Sources with weights Arstechnica: 1/8, Euractiv: 1/8, Fastcompany: 1/8, The Register: 1/8, Techcrunch: 1/8, The Guardian: 1/8, Venturebeat: 1/8, The Verge: 1/8 Methodology Frequency of appearances for all unigrams and bigrams in the texts Frequency: number of appearances of every term divided by the number of published articles (for every month and source) This measure reveals how many times an expression has been mentioned on average per article Several media sources: a representative index is calculated with weighted average (weights as above) Average monthly change in the analised term's frequency is calculated by OLS regressions The dependent variable of the estimation is the frequency index, while the number of months since the beginning of the analysed period (January 2016) is the independent variable The regression coefficient (referred to as coef) shows by how much on average the analysed expression’s frequency changed with every observed month (marginal change of the frequency), revealing which keywords had the biggest monthly growth Columns freq_months (e.g. freq_2019-04): the average frequency of the term coef: the regression coefficient coef_norm: the regression coefficient divided by the mean frequency of the keyword coef_norm_max: the regression coefficient divided by the maximum frequency of the keyword