Since an adequate academic definition of social media voice (SMV) is lacking or missing, Ravi Singh Dissertation defines social media voice as the method by which a social media user communicates in a comprehensible manner on a social media platform (SMP) to other users. SMV tell your brand's story. SMV is the selection of the type of tone, the polarity of sentiment, the structure of lingo, and the frequency of selection of words to express messages on a social media platform to direct interactions with others. SMV consists of the tone, sentiment, lingo, and pulse of a message (i.e., tweet).  It establishes the purpose of a social media leader (SML).  The SML uses his or her SMV to accomplish a specific purpose.  Leaders use SMV when they update on a social media platform like Twitter. It's highly important because it has a humanizing effect on your brand.

Middle-Range Theory

By definition, the middle-range theory is an approach to sociological theorizing aimed at integrating theory and empirical research. As Robert K. Merton, founder of middle-range theory suggests, a commitment to an idea like SMV, is a commitment to developing special theories applicable to limited conceptual ranges. In his Dissertation, Ravi Singh, concludes with an interpretation of findings that may support the creation of a new middle-range theory, or empirical method for measuring predictors of engagement on Twitter.

The middle-range theory suggests that Social Media Voice can be used in predicting engagement by likes, retweets, and replies. Meaning that the type of voice used on a social media post impacts engagement, and that can be assessed by the number of likes a post/tweet receives. For instance, in the Dissertation, 3 different personas (business executive persona (BEP), the political candidate persona (PCP), and the world leader persona (WLP) were analyzed, and findings show that each persona had unique engagement due to the voice used by Donald Trump between May 4, 2009, and November 6, 2018. Under each persona, the independent variables of sentiment, intensity, volatility, frequency deviation, and mentions impact follower engagement positively or negatively. The study helps understand that the voice or tone used on a post can create more or less engagement, and also the frequency of tweets is important because excessive tweeting in a short succession of time (measured by a pulse: frequency deviation and volatility) causes a decrease in engagement. For example, under political candidate persona tweets revealed that the independent variables of sentiment, intensity, volatility, frequency deviation, and mentions related negatively to the number of likes.  There was a significant positive relationship between retweets (RT) and #hashtags related to the number of likes.  Tone intensity and emojis were not significantly related to the number of likes.  The model summary for persona 2, in terms of likes as the dependent variable, accounted for 69.4% of the variance.  This suggests that social media voice explained a large degree of the variance in a number of likes.

Below is an abstract from the Dissertation, if you would like to read more on social media voice and how it impacts follower engagement measured by the number of likes, retweets, and replies a post gets, you can download or purchase the 450 pages dissertation.

Abstract

It is not just what Donald Trump says; it is how Donald Trump says it.  This study focused on the impact of social media voice (SMV) on the @realDonaldTrump official Twitter account.  The study provided empirical evidence that SMV (tone, sentiment, ling, and pulse) of the leader, Donald Trump, was associated with follower engagement on the social media platform Twitter, while controlling for the number of followers.  The quantitative study utilized chi-square, ANOVA, multiple regressions, and hierarchical regression analyses.

The research design measured the association between SMV (specifically dominant tone) and social media engagement (likes, retweets, and replies).  A longitudinal analysis of the @realDonaldTrump account identified 35,647 tweets that were confident, analytical, tentative, sad, fear, angry, and joyful as defined by the International Business Machines Corporation (IBM) Watson Tone Analyzer®, an artificial intelligence software platform.  The data was divided into three branded leadership personas: business executive, political candidate, and world leader.

Three theories guided this research: digital rhetoric theory, social presence theory, and distributed leadership theory.  Findings concluded that SMV was related to engagement and tone contributed to SMV.  Donald Trump’s use of joy, frequency deviation, and tone intensity within his tweets decreased engagement while negative sentiment and tone types increased engagement.  It was found that the three leadership personas had different SVM's.  Digital Lingo (hashtags, emojis, and abbreviations) contributed to increased engagement, while (@) mentions did not.  Proposed is a middle-range theory associated with SMV and engagement that measures social media volatility, social media frequency deviation, return on tone, social media saturation, and social media pulse.

Key Words: social media, voice, tone, engagement, lingo, pulse, sentiment, leadership, Donald Trump, Twitter, social media engagement, likes, retweets, replies, return on tone, social media, social media platform, social media leadership, social media voice, social media pulse, social media saturation, and Twitterism.