Search Results for author: Tingshao Zhu

Found 10 papers, 0 papers with code

Sensing Subjective Well-being from Social Media

no code implementations15 Mar 2014 Bibo Hao, Lin Li, Rui Gao, Ang Li, Tingshao Zhu

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.

Using Linguistic Features to Estimate Suicide Probability of Chinese Microblog Users

no code implementations4 Nov 2014 Lei Zhang, Xiaolei Huang, Tianli Liu, Zhenxiang Chen, Tingshao Zhu

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

no code implementations4 Nov 2014 Xiaolei Huang, Lei Zhang, Tianli Liu, David Chiu, Tingshao Zhu, Xin Li

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.

BIG-bench Machine Learning

Identifying Emotion from Natural Walking

no code implementations3 Aug 2015 Liqing Cui, Shun Li, Wan Zhang, Zhan Zhang, Tingshao Zhu

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.

Classification General Classification

Recognition of Emotions using Kinects

no code implementations4 Aug 2015 Shun Li, Changye Zhu, Liqing Cui, Nan Zhao, Baobin Li, Tingshao Zhu

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.

Emotion Recognition

Multivariate Regression with Grossly Corrupted Observations: A Robust Approach and its Applications

no code implementations11 Jan 2017 Xiaowei Zhang, Chi Xu, Yu Zhang, Tingshao Zhu, Li Cheng

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.

Hand Pose Estimation regression

Twitter discussions and emotions about COVID-19 pandemic: a machine learning approach

no code implementations26 May 2020 Jia Xue, Junxiang Chen, Ran Hu, Chen Chen, Chengda Zheng, Xiaoqian Liu, Tingshao Zhu

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.

BIG-bench Machine Learning

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