Blockchain technology forecasting by patent analytics and text mining
The aim of this paper is to analyze the trends in patents for blockchain technology from 2011 to 2020. Viscovery SOMine is used to cluster keywords according to their correlations in the text corpus in order to identify different branches of blockchain technology.
Quality of service evaluation of a university library using text mining and Kohonen self-organizing maps
Survey data on service satisfaction of customers of a university library are analyzed. Viscovery SOMine is used to identify and exclude outliers and to form four groups of customers with high vs. low expectations and high vs. low service experience. A text analysis model is evaluated on top of the defined groups.
Global and Latin American scientific production related to pneumococcal vaccines
This paper studies publication activities related to pneumococcal vaccines with special emphasis on Latin America. Viscovery SOMine was used to cluster articles with respect to covered topics and study their interrelationships.
An overview of iris recognition: a bibliometric analysis of the period 2000–2012
A bibliometric analysis of publications in the field of iris recognition is conducted. Viscovery SOMine is used to visualize the research focus of different authors and cluster them according to their research.
Relating IS developers’ attitudes to engagement
The attitudes of IS developers in comments on the Jazz development platform are analyzed in connection with their engagement to the development work. Viscovery SOMine is used to explore the text data with respect to different personality measures (extroversion, work focus, insightfulness, etc.) and outcome variables (number of comments, comment length, resolved tasks, etc.).
Tourism, travel and tweets: algorithmic text analysis methodologies in tourism
This paper analyzes tweets referring to the tourist regions Bangkok and Phuket in Thailand, Cancun in Mexico and Colombo in Sri Lanka. Viscovery SOMine is used to carry out cluster analyses to give a multidimensional view on sentiments towards these regions.
Text mining of medical records for radiodiagnostic decision-making
Radiology department records of children who had undergone a CT scan procedure at Nagasaki University Hospital in the year 2004 are analyzed using Viscovery SOMine. Keywords are identified with a significance value within the narratives of the medical records that could predict and thereby lower the number of unnecessary CT requests by clinicians. This method can be used to reduce overuse of medical radiation, which poses significant health risks and staggering costs, especially with regard to children.
Mining informetric data with self-organizing maps
This article describes three bibliometric models: 1) scientific performance of Latin America in the field of agriculture, 2) the visibility of Latin America in scientific journals, 3) research trends in biomedicine associated with non-linear dynamics. Viscovery SOMine is used for clustering with respect to bibliometric indices, such as number of references in different journals, number of citations and number of keywords.