Textual paralanguage and its implications for marketing communications

Abstract

Both face‐to‐face communication and communication in online environments convey information beyond the actual verbal message. In a traditional face‐to‐face conversation, paralanguage, or the ancillary meaning‐ and emotion‐laden aspects of speech that are not actual verbal prose, gives contextual information that allows interactors to more appropriately understand the message being conveyed. In this paper, we conceptualize textual paralanguage (TPL), which we define as written manifestations of nonverbal audible, tactile, and visual elements that supplement or replace written language and that can be expressed through words, symbols, images, punctuation, demarcations, or any combination of these elements. We develop a typology of textual paralanguage using data from Twitter, Facebook, and Instagram. We present a conceptual framework of antecedents and consequences of brands' use of textual paralanguage. Implications for theory and practice are discussed.

Creating Brand Meaning: A Review and Research Agenda

“…A nonexhaustive list (See footnote 1) of these individual (sets of) cues or stimuli would include: Visual cues used in advertising and packaging (Pracejus, O'Guinn, & Olsen, ; Scott, ), including aesthetic (Hagtvedt & Patrick, ; Schmitt & Simonson, ) and rhetorical styles (McQuarrie & Mick, , ); color, as used in packaging or advertising or logos (Labrecque & Milne, ); typefaces (Grohmann, ); logo designs (Henderson & Cote, ; Jiang, Gorn, Galli, & Chattopadhyay, ); and packaging shape and labels (Orth & Malkewitz, ; Van Rompay & Pruyn, ); Sensory cues , such as types of music (Zhu & Meyers‐Levy, ), and the sound (phonetic characteristics) of brand names and of speech patterns (Lowrey & Shrum, ; Spence, ); Human cues , such as types of advertising endorsers (McCracken, ), types of props and clothing (Solomon & Greenberg, ), and the “body language” (gestures, eye gaze, use of physical space, facial cues, etc.) used in advertising (Haley, Richardson, & Baldwin, ), some of which are used today in social media via text equivalents (Luangrath, Peck, & Barger, ). …”

How online word‐of‐mouth impacts receivers

“…Third, reviews vary in their use of textual paralanguage (TPL; e.g., exclamation marks and emoji; Luangrath, Peck, & Barger, ). Excessive TPL in a negative review produces a player signal that the sender is emotional and irrational, which decreases the informativeness of the review and its impact on receivers’ product evaluations; however, this effect is attenuated when multiple negative reviews contain excessive TPL (Kim & Gupta, )—in this case, the consensus among senders shifts the signal to the product, rather than the player.…”

“…Given that text communication lacks verbal and non‐verbal paralanguage, such as talking speed or facial expressions, textual paralanguage (TPL) is used to express audible, tactile, or visual elements of face‐to‐face communication through punctuation, style (e.g., bold font), capitalization, or emoji (Luangrath et al, ). Most research has explored TPL indirectly, in the process of manipulating other linguistic content, such as emotionality (Kim & Gupta, ), arousal (Yin et al, ), or humor (McGraw et al, ).…”

“…Indeed, although TPL commonly functions to clarify or intensify other message content (Derks, Bos, & von Grumbkow, ), it can be used in multiple ways. This is particularly true of emoji, which can communicate meaning independent of text (Moore, Das, & Mukhopadhyay, ) and can express various aspects of paralanguage (e.g., hand gestures, facial expressions, body movements; Luangrath et al, ).…”

Human or Bot? How (Corrected) Errors Humanize a Communicator

“…For instance, emphasizing words with exclamation points, Internet slang (e.g., "lol"), emoticons (e.g., ":-D"), emojis, and words altered to simulate verbal speech (e.g., "sooooo….") can enhance perceptions of the communicator's humanlike mental states (Luangrath, Peck, & Barger, 2017). In addition, handwritten-like typefaces on a product can create a sense of human presence and lead to more favorable product evaluation (Schroll, Schnurr, & Grewal, 2018), whereas a machine-like typeface makes people more likely to correctly identify chatbots as computers (Candello, Pinhanez, & Figueiredo, 2017).…”