Textual paralanguage (TPL) refers to “nonverbal audible, tactile, and visual elements” that can be represented in various ways (Luangrath, Peck, and Barger 2017), such as pictorial icons within text (i.e., emojis) and visual cues formed from typographical symbols (i.e., emoticons). This thesis explores the effects of TPL in digital marketing. The first essay examines the impact of emojis in online product reviews. The results of two field studies and five experimental studies show that (a) high-imagery (low-imagery) emojis have a greater (smaller) effect on review helpfulness, (b) the presence of product images in online reviews reduces the effect of emojis, and (c) positive (negative) emojis increase (decrease) purchase intention. The second essay presents a conceptual framework and employs a meta-analytic approach to investigate the effects of TPL. Synthesizing 239 effect sizes from empirical studies across multiple disciplines, this essay identifies two key findings. First, different types of TPL predominantly evoke affective responses, while some may elicit more cognitive responses. Second, across all contexts, using TPL in an inauthentic manner might backfire. The third essay explores how emojis influence online written conversations that lack audio-visual cues. We applied unsupervised machine learning methods to detect topic changes in turn-taking conversations. Using two conversation samples from Twitter, we find that emojis increase the number of topics covered in a conversation. Furthermore, results from three online experiments reveal that emojis increase the willingness of recipients to take more conversation turns and cover more conversation topics.