Zhong, B; Tian, J; Pan, X and Shen, L (2024) An online housing reputation assessment framework based on text mining and visualization technologies. Journal of Construction Engineering and Management, 150(8): 04024076, ISSN 0733-9364
Abstract
Learning from online comments is essential for enhancing understanding and improving online housing reputation (OHR). However, two significant issues require attention. First, analyzing online comments for reputation information extraction is a labor-intensive and time-consuming task. Second, most existing online housing information platforms lack effective visual aids, merely presenting the average comment ratings or listing comment texts without secondary interpretation. To address these challenges, this study proposes an OHR assessment framework based on text mining and visualization technologies. This study first evaluates the performance of eight sentiment analysis models for analyzing housing comments, and the attention-based BiLSTM model achieved the highest accuracy (83.57%). Additionally, a housing attribute ontology is constructed to reveal eight critical attributes influencing OHR. Finally, a reputation visualization scheme is designed to comprehensively present OHR. A case study for analyzing online comments from three construction enterprises reveals the advantages and feasibility of the proposed framework for assessing OHR. This study contributes to the body of knowledge by establishing the connection between housing comments and OHR, greatly advancing the research in the construction domain's reputation management. Furthermore, OHR analysis can facilitate decision making optimization for both consumers and managers, which has theoretical and practical significance for the healthy and sustainable development of the online housing market.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | online comments; online housing reputation; reputation analysis; reputation visualization; text mining |
| Index terms: | body of knowledge, manager, housing, case study, accuracy, platform, visualization, mining, ontology, housing information, decision-making, sustainable development |
| Subjects: | geotechnical engineering, construction type, health safety and environment, decision analysis, data collection methods, practitioner, knowledge management, design practice, economic analysis, digital design, professional development, education and knowledge transfer |
| Topics: | Construction Technology, Roles and Professions, Digital Applications, Risk Management, Research Practice, Engineering Principles, Design Practice, Health and Safety, Information Management |
| Descriptive scope: | 4 PCTE |
N.B. Descriptive scope is a count of how many of the five facets of empirical research are indicated by the words used in title, abstract and keywords. It is not intended as a judgement on the research; merely a count of the kind of word we would expect to indicate Phenomenon, Concepts, Theoretical framing, Empirical techniques, Analytical techniques. If all five are present, then a code of “5 PCTEA” will indicate this. If you feel the coding for this record is questionable, we welcome discussion around the terms we matched or the way we categorized them. The facet you would expect may not be coded, or a facet may be coded inappropriately. This can also bear on a larger question, of which facets should be treated as defining in construction management research. Please get in touch, and we will look at it. More details here