Image–text sentiment analysis via deep multimodal attentive fusion

Volume: 167, Pages: 26 - 37
Published: Jan 16, 2019
Abstract
Sentiment analysis of social media data is crucial to understand people’s position, attitude, and opinion toward a certain event, which has many applications such as election prediction and product evaluation. Though great effort has been devoted to the single modality (image or text), less effort is paid to the joint analysis of multimodal data in social media. Most of the existing methods for multimodal sentiment analysis simply combine...
Paper Details
Title
Image–text sentiment analysis via deep multimodal attentive fusion
Published Date
Jan 16, 2019
Volume
167
Pages
26 - 37
Citation AnalysisPro
  • Scinapse’s Top 10 Citation Journals & Affiliations graph reveals the quality and authenticity of citations received by a paper.
  • Discover whether citations have been inflated due to self-citations, or if citations include institutional bias.