"Framing" involves the positive or negative presentation of an argument or issue depending on the audience and goal of the speaker (Entman 1983). Differences in lexical framing, the focus of our work, can have large effects on peoples' opinions and beliefs. To make progress towards reframing arguments for positive effects, we create a dataset and method for this task. We use a lexical resource for "connotations" to create a parallel corpus and propose a method for argument reframing that combines controllable text generation (positive connotation) with a post-decoding entailment component (same denotation). Our results show that our method is effective compared to strong baselines along the dimensions of fluency, meaning, and trustworthiness/reduction of fear.
翻译:“Framing”是指根据发言者的听众和目标对一个论点或问题进行正面或负面的介绍(Entman 1983年)。我们工作的重点——词汇设置方面的差异可能对人民的意见和信仰产生很大影响。为了在重新确定积极效果的论据方面取得进展,我们为这项任务创建了一个数据集和方法。我们使用“批注”词汇资源来创建一个平行的主体,并提议一种将可控文本生成(积极含义)与后解码隐含成分(同注解)结合起来的论据重组方法。我们的结果表明,我们的方法是有效的,比起流利、意义和信任/减少恐惧的强基线。