Phrasing for UX: Enhancing Information Engagement through Computational Linguistics and Creative Analytics

This underscores the critical role of information as a precursor to knowledge, rather than knowledge itself (Zins, 2007; Frické, 2009). In digital environments, symbols, letters, words, and phrases have the potential to contribute to knowledge formation, necessitating effective communication and optimal information presentation for Information Systems (IS) success (Delone & McLean, 2003; Venkatesh & Bala, 2008; ISO, 2019). Engagement, defined as the emotional, cognitive, and behavioral connection between users and technological resources, has emerged as a key metric for evaluating user experience (UX), reflecting user interaction depth with a system (O'Brien et al., 2020; Attfield et al., 2011; O'Brien & Cairns, 2016). The digitization of communication through Information and Communication Technologies (ICT) has revolutionized information conveyance, demanding engaging and effective digital content to ensure successful knowledge transmission and user retention (Beaudry, 2005; Dvir, 2018). Information Engagement (IE) has gained prominence, focusing on the quality of user-system interactions and the impact of digital content design on user decision-making and UX (ISO, 2019; O'Brien, 2020). IE is crucial in enhancing user interactions across domains such as education, government, and industry, aiming to foster meaningful user engagement with digital text (Choi et al., 2018; Feng et al., 2020; Han et al., 2022). Failure to achieve IE with digital text hinders content producers, yet overcoming this challenge is complicated by a lack of engaging information experience guidelines (Blythe, 2005; Overbeeke et al., 2003). Limited research on IE development has resulted in a scarcity of systematic approaches for its initiation, sustainment, and improvement (O'Brien, 2017; O'Brien & Toms, 2016).