Towards Quantifying the Distance between Opinions
Table 3: ARI and Silhouette coefficient scores.
['Methods', 'Seanad Abolition ARI', 'Seanad Abolition  [ITALIC] Sil', 'Video Games ARI', 'Video Games  [ITALIC] Sil', 'Pornography ARI', 'Pornography  [ITALIC] Sil']
among opinions: We see that OD significantly outperforms the baseline methods and the OD-parse variant [CONTINUE] OD achieves high ARI and Sil scores, [CONTINUE] From the above table, we observe that the text-similarity based baselines, such as TF-IDF, WMD and Doc2vec achieving ARI and Silhouette coefficient scores of close to zero on the "Video Games" and "Pornography" datasets (barely providing a performance improvement over random clustering, i.e., a zero ARI score). [CONTINUE] A notable exception is the "Seanad Abolition" dataset, where TF-IDF performs relatively better than WMD, Sent2vec and Doc2vec.