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Ethical filtering has been a painful and controversial issue seen by different angles worldwide. Stalwarts for freedom find newer methods to circumvent banned URLs while generative power of the Internet outpaces velocity of censorship. Hence, keeping online content safe from anti-religious and sexually provocative content is a growing issue in conservative countries in Asia and The Middle East. Solutions for online ethical filters are linearly upper bound given computation and big data growth scales. In this scenario, Semantic Vectors are applied as automatic ethical filters to calculate accuracy and efficiency metrics. The results show a normative tag cloud generated with superior performance to industry solutions.

Automatic Ethical Filtering using Semantic Vectors Creating Normative Tag Cloud from Big Data