How text network analysis can be used for website SEO. We use an example of a travel guide website to find out what people are searching for in relation to travel, what they actually find, and how well the travel guide website studied responds to the needs of the users. We also explore the idea of content polysingularity ensuring that information offered within the website does not only fulfil the readers’ needs, but also helps them learn more and discover new perspectives about the topics they’re interested in.
Any group of people working together has a field of interests, which can be represented as a network of interrelated concepts. Mark might be interested in studying trends and fashion, while Joanne might be into fashion and arts. Identifying those interests and their relation to one another can be very useful for improving the collaboration, indicating the vantage points as well as the structural gaps within the group.
Text network analysis can be used for such quick group profiling. The members of the group can write a short text (or be interviewed) outlining their interests. Alternatively, publicly available texts can be used to gather the data. Next, graph visualization of this aggregated text can help identify the most prominent topics and their relations within that text corpus.
We could have also called it The Study of Political Manipulation Techniques. This article reveals how the US presidents masterfully used the right rhetorics to address the general sentiment of their voters and set the forthcoming political agenda. Comparative analysis of their inauguration speeches using dynamic text network analysis clearly demonstrates how the importance of various concepts shifts with the new political challenges that the newly elected presidents face.
We now offer high quality large-format prints of network visualizations created using a combination of our own software (Textexture), open-source Gephi platform, iterative algorithms, fuzzy logic, trial and error, as well as intuition, magic, science, and experiment.
It is possible to order prints of the already existing text network visualizations or to create custom-made prints using your own source data (any text, social network, or any other connectivity that can be represented as a network).
When we read a text, we normally follow it in quite a linear fashion: from left to right, from top to bottom. Even when we skim articles quickly online, the trajectory is still the same. However, this is not the most efficient method of reading: in the age of hypertext we tend to create our own narratives using the bits and pieces from different sources.
As a response to this challenge we at Nodus Labs developed a new free online software tool Textexture.Com, which visualizes any text as a network and enables the user to use this interactive visualization to read through the text in a non-linear fashion.