Opinion Retrieval in Twitter
Zhunchen Luo, Miles Osborne, Ting Wang
2021Proceedings of the International AAAI Conference on Web and Social Media39 citationsDOIOpen Access PDF
Abstract
We consider the problem of finding opinionated tweets about a given topic. We automatically construct opinionated lexica from sets of tweets matching specific patterns indicative of opinionated messages. When incorporated into a learning-to-rank approach, results show that this automatically opinionated information yields retrieval performance comparable with a manual method. Finally, topic-related specific structured tweet sets can help improve query-dependent opinion retrieval.
Topics & Concepts
Computer scienceConstruct (python library)Information retrievalMatching (statistics)Sentiment analysisRank (graph theory)Learning to rankArtificial intelligenceNatural language processingRanking (information retrieval)MathematicsStatisticsCombinatoricsProgramming languageSentiment Analysis and Opinion MiningAdvanced Text Analysis TechniquesTopic Modeling