Name
Abstract | ||
|---|---|---|
A growing body of work has highlighted the challenges of identifying the stance a speaker holds towards a particular topic, a task that involves identifying a holistic subjective disposition. We examine stance classification on a corpus of 4873 posts across 14 topics on ConvinceMe.net, ranging from the playful to the ideological. We show that ideological debates feature a greater share of rebuttal posts, and that rebuttal posts are significantly harder to classify for stance, for both humans and trained classifiers. We also demonstrate that the number of subjective expressions varies across debates, a fact correlated with the performance of systems sensitive to sentiment-bearing terms. We present results for identifing rebuttals with 63% accuracy, and for identifying stance on a per topic basis that range from 54% to 69%, as compared to unigram baselines that vary between 49% and 60%. Our results suggest that methods that take into account the dialogic context of such posts might be fruitful. |
Year | Venue | Keywords |
|---|---|---|
2011 | WASSA@ACL | greater share,online debate,holistic subjective disposition,ideological debate,subjective expression,rebuttal post,dogs drool,cats rule,identifing rebuttal,dialogic context,particular topic,stance classification,classifying stance,topic basis |
Field | DocType | Citations |
Social psychology,Dialogic,Expression (mathematics),Computer science,Ideology,Rebuttal,Disposition | Conference | 65 |
PageRank | References | Authors |
3.19 | 14 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Pranav Anand | 1 | 260 | 19.70 |
| Marilyn A Walker | 2 | 3893 | 418.91 |
| Rob Abbott | 3 | 206 | 9.62 |
| Jean E. Fox Tree | 4 | 198 | 14.77 |
| Robeson Bowmani | 5 | 74 | 4.41 |
| Michael Minor | 6 | 65 | 3.19 |