English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Authors of posts in social media communicate their emotions and what causesthem with text and images. While there is work on emotion and stimulusdetection for each modality separately, it is yet unknown if the modalitiescontain complementary emotion information in social media. We aim at fillingthis research gap and contribute a novel, annotated corpus of Englishmultimodal Reddit posts. On this resource, we develop models to automaticallydetect the relation between image and text, an emotion stimulus category andthe emotion class. We evaluate if these tasks require both modalities and findfor the image-text relations, that text alone is sufficient for most categories(complementary, illustrative, opposing): the information in the text allows topredict if an image is required for emotion understanding. The emotions ofanger and sadness are best predicted with a multimodal model, while text aloneis sufficient for disgust, joy, and surprise. Stimuli depicted by objects,animals, food, or a person are best predicted by image-only models, whilemultimodal models are most effective on art, events, memes, places, orscreenshots.

On the Complementarity of Images and Text for the Expression of Emotions in Social Media