Using millions of emoji occurrences to learn any-domain representations for detecting sentiment, emotion and sarcasm

NLP tasks are often limited by scarcity of manually annotated data. In social media sentiment analysis and related tasks, researchers have therefore used binarized emoticons and specific hashtags as forms of distant supervision. Our paper shows that by extending the distant supervision to a more diverse set of noisy labels, the models can learn richer representations. Through emoji prediction on a dataset of 1246 million tweets containing one of 64 common emojis we obtain state-of-the-art performance on 8 benchmark datasets within sentiment, emotion and sarcasm detection using a single pretrained model. Our analyses confirm that the diversity of our emotional labels yield a performance improvement over previous distant supervision approaches.Comment: Accepted at EMNLP 2017. Please include EMNLP in any citations. Minor changes from the EMNLP camera-ready version. 9 pages + references and supplementary materia

Defect chemistry and oxygen transport of (La0.6Sr0.4 − xMx)0.99Co0.2Fe0.8O3 − δ, M = Ca (x = 0.05, 0.1), Ba (x = 0.1, 0.2), Sr: Part I: Defect chemistry

This paper is the first part of a two part series, where the effects of varying the A-site dopant on the defect chemistry, the diffusion coefficient and the surface catalytic properties of the materials (La0.6Sr0.4 − xMx)0.99Co0.2Fe0.8O3 − δ, M = Sr, Ca (x = 0.05, 0.1), Ba (x = 0.1, 0.2) (LSMFC) have been investigated. In part I, the findings on the defect chemistry are reported, while the transport properties are reported in part II. Substitution of Sr2+ ions with Ca2+ ions (smaller ionic radius) and Ba2+ ions (larger ionic radius) strains the crystal structure differently for each composition while keeping the average valence of the cations constant. The Ba2+ containing materials show the largest oxygen loss at elevated temperatures, while the purely Sr2+ doped material showed the smallest oxygen loss. This was reflected in the partial oxidation entropy of the materials. The measured oxygen loss was modelled with point defect chemistry models. Measurements at very low pO2 showed several phase transitions