Identifying neologisms is important for natural language processing of social web text when informal language is standard and youth slang is common. For example, failing to identify neologisms can reduce the accuracy of the lexical sentiment analysis if opinions are frequently expressed in words that are too new to be in the sentiment dictionary. This article proposes a method based on orthographic pleonasm to identify emotion-related neologisms in the social web: finding words with the most different letter repetition spelling variations. For this method, nondictionary words are extracted from a large social web corpus, spelling standardization is applied, and then words are ranked in a decreasing order of spelling variation frequency. Words with the most spelling variations are then keyword-in-context-analyzed for semantic context. Applied to a collection of comments on YouTube influencers, this method founds neologisms such as slay and early as positive terms, mixed with traditional sentiment words, exclamations, and nouns. Although orthographic pleonasm was originally used to express the speaker’s rhythm and tone of voice, it is also used for initialisms in a way that is difficult to vocalize. The method is, therefore, a practical way to identify new sentiment slang, including both normal words and initialisms.

中文翻译：

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这个！通过 Orthographic Pleonasm Online 识别新的情感俚语：Yass Slay Gorg Queen Ilysm

当非正式语言是标准的并且青年俚语很常见时，识别新词对于社交网络文本的自然语言处理很重要。例如，如果意见经常用太新而无法出现在情感词典中的词表达，则未能识别新词会降低词汇情感分析的准确性。本文提出了一种基于正字法pleonasm的方法来识别社交网络中与情感相关的新词：查找具有最不同字母重复拼写变化的单词。对于这种方法，从大型社交网络语料库中提取非字典词，应用拼写标准化，然后按照拼写变化频率的降序排列单词。然后对拼写变化最大的单词进行上下文关键字分析以获取语义上下文。应用于 YouTube 影响者的评论集合，该方法创建了新词，例如 slay 和 early as positive terms，混合了传统的情感词、感叹词和名词。尽管正字法pleonasm最初用于表达说话者的节奏和语调，但它也以难以发声的方式用于声母。因此，该方法是识别新的情感俚语的实用方法，包括普通词和首字母缩写。