Publication | Closed Access
The Use of Metrics for Measuring Informality Levels in Web 2.0 Texts
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Citations
5
References
2011
Year
Unknown Venue
Text InformalityCommunicationSentiment AnalysisCorpus LinguisticsJournalismText MiningApplied LinguisticsNatural Language ProcessingComputational Social ScienceMeasuring Informality LevelsSocial MediaInformality LevelComputational LinguisticsOnline CommunityInformality LevelsLanguage EngineeringDocument ClassificationLanguage StudiesContent AnalysisWeb-based CollaborationSocial Medium MiningWeb LiteracyWeb 2.0SociolinguisticsNlp TaskKnowledge DiscoveryWeb TrendSocial WebSocial ComputingSocial Medium DataArtsLinguistics
The study of text informality can provide us with valuable information for different NLP tasks. In the particular case of social media texts, their special characteristics like the presence of emoticons, slang or colloquial words can be used for obtaining additional information about their informality level. This pa- per demonstrates that the discovery of informality levels in Web 2.0 texts can be improved by incorporating formality and informality scores. The classification method based on our proposal reaches a 78% F1 using unsupervised machine learning techniques.
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