Understanding the Emotional Intelligence Discourse on Social Media: Insights from the Analysis of Twitter

Characteristics, hotspots, and prospects of short video research: A review of papers published in China from 2012 to 2022

In recent years, due to the increase in their global popularity, short video applications have become an important topic of research. The number of users has now exceeded one billion in China; accordingly, Chinese researchers have conducted many studies on short videos. Their findings can serve as important references for both theoretical research on and the practical development of short videos worldwide. In this study, we used bibliometrics method and the CiteSpace application to analyze the content of 2163 representative research papers on short videos published in China from 2012 to 2022. The number of such papers is increasing annually in China; moreover, several core groups of authors and research institutions focusing on short video research have already been formed. Some popular topics of research on these videos include the main characteristics of short videos, phenomenon of media convergence based on short videos, and application scenarios of short videos. Over the years, research on the popular short video application Douyin has been increasing, as well. The research results indicate that issues such as the marketing of short knowledge videos, standardized management of short video platforms, and impact of these videos on the education of college students are expected to become popular subjects of scholarly research in the near future.

Affinity, value homophily, and opinion dynamics: The coevolution between affinity and opinion

We propose two analytical relationships between affinity and opinion change. The first one focuses on value homophily, while the second one incorporates affinity in opinion dynamics. Three analytical test models are derived based on these relationships: the value homophily model, the temporal evolution of opinion summation, and the evolution of opinion difference between two individuals. We test these models using data from a previous experiment, and the results demonstrate their validity.

Microblog User Emotion Analysis Method Based on Improved Hierarchical Attention Mechanism and BiLSTM

The goal of Chinese fine-grained emotion analysis is to identify the target words corresponding to fine-grained elements from sentences and determine the corresponding emotional polarity for the target words. Aiming at the problem that the current Sina Microblog user emotion analysis methods have low accuracy and are difficult to effectively predict and manage, a Sina Microblog user emotion analysis method based on the Bidirectional Long Short-Term Memory algorithm (BiLSTM) and improved hierarchical attention mechanism is proposed. Firstly, an emotion analysis model is constructed based on text-level analysis and subjective and objective analysis, and the dimensionality curse problem of one-hot representation is solved by integrating the weighted word vector of TF-IDF. Then, by constructing a bidirectional long short-term memory neural network, the full acquisition of context information is realized, which increases the fine-grained elements of emotion analysis. Finally, by introducing an improved hierarchical attention mechanism, the network model can focus on different parts to achieve text classification and emotion analysis. Through simulation experiments, the proposed emotion analysis method and the other two methods are compared and analyzed under the condition of using the same database. The results show that the precision, recall, and F1 value of the method proposed in this paper are the best under 7 different emotion classifications, with the highest reaching 95.8%, 95.9%, and 96.1%, respectively, and the algorithm performance is better than the other two comparisons algorithm. It is proved that the proposed model has excellent performance.