Instituto Politécnico Nacional

About: Instituto Politécnico Nacional is a education organization based out in Mexico City, Mexico. It is known for research contribution in the topics: Population & Context (language use). The organization has 43351 authors who have published 63315 publications receiving 938532 citations. The organization is also known as: Instituto Politécnico Nacional & Instituto Politecnico Nacional.

Recent trends in deep learning based personality detection

Abstract: Recently, the automatic prediction of personality traits has received a lot of attention. Specifically, personality trait prediction from multimodal data has emerged as a hot topic within the field of affective computing. In this paper, we review significant machine learning models which have been employed for personality detection, with an emphasis on deep learning-based methods. This review paper provides an overview of the most popular approaches to automated personality detection, various computational datasets, its industrial applications, and state-of-the-art machine learning models for personality detection with specific focus on multimodal approaches. Personality detection is a very broad and diverse topic: this survey only focuses on computational approaches and leaves out psychological studies on personality detection.

Multimodal Sentiment Analysis: Addressing Key Issues and Setting Up the Baselines

Abstract: We compile baselines, along with dataset split, for multimodal sentiment analysis. In this paper, we explore three different deep-learning-based architectures for multimodal sentiment classification, each improving upon the previous. Further, we evaluate these architectures with multiple datasets with fixed train/test partition. We also discuss some major issues, frequently ignored in multimodal sentiment analysis research, e.g., the role of speaker-exclusive models, the importance of different modalities, and generalizability. This framework illustrates the different facets of analysis to be considered while performing multimodal sentiment analysis and, hence, serves as a new benchmark for future research in this emerging field.