(333h) The Distribution of Online News Evaluated By Chemical Engineering and Process Control Tools
AIChE Annual Meeting
2016
2016 AIChE Annual Meeting
Computing and Systems Technology Division
Big Data Analytics in Chemical Engineering
Tuesday, November 15, 2016 - 2:15pm to 2:30pm
As data source we firstly focused on news triggered by scientific events (publication of new articles in scientific journals), as the flow of such news can be monitored precisely by a free-to-use online tool (Altmetrics). Data was aggregated from the online tool and a linear system identification method was applied to identify the main characteristics of the processes involved. The data is discussed in terms of time scale analysis, but also in terms of preferential attachment (i.e. aggregation) phenomena.
In a second step the derived characteristics of scientific news were compared with data on political news today and in the past (prior to the internet). In this comparison the metrics of time constants and gains were highly beneficial and resulted in a quantitative insight into describing the flow of information.
We believe that the discussed approach is not only of educational value, but that traditional chemical engineering tools (e.g. linear system response, aggregation and diffusion phenomena) are highly valuable in identifying and quantifying processes in big data.
(1) RN Grass, WJ Stark, AIChE J. 62, 1104 (2016).