Text mining and bibliometrics (6 articles)

Global and Latin American scientific production related to pneumococcal vaccines

Castro, R. M., Sánchez, M. V. G., Rivero, Y. M., Ramos, R. C., & Díaz, I. Á. (2018). Scientometrics, 1-11.

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

Alvarez-Betancourt, Y., & Garcia-Silvente, M. (2014). Scientometrics, 101(3), 2003-2033.

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

Licorish, S., & MacDonell, S. (2014). Australian Conference on Information Systems (ACIS).

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

Claster, W., Pardo, P., Cooper, M., & Tajeddini, K. (2013). Middle East Journal of Management, 1(1), 81-99.

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

Claster, W., Shanmuganathan, S., & Ghotbi, N. (2008). JCP, 3(1), 1-6.

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

Sotolongo-Aguilar, G., Guzmán-Sánchez, M. V., Saavedra-Fernández, O., & Carrillo-Calvet, H. A. (2001). Proceedings of the 8th international society for scientometrics and informetrics, 665-673.

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.