Multimodal Sentiment Analysis of Social Media
Diana Maynard, David Dupplaw, Jonathon S. Hare · ePrints Soton (University of Southampton) · 2013
Abstract This paper describes the approach we take to the analysis of social media, combining opinion mining from text and multimedia (images, videos, etc), and centred on entity and event recognition. We examine a particular use case, which is to help archivists select material for inclusion in an archive of social media for preserving community memories, moving towards structured preservation around semantic categories. The textual approach we take is rule-based and builds on a number of sub-components, taking into account issues inherent in social mediasuchasnoisyungrammaticaltext,useofswearwords,sarcasmetc. The analysis of multimedia content complements this work in order to helpresolveambiguityandtoprovidefurthercontextualinformation.We provide two main innovations in this work: first, the novel combination of text and multimedia opinion mining tools; and second, the adaptation of NLP tools for opinion mining specific to the problems of social media. 1