Twitter Sentiment Analysis: The Good the Bad and the OMG!
Efthymios Kouloumpis, Theresa Wilson, Johanna D. Moore
2021Proceedings of the International AAAI Conference on Web and Social Media1,244 citationsDOIOpen Access PDF
Abstract
In this paper, we investigate the utility of linguistic features for detecting the sentiment of Twitter messages. We evaluate the usefulness of existing lexical resources as well as features that capture information about the informal and creative language used in microblogging. We take a supervied approach to the problem, but leverage existing hashtags in the Twitter data for building training data.
Topics & Concepts
MicrobloggingLeverage (statistics)Computer scienceSocial mediaSentiment analysisData scienceArtificial intelligenceNatural language processingInformation retrievalWorld Wide WebSentiment Analysis and Opinion MiningSpam and Phishing DetectionAdvanced Text Analysis Techniques