Active learning in annotating micro-blogs dealing with e-reputation
Table 4: Overview of annotations and corrections within each groups of annotators. C.S. stands for Computer Science.
['# Hollande - FH Domain', '# Hollande - FH Annotations', '# Hollande - FH Aspect corr.', '# Hollande - FH Polarity corr.', '# Hollande - FH Corr. Rate', '# Hollande - FH Corr. Rate']
It is interesting to note several points. We can observe a major difference between NS and FH, in the first case (NS), there are more opinion corrections (since it is a 3 class problem while FH holds two polarity levels having only poll and injunction as positive examples). Whereas in the second case FH holds much more mistakes on aspects mainly concentrated between assessment, political line and project but also between skills and communication. For NS aspects mistakes appear to be limited between ethic and person. Annotations on tweets concerning NS presents more stability between aspect and opinion with similar error rates.