GIP IG Barometer: a text-mining approach to Internet Governance Monitoring

The IG Barometer methodology results in the computation of four scores for each IG Issue: Relevance, Specificity, Diversity, and Positivity, all expressed as percentile ranks - similar to standardized test results reporting. Each of these scores reflects the relative position of a particular IG Issue in respect to all other issues encompassed by the analysis. The computation of the scores is based upon the previously statistically modeled IGF Session Transcripts Text Corpus: a collection of hundreds manually tagged session transcripts from the Internet Governance Forum 2006-14, rich with meta-data, encompassing the codification of expert IG knowledge as represented in the various IGF sessions, workshops, and fora . All IG Barometer computations are supported by the IG Terminological Model, a hand-picked and manually tagged selection of approximately 5,000 most relevant IG keywords, terms and phrases. Hereby we describe conceptually the elements upon which the computation of the IG Barometer scores is founded; the interpretation of the four IG Barometer scores is provided immediately afterwards.