In particular researchers whether students or professionals are tasked to search tons of papers in order to find related detail that is important to their research. I remember one class that I have taken at University of Queensland back in 2010 and had to write an article on Lightning from Physics point of view.

From the first instance, the topic seem obvious and familiar to understand, specially we all learned in school that when two nearby clouds accumulate opposite electrical charge, the vacuum in between creates the lighting to balance this imbalance. Unfortunately it turned out to be the mechanism of lightning and thunderstorms is more complicated than this explanation.

When reading several papers on this topic I realized that there are multiple of theories that I have to study very well in order make a logical structure for my research, when reading didn’t stop, I have discovered more and more information that is probably more important to mentioned. The challenge also, is to workout which of these theories still holds and which proven to be invalid.

Now if I was able to travel back in the past, I would have approached this problem in a different way. With NLP and Text Analytics tools, I could utilize topic analysis and thematic entities to discover all related articles and only focus my reading on the papers that are relevant the most. With the help of text analytics it will be possible to target the theory titles and build the analysis between each of these theories.

Tools such as Word Cloud, Entity Recognition and basic Text Visualization can drive the navigation thru tons of research articles to select the relevant information that is required for this exercise.

To do a similar experiment, I picked 10 articles from BBC archived news back from 2005 on technology, when using the free text visualization tool on VizRefra, I have found few interesting insights. One article mentions about the latest discovery breakthrough in laser computing or quantum computing using the light beam instead of the electrons in the conventional silicon chip. We know from current technology we use in year 2021, the whole industry still relies on silicon chips. From the view below, the orange color that is strongest entity after the yellow circle, shows the leading photonics scientist Mario Paniccia working at Intel Corporation as shown in the big circle nearby.

VizRefra Visualize Text

Another interesting article is again about the development of CPU processors or (Chip in yellow circle) in its relation to the playing games consoles and movies. From a quick overlook at the VizRefra map, one can see the topic discusses the gap between playing consoles, in this instance PlayStation and watching movies. As circled in red, the challenge is addressed by leading companies, IBM, Toshiba and Sony, Once can conclude that main issues for this gap in providing graphics and special effect as in the middle circle.


VizRefra Visualize Text


Finally the article I put in VizRefra map, that it is related all computer display and screens. Knowing that VizRefra uses yellow as the strongest entity identified, shows as Screens, Another topic seen in the right of the map is Print related. There is also UK Film Council, Arts Alliance Cinema, Projectors, etc. The researcher can conclude that this article discussed the proposed technology development of screens serving the cinema industry and the main players are Arts Alliance Cinema in the UK.


VizRefra Visualize Text