# Generating Indicators of Disruptive Innovation Using Big Data
## 3 Method/Approach
### Analysis and Results  
For each technology term in the reference list (Gartner, Economist, etc. ), a query was performed to obtain a list of papers in which the term appears in the abstract. The input to the process was a file of the form shown in Table 1.  
Queries were derived which analyzed both the formatted fields in the data (dates, locations, etc. ), and scanned the free text in the title and abstract in the metadata for all papers. Several techniques were used to avoid falsely detecting short words in other words (e.g., 'VR' in manoeuvWe) by carefully conditioning the query and post processing. The following measures were generated:  
* Profile over time of a technology term (number of occurrences each year). * Profile over time of the term within different subject areas (technology, medicine, law, etc.). * Profile over time of the publication country of papers containing the term. * Co-occurrence with other terms (how often do other technology terms appear in papers relating to one technology). Each measure offers a different insight into technology progression--addressing the overall growth of a technology, how it starts to pervade different subject areas (applications), its geographic spread, and its alignment with other technologies. The latter supports identification of co-dependence, or shared relevance to a problem. The results of the analysis are presented in textual and graphical form in a linked HTML structure (results website), allowing for the revision of the analysis of a given collection of technologies. In addition to the measures pages per technology, there is an overview page, providing an index for the results. A typical overview page output for a processing run, with a list of input technologies, is shown in Figure 7.  
In addition to the human readable outputs (HTML) a series of data outputs were generated, comma separated variable (CSV), JavaScript object notation (JSON) and resource description framework (RDF) files per technology. These allow other tools to be used to assess the data. To validate the results or review specific technology topic results, both the titles and the paper abstracts were presented in HTML for a given technology topic (Figure 8). The abstract table is helpful in identifying erroneous detections, particularly with the implementation of highlighting showing where the detections occurred. A typical issue was, for example, the term 'OLED' (organic light emitting diode) is a common string in many words (e.g., pooled). This was easily avoided once identified (by conditioning the queries) to add spaces around small terms \"old\" and \"(old)\" and also some further processing. This is not perfect as it then misses some potential results but is more stable. For a given set of reference technology topics (over 300 in total), all the analyses described in the previous section were calculated automatically and hyperlinked to the relevant technology topic presented in an HTML table as shown in Figure 7. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Technology Term** &
\begin{tabular}{c} **First** \\ **Occurrence** \\ \end{tabular} & **Source** & **Synonym(1)** & **Synonym(n)** \\ \hline Cloud Computing & 2008 & Source1 & & \\ Virtual Reality & 2011 & Source1 & VR & \\ Service Oriented Architecture & 2016 & Source1 & SOA & \\ Unmanned Aerial Vehicle & 2016 & Source1 & UAV & Drone \\ Organic Light Emitting Diode & 2012 & Source1 & OLED & \\
3D Printing & 2011 & Source1 & 3d Printer & \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Technology Topic Input. Various steps were taken to validate the harvesting and analysis. * An extensive logging of errors was implemented and retained, allowing all failures in processing to be reviewed. * To test if the set of paper abstracts was representative, the papers present for each of the authors of this paper were searched for (as we are each aware of the papers we have published and so can check their presence, relevance, and publication dates). The results were as expected.