VISUAL AND TEXTUAL SENTIMENT ANALYSIS USING DEEP FUSION CONVOLUTIONAL NEURAL NETWORKS
Table 1: Results on VSO dataset.
['[BOLD] Methods Baseline', '[BOLD] Methods ST', '[BOLD] Prec. 0.701', '[BOLD] Rec. 0.680', '[BOLD] F1 0.690', '[BOLD] Acc. 0.695']
It can be observed that the proposed approach significantly outperforms baselines and PCNN method, indicating fusing two modalities information does improve sentiment prediction. This is mainly because multi-modalities information enrich the semantic space. Our deep fusion model also obtains better results than T-LSTM and You’s method. We believe it mainly because our model utilizes the global information of image.