Natural Language Processing Of Online Propaganda As A Means Of Passively Monitoring An Adversarial Ideology
Technical Report,05 Jul 2016,31 Mar 2017
Naval Postgraduate School Monterey United States
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Online propaganda embodies a potent new form of warfare one that extends the strategic reach of our adversaries and overwhelms analysts. Foreign organizations have effectively leveraged an online presence to influence elections and distance-recruit. The Islamic State has also shown proficiency in outsourcing violence, proving that propaganda can enable an organization to wage physical war at very little cost and without the resources traditionally required. To augment new counter foreign propaganda initiatives, this thesis presents a pipeline for defining, detecting and monitoring ideology in text. A corpus of 3,049 modern online simulate how an ideology can be detected and how its composition could be passively monitored across time. Implementation of such a system could conserve manpower in the intelligence community and add a new dimension to analysis. Although this pipeline makes presumptions about the quality and integrity of input, it texts was assembled and two classifiers were created one for detecting authorship and another for detecting ideology. The classifiers demonstrated 92.70recall and 95.84 precision in detecting authorship, and detected ideological content with 76.53 recall and 95.61 precision. Both classifiers were combined to is a novel contribution to the fields of Natural Language Processing and Information Warfare.
- Sociology and Law