Prior studies measure organizations’ visibility on Twitter through the estimation of its audience including the number of followers and followings, numbers retweets, favorites, and replies. However, these indicators only measure the visibility based on the interactions of active audiences. Meanwhile, audiences on social media exist in different modes of seeing. They are also passive/invisible audiences, who see but do not interact/reveal themselves and those are proactive to discuss organizations without being fans of those organizations. More importantly, these indicators cannot reflect the mobility of audiences and content diffusion on social media, in which, each user can become a bridge to transmit information and network from this cluster of audiences to another.
To overcome the drawbacks of previous indicators, this study uses “extended audiences” and Socially Mediated Visibility theory to re-define audience measurements and use them to quantify the visibility of organizations. Two old indicators are kept, which are the number of retweets and replies; two new indicators are developed which are the number of organizations’ mentions and audience reach. Using multivariate tests and content analyses, the study found that previous results might have underestimated the visibility of organizations. Based on the new measurements, the study shows that a typical non-profit organization in the Nonprofit Times 100 list has more than 529,000 followers and receives 906 mentions, retweets, replies in a 2-week period. However, the actual number of social media users they could reach is more than 15.7 million. This is to say, audiences on social media are more extended and unintended than those measured in previous studies. In addition, as the number of organizations’ mentions is used as one of visibility measurement, it is found that there is also reciprocity in targeting strategy and communication tones. Organizations that mention other users more often are more likely to get mentions from audiences in return, and organizations communicate in positive tone will not likely to receive negative responses. Results also show that with the new indicators for organizational visibility, among predictors, only the number of followers, tweet volume, and the number of tweets that contain user mentions are significant to predict the visibility of organizations.
The study makes several contributions to the existing theories. First, it contributes to the literature of the Socially Mediated Visibility theory, which is still a new branch of visibility. Second, within the non-profit landscape, the study contributes to current literature research regarding organizational visibility and public attention with new measures of visibility. Third, the results help to explain why some organizations can make them visible and others cannot.