a vastly expanded reach. Academic scientists generally have limited reaches, i.e., they are followed by people (usually other academics) who have few followers. The broadening of diversity associated with a larger following also brings follower types that are more popular, drastically increasing the overall reach of scientific messages.
INFLUENCE AND REACH
Of course, high numbers, diversity, and reach of followers offer no guarantee that messages will be read or understood. There is evidence that people selectively read what fits with their perception of the world (e.g., Sears and Freedman 1967; McPherson et al. 2001; Sunstein 2001; Himelboim et al. 2013). Thus, non-scientists who follow scientists on Twitter might already be positively inclined to consume scientific information. If this is true, then one could argue that Twitter therefore remains an echo chamber, but it is a much larger one than the usual readership of scientific publications.
Moreover, it is difficult to gauge the level of understanding of scientific tweets. The brevity and fragmented nature of science tweets can lead to shallow processing and comprehension of the message (Jiang et al. 2016). One metric of the influence of tweets is the extent to which they are shared (i.e., retweeted).
Twitter users retweet posts when they find them interesting (hence the posts were at least read, if not understood) and when they deem the source credible (Metaxas et al. 2015). To our knowledge, there are no data on how often tweets by scientists are reposted by different types of followers. Such information would provide further evidence for an outreach function of Twitter in science communication.
AFFECTING POLICY CHANGE
Under most theories of change that describe how science ultimately affects evidence-based policies, decision-makers are a crucial group that should be engaged by scientists (Smith et al. 2013).
Policy changes can be effected either through direct application of research to policy or, more often, via pressure from public awareness, which can drive or be driven by research (Baron 2010; Phillis et al. 2013). Either pathway requires active engagement by scientists with society (Lubchenco 2017). It is arguably easier than ever for scientists to have access to decision- and policy-makers, as officials at all levels of government are increasingly using social media to connect with the public (e.g., Grant et al. 2010; Kapp et al. 2015).
However, we found that decision-makers accounted for only ∼3% (n = 191 out of 64 666) of the followers of academic scientists (see also Bombaci et al. 2016 in relation to the audiences of conference tweeting). Moreover, decision-makers begin to follow scientists in greater numbers only once the latter have reached a certain level of “popularity” (i.e., ∼2200 followers; Table 2).
The general concern about whether scientific tweets are actually read by followers applies even more strongly to decision-makers, as they are known to use Twitter largely as a broadcasting tool rather than for dialogue (Grant et al. 2010). Thus, social media is not likely an effective replacement for more direct science-to-policy outreach that many scientists are now engaging in, such as testifying in front of special governmental committees, directly contacting decision-makers, etc.
However, by actively engaging a large Twitter following of non-scientists, scientists increase the odds of being followed by a decision-maker who might see their messages, as well as the odds of being identified as a potential expert for further contributions.
BUILDING A TWITTER FOLLOWING
So how can a scientist build and engage with their Twitter following? In general, people who tweet more have more followers (e.g., Huberman et al. 2008; Kwak et al. 2010). Whether causal or simply correlational, the strength of this association is nevertheless variable and generally low (e.g., in this study, r = 0.48).
Moreover, the size of the following does not reflect how much followers engage with a user’s tweets, for example by retweeting (Avnit 2009; Cha et al. 2010). For audience engagement, content matters (Bik et al. 2015). Tweets that contain hyperlinks and hashtags are more likely to be retweeted (e.g., Nagarajan et al. 2010; Suh et al. 2010; Pang and Law 2017), as are tweets that contain images (e.g., Bruni et al. 2012). Even more important for the likelihood of being retweeted is the topical relevance of the tweet to the follower (Shi et al. 2017), which speaks to the need for scientists to make their message matter to their intended audiences (Baron 2010).
One final important lesson is that ordinary users that become influential (i.e., that are mentioned and (or) retweeted frequently) tend to limit their tweets to narrow topics (Cha et al. 2010). Thus, although Twitter influence can be gained accidentally because of timing, circumstance, or emotion (e.g., Jackson and Spencer 2017), it is more often the result of concerted and persistent effort.
We assume that the patterns we have uncovered for a sample of ecologists and evolutionary biologists in faculty positions can apply broadly across other academic disciplines. We acknowledge that the initial list from which we chose users at random was likely to be biased in several ways.
About 70% of users in the original list, and ∼75% in our sample of 110 users (Table S5), were from the USA or the UK, although this matches the global distribution of Twitter users (Kulshrestha et al. 2012). Our sample also included predominantly male users (69%), but again, this gender bias reflects accurately the underrepresentation of women in academic positions, particularly across science and technology (e.g., <30% in American public universities, Li and Koedel 2017).
Our selection of academics on Twitter also presents some bias through which academics choose to be on Twitter, who actively tweet about science, and who were selected to join the Twitter list we used in our analysis.
There are some documented disciplinary differences in use of Twitter. For example, in a comparison of 10 academic fields spanning the sciences and humanities, researchers in digital humanities tweeted the most, economists shared the most links, and biochemists retweeted more than academic users in other fields (Holmberg and Thelwall 2014). However, whether these differences translate into differences in rates of accumulation of followers, and of different follower types, among disciplines is unclear.
The greatest challenge for science communication is reaching the audience (Bubela et al. 2009). Today’s audiences are increasingly turning to unconventional media sources of information about specific scientific issues and away from online versions of traditional news outlets (National Science Board 2016).
Twitter, therefore, offers a timely means for academics to reach a wide popular audience. Here, we show that reaching a broad audience on Twitter is a non-linear process that requires a sustained online engagement, and may only occur past a certain threshold numbers of followers. Our results provide scientists with clear evidence that social media can be used as a first step to disseminate scientific messages well beyond the ivory tower.
Copyright: © 2018 Côté and Darling. This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.