This! Identifying new sentiment slang through orthographic pleonasm online: Yasss slay gorg queen ilysm
AbstractIdentifying 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 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, non-dictionary words are extracted from a large social web corpus, spelling standardisation is applied, and then words are ranked in decreasing order of spelling variation frequency. Words with the most spelling variations are then KWIC-analysed for semantic context. Applied to a collection of comments on YouTube influencers, this method found neologisms like 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 one of voice, it is also used for initialisms in a way that is difficult to vocalise. The method is therefore a practical method to identify new sentiment slang, including both normal words and initialisms.
CitationThelwall, M. (2021) This! Identifying new sentiment slang through orthographic pleonasm online: Yasss slay gorg queen ilysm. IEEE Intelligent Systems, 36 (4), pp. 114-120.
JournalIEEE Intelligent Systems
DescriptionThis is an accepted manuscript of an article published by IEEE in IEEE Intelligent Systems on 13 Sept 2021, available online: https://ieeexplore.ieee.org/document/9536263 The accepted version of the publication may differ from the final published version.
Except where otherwise noted, this item's license is described as https://creativecommons.org/licenses/by-nc-nd/4.0/