The Language of Dialogue Is Complex
The Language of Dialogue Is Complex
复制标题
对话的语言很复杂
DOI：
10.1609/icwsm.v13i01.3241
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发表时间：
2019
期刊：
影响因子：
--
通讯作者：
D. Quercia
中科院分区：
文献类型：
--
作者：
Alexander Robertson;L. Aiello;D. Quercia
综合复杂性（IC）是一种心理测量学，衡量一个人识别多种观点并将它们联系起来的能力，从而确定解决冲突的路径。 IC 与各种政治、社会和个人结果相关，但对其进行评估是一个耗时的过程，需要熟练的专业人员对文本进行手动评分，这一事实说明了社交媒体上对 IC 的大规模探索有限。我们将自然语言处理和机器学习相结合来训练 IC 分类模型，该模型在未见过的数据上实现了最先进的性能，并且比以前的自动化方法更紧密地遵循 IC 编码过程的既定结构。当应用于在线论坛上关于抑郁症和知识交流的 40 万多条评论内容时，我们的模型能够复制之前工作的关键发现，从而提供了使用 IC 工具进行大规模社交媒体分析的第一个示例。
Integrative Complexity (IC) is a psychometric that measures the ability of a person to recognize multiple perspectives and connect them, thus identifying paths for conflict resolution. IC has been linked to a wide variety of political, social and personal outcomes but evaluating it is a time-consuming process requiring skilled professionals to manually score texts, a fact which accounts for the limited exploration of IC at scale on social media. We combine natural language processing and machine learning to train an IC classification model that achieves state-of-the-art performance on unseen data and more closely adheres to the established structure of the IC coding process than previous automated approaches. When applied to the content of 400k+ comments from online fora about depression and knowledge exchange, our model was capable of replicating key findings of prior work, thus providing the first example of using IC tools for large-scale social media analytics.
影响因子：
22.7
作者：
MILLER, GA
通讯作者：
MILLER, GA