Sentiment Network Analysis of Taleban and RFE/RL Open-Source Content about Afghanistan

Analysis of sentiment expressed in political systems\´ communication over long periods of time has been difficult. This research illustrates a method based on network analysis, the Sentiment Network Analyzer (SNAZ). It identifies weighted shortest paths between seed words and 3,500 target sentiment words as these occur in semantic networks extracted from open-source documents sliced into time intervals. Computing the normalized intensity ratios of positive and negative sentiment for each time slice enables application of the "Losada Line." For a system to be flourishing there must be at least 2.9 times more positive than negative communication. Below that ratio the system is languishing. Excessive positivity above a ratio of 11.6 marks the disintegration of a system into chaotic oscillation. We collected and analyzed five years of documents propaganda mentioning the Tale ban from Afghani and Pakistani sources transcribed by BBC International Monitoring. Likewise, we extract and analyze stories communicated by Radio Free Europe/Radio Liberty (RFE/RL) connected with Afghanistan over the same five-year period. Semantic network and sentiment network analysis is coupled with the computation of positivity ratios in each time slice during this period. Tale ban content is generally evident of flourishing, except for a period of oscillation between flourishing and excessive positivity beginning in the third quarter of 2010. RFE/RL is consistently languishing, reaching the 2.9 flourishing level in only one period. We discuss possible reasons. We also consider some implications for perception management and counter terrorism strategy.