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This dataset contains 175 cases. It is manually created to reveal the ability of models to solve different types of adversarial cases for same side stance predictions more systematically. The examples selected here are derived from the dataset used in the Same Side Stance Classification shared task. We have selected 25 distinct arguments from the "gay marriage" topic that are short and express their stance clearly. For each selected argument, we construct new arguments of four distinct types to obtain two pairs, one with the same stance, and one with an opposing stance: Negation: a simple negation of the argument. Paraphrase: alters important words from the argument to synonymous expressions with the same stance. Argument: uses an argument from the same topic and stance, but semantically completely different regarding the first one. Citation: repeats or summarizes the first argument and then expresses agreement or rejection (a case frequently occurring in the dataset). The types Paraphrase, Argument, and Citation are also formulated in a negated version to create additional test instances for the opposite stance.
{"references": ["Benno Stein, Yamen Ajjour, Roxanne El Baff, Khalid Al-Khatib, Philipp Cimiano, and Henning Wachsmuth. Same Side Stance Classification. In Yamen Ajjour et al, editors, Same Side Stance Classification Shared Task 2019, volume 2921, July 2021"]}
Stance Classification, Computation Argumentation, Same Side Stance Classification
Stance Classification, Computation Argumentation, Same Side Stance Classification
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
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| downloads | 1 |

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