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Twitter discussions and emotions about COVID-19 pandemic: a machine learning approach
Across all identified topics, the dominant sentiments for the spread of coronavirus are anticipation that measures that can be taken, followed by a mixed feeling of trust, anger, and fear for different topics.
Public discourse and sentiment during the COVID-19 pandemic: using Latent Dirichlet Allocation for topic modeling on Twitter
The study aims to understand Twitter users' discourse and psychological reactions to COVID-19.
Multivariate Regression with Grossly Corrupted Observations: A Robust Approach and its Applications
The implementation of our approach and comparison methods as well as the involved datasets are made publicly available in support of the open-source and reproducible research initiatives.
Recognizing Temporal Linguistic Expression Pattern of Individual with Suicide Risk on Social Media
We examined temporal patterns of the linguistic expression of individuals on Chinese social media (Weibo).
Recognition of Emotions using Kinects
By using the NaiveBayes, RandomForests, libSVM and SMO classification, the recognition rate of natural and unnatural emotions can reach above 70%. It is concluded that using the Kinect system can be a new method in recognition of emotions.
Identifying Emotion from Natural Walking
Emotion identification from gait aims to automatically determine persons affective state, it has attracted a great deal of interests and offered immense potential value in action tendency, health care, psychological detection and human-computer(robot) interaction. In this paper, we propose a new method of identifying emotion from natural walking, and analyze the relevance between the traits of walking and affective states.
Using Linguistic Features to Estimate Suicide Probability of Chinese Microblog Users
If people with high risk of suicide can be identified through social media like microblog, it is possible to implement an active intervention system to save their lives.
Detecting Suicidal Ideation in Chinese Microblogs with Psychological Lexicons
Currently, we have identified 53 known suicidal cases who posted suicide notes on Weibo prior to their deaths. We explore linguistic features of these known cases using a psychological lexicon dictionary, and train an effective suicidal Weibo post detection model.
Sensing Subjective Well-being from Social Media
Nowadays, people are motivated to share their experiences and feelings on social media, so we propose to sense SWB from the vast user generated data on social media.
