Sex, drugs, and violence
Table 3: Lowest absolute error between inferred and average human ratings, for each category, including associated ntopics.
['[EMPTY]', '[ITALIC] ntopics', '1', '2', '3', '4', 'W.Avg.']
An eventual aim of this work is to automatically provide meaningful ratings for each of sexual, violent, and drug-abuse content, to be used in practice. shows the absolute distance between inferred and average human ratings, for each category. The weighted average multiplies the contribution of each rating error by the inverse of that rating’s prevalence in the data; e.g., ‘appropriate’ texts were weighted lower, since there were more of them in the data. The table also shows a ‘total’ row which selects the best PLDA model by averaging the errors for each rating and the average error across rating levels (i.e., each column in the table) for the sex, drugs, and violence regressors trained on that PLDA model. The classification rates are clearly lowest for the extremes of rating levels 1 and 4. Overall, the regression gives absolute errors <1 for each of the three categories of content; while promising, future work with more annotated data and non-linear models is recommended.