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During the initial phase of the COVID-19 crisis, Kuwait introduced the Shlonik mobile contact tracing application (app). Implemented by the Central Agency for Information Technology and developed by the mobile communications company Zain, the app was designed to support tracing quarantined citizens, allow a connection with them, and support the delivery of critical information (Ministry of Health, Kuwait). Through the Shlonik app, the ministry could monitor the location of quarantined people 24/7, along with persons with whom they may come into contact. Quarantined people could also enter their vital data into the app and communicate with relevant medical teams if any symptoms appeared (Communication & Information Technology Regulatory Authority, 2022).
Digital contact tracing apps symbolized the permeation of technology into all aspects of citizens’ lives and were particularly stringent during the pandemic (Akinbi et al., 2021). Social media was another prevalent technological tool during this period, providing a source of trending information for many domains. Both users and providers utilized social media in all areas of business, crisis management, healthcare, and politics. This also resulted in “[an] enormous growth of social media usage… [leading to] an increasing accumulation of data, which has been termed Social Media Big Data” (Stieglitz et al., 2018, p. 156). Twitter, one of the most prominent social media platforms, contributed to this mass accumulation (Naseem et al., 2021). Not unexpectedly, the outbreak of the pandemic and accompanying lockdowns prompted a flood of social media postings as people sought information to allay their fears and share opinions and experiences (Chen et al., 2014; Zou et al., 2018). Twitter recorded the lived experiences of diverse groups (Tsao et al., 2021), introducing a new potential format for research data collection differing from conventional methods such as interviews, surveys, and focus groups (Chen et al., 2014). Notably, some researchers perceive traditional sources as restrictive when collecting respondents’ opinions compared to the potential of disorganized and unstructured data on social media platforms (Chen et al., 2014). Therefore, social media data gained considerable attention and legitimacy from policymakers and academics (Stieglitz et al., 2018). We considered Twitter data appropriate for this study, with its specific aim of exploring users’ experiences with contact tracing.
Kuwait, one of several oil-rich developing countries, has a population of 4.329 million (World Bank, 2021). As in other countries, Kuwaiti residents resorted to social media to express their opinions about contact-tracing apps (Akinbi et al., 2021). The Shlonik contact-tracing app generated feedback from Kuwatis, who posted comments about their experiences on Twitter. This research uses the Twitter dataset to explore users’ opinions about the system quality (usability, availability, reliability, adaptability) and service quality (technical and medical features) of the Shlonik app.