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In this paper, we introduce the T-MexNeg corpus of Tweets written in Mexican Spanish. It consists of 13,704 Tweets, of which 4895 contain negation structures. We performed an analysis of negation statements embedded in the language employed on social media. This research paper aims to present the annotation guidelines along with a novel resource targeted at the negation detection task. The corpus was manually annotated with labels of negation cue, scope, and, event. We report the analysis ofdoi:10.3390/app11093880 doaj:aabcbb3275f84774a29fd5316c428436 fatcat:dzcyo2mp5fdajgnm7yz5zzbora