In this paper, we present our participation to CLEF MC2 2018 edition for the
task 2 Mining opinion argumentation. It consists in detecting the most
argumentative and diverse Tweets about some festivals in English and French
from a massive multilingual collection. We measure argumentativity of a Tweet
computing the amount of argumentation compounds it contains. We consider
argumentation compounds as a combination between opinion expression and its
support with facts and a particular structuration. Regarding diversity, we
consider the amount of festival aspects covered by Tweets. An initial step
filters the original dataset to fit the language and topic requirements of the
task. Then, we compute and integrate linguistic descriptors to detect claims
and their respective justifications in Tweets. The final step extracts the most
diverse arguments by clustering Tweets according to their textual content and
selecting the most argumentative ones from each cluster. We conclude the paper
describing the different ways we combined the descriptors among the different
runs we submitted and discussing their results.

本篇文章描述我们参加 CLEF MC2 2018 探究的任务为挖掘与节日相关的意见论证 Tweets，通过计算 Tweets 中的论证成分、使用语言描述器来检测主张和它们的支持理由，最终通过聚类算法提取最具论点的多元化主张。