034 Citation: Whissell C (2020) The increasing frequency of president donald trump’s social communications: Is there a limit? Trends Comput Sci Inf Technol 5(1): 034- 036. DOI: https://dx.doi.org/10.17352/tcsit.000016 https://dx.doi.org/10.17352/tcsit DOI: 2641-3086 ISSN: ENGINEERING GROUP Since he became president of the US in 2017, Donald Trump has been tweeting more and more frequently on a daily basis, to the point where both political analysts and the general public have begun to comment. In several cases, more than 100 tweets have been posted in a single day. The president has other means of communicating via social media but currently tweets posted from an iPhone on the account @realDonaldTrump are by far his most common outlet. These tweets are marked as favorites by millions of followers and retweeted by hundreds of thousands of them on a regular basis. Some (6-7%) of the president’s posts are in fact retweets. This brief article describes the rise in messaging rate during the first 41 months of Trump’s presidency. The function relating time (months in office) to messaging rate is described, and its limit (in terms of real-life controls on messaging) is estimated. The research is conducted in the full realization that messaging data are not necessarily trustworthy, and that the author and the audience may both be other than they seem. What is being analyzed is that which is offered to the public, with no guarantees. Trump’s tweet volume has been studied previously (TweetBinder blog, n.d.). His tweets were seen to peak when he entered politics, and they decreased in frequency after his election, after which they rose again. The attention paid to the president’s tweets is such that even misspellings (such as the famous “covfefe” or “smocking” appearing in lieu of “smoking”) draw extreme attention and many follow-up messages [1]. The function relating messaging rate to time may have a mathematical limit, but it is more likely that messaging rate will be constrained by everyday realities. Killeen’s classic mathematical learning theory predicting behavior [2] includes a factor of constraint. Constraint is defined as anything that limits the possible response output rate – e.g. the hours in a day or muscle fatigue. A behaviour will decrease in frequency when constraint is high and increase when it is low. Killeen and Sitomer point out that “the time required to respond constrains maximum response rates” [2]. Method Trump’s social messages were accessed at the website trumptwitterarchive.com (n.d.). Those studied occurred between January 1 st , 2017 (when Trump was awaiting his inauguration) and May 31 st , 2020 (when the research described in this paper began). The main criterion of the research was messaging rate. Daily rates were calculated by dividing each monthly rate by the number of days in the month. Because the function relating month to rate was quadratic in shape, the square of month was also included as a predictor. Additional predictors were the general and Republican approval ratings for the president during the first week of each month, as reported in Gallup polls posted online (n.d.). A stepwise linear regression was employed to predict daily messaging rate from month, the square of month, and the two approval ratings. Abstract This brief article offers a regression formula which accurately predicts Trump’s messaging rate as president (R=.96, p<.001). Rate is a quadratic function of months in office, with Republican approval rating entering the formula with a negative weight. The function has no mathematical limit, but real-life constraints associated with time available for messaging are discussed and exemplified, and a maximum messaging rate (150 messages daily, in an ongoing pattern) is suggested. Research Article The increasing frequency of president donald trump’s social communications: Is there a limit? Cynthia Whissell* Psychology Department, Laurentian University, Sudbury, Ontario, Canada Received: 04 July, 2020 Accepted: 27 July, 2020 Published: 28 July, 2020 *Corresponding author: Cynthia Whissell, Psychology Department, Laurentian University, Sudbury, Ontario, Canada, E-mail: Keywords: Social messaging; Trump; Volume https://www.peertechz.com