Given that existing/outgoing care users express genuine comments on a specific care service (health or social care) and incoming users consult online reviews before visiting a health/social care venue, it is important for care providers and policymakers to be aware of authentic consumer evaluations on a real time basis and improve their service offering in the future. There are no studies of how consumers have perceived health/social care services over time and how ethnic minority consumers have experienced inequalities in accessing health and social care services. This project aims at conducting health and social care analytics through analysing big data of health and social care reviews to (1) help care users and families to select the best care service, (2) support care providers to identify and satisfy user needs, and (3) provide policymakers with strategic guidance about how to mitigate inequitable service access to vulnerable neighbourhoods. For the health care research, I have discussed with IWGC patient review platform, which intends to provide over 3 million reviews generated by anonymized patients for five years (2016-2022). In addition, I found that IWGC data include rich review and rating information with various reviewer characteristics, excluding personal information, such as (1) 14 UK regions (e.g., Wales, Greater London), (2) actual age (young, senior), (3) gender (male, female), (4) patient condition (short-term, long-term), and (5) ethnicity. For the social care research, we may attempt to collect (1) user-generated reviews about social care service and/or (2) government (e.g., Care Inspection Wales)-generated inspection reports. As of 6 September 2022, CAREHOME has 6,766 online reviews about 403 care homes in Wales and HOMECARE has 1,165 online reviews about 375 domiciliary care providers in Wales. After collecting review or report text data, we can use text mining techniques (i.e., natural language processing) to analyze qualitative/text data, which can provide a better understanding of authentic needs, wants and evaluations about particular care services generated by care users and care inspectors. This interdisciplinary project will offer sophisticated policy and strategic guidance to various health and social care stakeholders in terms of taking data-informed decisions. Research outcomes will provide Welsh/UK health/social care providers and policymakers with capabilities to use social media data for prompt decision-making, prediction and forecasting, and use of qualitative data/sentiment data to better deal with care demand.
Invited Speaker: [Seongsoo (Simon) Jang (Senior Lecturer of Marketing, Cardiff Business School)
Bio: Dr. Jang is a Senior Lecturer of Marketing in Cardiff Business School at Cardiff University. As an interdisciplinary empirical researcher, he does quantitative research on digital marketing, health/sustainability marketing, and tourism analytics by (1) using real-world data collected from two-sided platforms, mobile app operators, and other commercial sources, (2) combining psychology/behavioral theories and advanced methods (hierarchical modeling, text mining, and spatial analytics), and (3) addressing contemporary marketing and business problems. He has published in decent marketing and tourism journals, including Journal of Product Innovation Management, British Journal of Management, Journal of Public Policy and Marketing, Journal of Business Research, Annals of Tourism Research, Tourism Management, Journal of Travel Research, and International Journal of Hospitality