On 2017 Mar 10, Melissa Vaught commented:

Prior randomized controlled trials have examined the impact of organizational social media promotion (i.e., using journal’s official social media accounts) on article views (Fox CS, 2015, Fox CS, 2016, Adams CE, 2016) or on article downloads and citations (Tonia T, 2016). With the exception of Adams CE, 2016, no significant effect of social media posting on page views or downloads has been observed. However, a key question has remained: Might sharing by individuals have an effect where publisher promotion has not?

The trial reported here attempts to address this question directly. The authors enlisted members and trainees on its editorial board to share links to articles from their personal social media accounts (enhanced Twitter intervention). Outcomes were compared to control and to sharing via the journal’s official Twitter account (basic Twitter intervention). Selected publications were between 2 months and more than 2 years old at the time of intervention.

Similar to Fox CS, 2015, Fox CS, 2016, & Tonia T, 2016, posts by the @JACRJournal account did not increase article views (though removing a ‘most read’ outlier that had been randomized to the control group changed this conclusion). As summarized in the abstract, weekly page views were higher in the enhanced intervention than in control and basic groups. In fact, the enhanced group outperformed the basic group in all 4 primary and secondary endpoints. Authors found no significant effect of publication age.

The authors note that the difference between enhanced and basic groups may derive from multiple vs. single posting of a link. The difference in effects is not proportional to the number of posts, and as the authors note, Fox CS, 2016 used a high frequency social media posting to no avail. In addition, the JACR authors observed that 1 team had a much larger effect on page views than the other 3, and the effect did not track with follower count.

I would first note that some limitations in the methods and/or reporting might influence interpretation of these comparisons. Methods state that team members were assigned 1 article to tweet per day, and they were to only post about each article once. However, there is no indication that participants’ accounts were reviewed to check adherence to the instructions, in particular whether all 4 team members posted the assigned article with a functioning link on the designated day. It was unclear to me whether team members were sent a link the day they were assigned to post it, or whether these might have been provided in batches with instruction to tweet on the assigned day. The article also does not discuss how teams were assigned and whether members knew who their teammates were. Finally, although the team effect did not correlate with follower number, it would have been useful to know the number of followers for @JACRJournal at the start of the intervention, for comparison.

Nonetheless, the outsized effect on outcomes for 1 team is interesting. Though largely beyond the scope of this article, additional analytics could provide the basis for some interesting exploratory analysis and might be worth consideration in future studies of this type. At the Twitter account level, the authors reported the number of followers for each team member, but the age and general activity of the account during the intervention period could be relevant. Follower overlap between team members (or more refined user network analysis, as suggested by the authors) might also be informative.

It also might have been useful to also gather tweet-level analytics from team members, to identify high-engagement tweets (e.g., based on URL clicks and/or replies). This could determine whether team performance was driven by a single member, particular publications/topics, or discussion about a publication. I liked that team members composed their own tweets about articles, so that there was a chance for the tweets in the intervention to have congruent “voice”/style. Pairing tweet-level analytics with content analysis—even as simple as whether a hashtag or an author’s Twitter handle were included—could offer some insight.

Overall, I appreciate this authors’ efforts to untangle questions about how organizational and individual social media promotion might differentially influence viewing (and perhaps reading) of scholarly publications.

On 2017 Mar 10, Melissa Vaught commented:

Prior randomized controlled trials have examined the impact of organizational social media promotion (i.e., using journal’s official social media accounts) on article views (Fox CS, 2015, Fox CS, 2016, Adams CE, 2016) or on article downloads and citations (Tonia T, 2016). With the exception of Adams CE, 2016, no significant effect of social media posting on page views or downloads has been observed. However, a key question has remained: Might sharing by individuals have an effect where publisher promotion has not?

The trial reported here attempts to address this question directly. The authors enlisted members and trainees on its editorial board to share links to articles from their personal social media accounts (enhanced Twitter intervention). Outcomes were compared to control and to sharing via the journal’s official Twitter account (basic Twitter intervention). Selected publications were between 2 months and more than 2 years old at the time of intervention.

Similar to Fox CS, 2015, Fox CS, 2016, & Tonia T, 2016, posts by the @JACRJournal account did not increase article views (though removing a ‘most read’ outlier that had been randomized to the control group changed this conclusion). As summarized in the abstract, weekly page views were higher in the enhanced intervention than in control and basic groups. In fact, the enhanced group outperformed the basic group in all 4 primary and secondary endpoints. Authors found no significant effect of publication age.

The authors note that the difference between enhanced and basic groups may derive from multiple vs. single posting of a link. The difference in effects is not proportional to the number of posts, and as the authors note, Fox CS, 2016 used a high frequency social media posting to no avail. In addition, the JACR authors observed that 1 team had a much larger effect on page views than the other 3, and the effect did not track with follower count.

I would first note that some limitations in the methods and/or reporting might influence interpretation of these comparisons. Methods state that team members were assigned 1 article to tweet per day, and they were to only post about each article once. However, there is no indication that participants’ accounts were reviewed to check adherence to the instructions, in particular whether all 4 team members posted the assigned article with a functioning link on the designated day. It was unclear to me whether team members were sent a link the day they were assigned to post it, or whether these might have been provided in batches with instruction to tweet on the assigned day. The article also does not discuss how teams were assigned and whether members knew who their teammates were. Finally, although the team effect did not correlate with follower number, it would have been useful to know the number of followers for @JACRJournal at the start of the intervention, for comparison.

Nonetheless, the outsized effect on outcomes for 1 team is interesting. Though largely beyond the scope of this article, additional analytics could provide the basis for some interesting exploratory analysis and might be worth consideration in future studies of this type. At the Twitter account level, the authors reported the number of followers for each team member, but the age and general activity of the account during the intervention period could be relevant. Follower overlap between team members (or more refined user network analysis, as suggested by the authors) might also be informative.

It also might have been useful to also gather tweet-level analytics from team members, to identify high-engagement tweets (e.g., based on URL clicks and/or replies). This could determine whether team performance was driven by a single member, particular publications/topics, or discussion about a publication. I liked that team members composed their own tweets about articles, so that there was a chance for the tweets in the intervention to have congruent “voice”/style. Pairing tweet-level analytics with content analysis—even as simple as whether a hashtag or an author’s Twitter handle were included—could offer some insight.

Overall, I appreciate this authors’ efforts to untangle questions about how organizational and individual social media promotion might differentially influence viewing (and perhaps reading) of scholarly publications.