Nexalogy Environics has developed innovative methodologies to perform its advanced intelligence services. An important part of the process involves the use of our proprietary semantic analysis techniques – but just as important is that using those techniques allows Nexalogy Environics to do superior human analysis. Our methodology is fundamentally a question of using the best tools to do the best job possible.
There are four distinct phases to Nexalogy Environics’ analysis process.
- Dataset creation
The first step in the analysis process is to construct a dataset that includes all of the blog posts related to the subject being analyzed. There are several possible strategies that may be used to construct this dataset for each project – Nexalogy Environics takes care to ensure that the particular strategy used will lead to the best possible analysis. Characteristics of a good dataset are extensiveness, balance, and that it is not biased towards a particular result based on the keywords used. An integral part of the dataset creation process is to ensure that the resulting dataset will be as free from spam and other malicious “noise” as possible. - Quantitative analysis
The second step in the analysis process is to perform an extensive quantitative analysis on the whole dataset. This analysis relies on software that uses advanced datamining and semantic analysis techniques to perform artificial reading on the dataset. The typical outputs of the quantitative analysis are: Source Maps (Author or Publisher); Lexical graphs; Word association tables, Timelines, and Key Actor/Opinion Leader lists. - Qualitative analysis
Based on the output of quantitative analysis, Nexalogy Environics engages a team of trained content analysts to go into the original dataset and read the blog posts that have been identified as the most important or relevant based on their semantic characteristics (in other words, based on the posts’ content). The content analysts perform a number of qualitative analyses, including (depending on the mandate) content scoring, content summaries, author identification, behavioural or attitudinal segmentation, etc. The analysts pay special attention to unexpected patterns that were found in the data during the quantitative analysis. - Reporting and Strategic recommendations
The final step of the analysis process is to take all of the outputs of the preceding steps and synthesize them into a comprehensive report consisting of observations, interpretations and detailed strategic recommendations about how the client might take advantage of an opportunity or mitigate the effects of a challenge.
