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Zillmann (1988) argued that individuals choose content to optimize their affective state—seeking exciting content when bored or relaxing content when stressed. However, recent studies suggest that short-form video platforms exploit this tendency by creating a “mood matching” loop that discourages exposure to dissonant or challenging material (Tam & Walter, 2022).

Wu (2016) describes how social media and streaming services compete for user attention by minimizing “friction” (e.g., auto-play, infinite scroll). This design logic directly serves emotional avoidance—the desire to escape negative feelings—rather than emotional processing. GirlCum.24.06.01.Ashlyn.Angel.Orgasm.Chair.XXX....

Data from a 2023 survey of 1,200 streaming users found that 68% deliberately rewatch familiar series (e.g., The Office , Friends ) to reduce post-work anxiety (Lee & Cho, 2023). This “comfort content” provides predictability and a sense of control—key components of effective emotional self-regulation. Algorithms that surface such content can function as a digital security blanket. Zillmann (1988) argued that individuals choose content to

Katz, Blumler, and Gurevitch (1973) proposed that audiences actively select media to fulfill specific needs, including diversion, personal relationships, and identity exploration. In the streaming era, this theory remains relevant but requires updating: algorithmic recommendations now pre-select gratifications, reducing conscious choice. Algorithms that surface such content can function as