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Stance Detection in Facebook Posts of a German Right-wing Party

机译:德国右翼政党的Facebook帖子中的姿态检测

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We argue that in order to detect stance, not only the explicit attitudes of the stance holder towards the targets are crucial. It is the whole narrative the writer drafts that counts, including the way he hyposta-sizes the discourse referents: as benefactors or villains, as victims or beneficiaries. We exemplify the ability of our system to identify targets and detect the writer's stance towards them on the basis of about 100 000 Facebook posts of a German right-wing party. A reader and writer model on top of our verb-based attitude extraction directly reveal stance conflicts.
机译:我们认为,为了发现立场,不仅立场持有人对目标的明确态度至关重要。作家起草的整个叙述是很重要的,包括他对话语对象进行大小调整的方式:作为恩人或小人,作为受害者或受益人。我们以德国右翼政党的约10万个Facebook帖子为基础,举例说明了系统识别目标并检测作者对目标的立场的能力。基于动词的态度提取之上的读者和作家模型直接揭示了立场冲突。

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