Thanks to the popularity of social media, data generated by online communities provides an abundant source of diverse language information. This abundance of data allows NLP practitioners and computational linguists to analyze sociolinguistic phenomena occurring in digital communication. In this paper, we analyze the Twitter discourse around the Mexican Spanish-speaking LGBT+ community. For this, we evaluate how the polarity of some nouns related to the LGBT+ community has evolved in conversational settings using a corpus of tweets that cover a time span of ten years. We hypothesize that social media’s fast-moving, turbulent linguistic environment encourages language evolution faster than ever before. Our results indicate that most of the inspected terms have undergone some shift in denotation or connotation. No other generalizations can be observed in the data, given the difficulty that current NLP methods have to account for polysemy, and the wide differences between the various subgroups that make up the LGBT+ community. A fine-grained analysis of a series of LGBT+-related lexical terms is also included in this work.