Since the launch of DiVoMiner®, many academic researchers and students have been adopting it for publishing academic papers. Here are some examples:
1. “We constructed an online reliability test bank with a 10% randomly selected sample at DiVoMiner® for independent coding by three coders.”
Gao, H., Zhao, Q., Ning, C., Guo, D., Wu, J., Li, L. (2022).Does the COVID-19 Vaccine Still Work That “Most of the Conﬁrmed Cases Had Been Vaccinated”? A Content Analysis of Vaccine Effectiveness Discussion on Sina Weibo during the Outbreak of COVID-19 in Nanjing. J. Environ. Res. Public Health, 19/241.
2. “With optional filtering of articles, the tailored task powered by DiVoMiner® is coming with a web browser extension through which news articles can be categorized.”
Chang, A. (2020). Misinformation from Web-based News Media? Computational Analysis of Metabolic Disease Burden for Chinese. In Multidisciplinary International Symposium on Disinformation in Open Online Media (pp. 52-62). Springer, Cham.
3. “Specifically, based on the internal rules of mining text, DiVoMiner® guided the machine to automatically label obesity and its related keywords. The classification results of algorithm coding generated by DiVoMiner® were obtained simultaneously.”
Chang, A., Jiao, W. & Liu, M. T. C. (2021). Obesity communication with etiology and disease: Automated content analysis of digital Chinese news in Mainland China, Hong Kong and Taiwan. JMIR Public Health and Surveillance (JPHS). 7(11).
DiVoMiner® is well known for its AI-aided content analysis capability which allows users to design, conduct and present their research all in one simple tool. So how to quote DiVoMiner® for your research? Here are some references:
(1) This study uses DiVoMiner®: an AI-aided Content Analysis (ACA) platform for data processing and analysis.
(2) The semantic machine learning model having been introduced into DiVoMiner®, the textual mining and analysis platform can not only be used for manual coding, but also for machine coding, analysis of the correlation between multiple variables, cross analysis, regression analysis, statistical verification, and the creation of word clouds.
(3) This study uses the method of AI-aided Content Analysis (ACA). Based on the quantitative approach of content analysis, the text is coded, classified, semantically and statistically analyzed to measure the variables in an objective and systematic way.
(4) DiVoMiner® platform was used to do data processing and content analysis for this study.
(5) This paper utilized DiVoMiner® for online content analysis, developed by uMax Data Technology Limited.