Notice: This website is continuously updated as new conference proceedings and journal volumes are published. Consequently, the figures presented here may differ from those reported in our publications.
A brief overview of our methodology is provided on the Methods page, along with references to publications documenting our approach and links to the code and data used in each study.
The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates.
What Does Social Media Say about Your Stress?
Authors: Huijie Lin, Jia Jia, Liqiang Nie, Guangyao Shen, Tat-Seng Chua
IJCAI 2016 | Venue PDF | LLM Run Details | Input Tokens: 14,770 Total number of tokens sent to the LLM as input for this paper's analysis. | Output Tokens: 5,373 Total number of tokens produced by the LLM (including reasoning/thinking tokens) for this paper's analysis.
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Extensive experiments on real-world datasets well verify the effectiveness of our scheme. |
| Researcher Affiliation | Academia | 1Department of Computer Science and Technology, Tsinghua University, Beijing, China Tsinghua National Laboratory for Information Science and Technology (TNList) Key Laboratory of Pervasive Computing, Ministry of Education 2School of Computer Science and Technology, Shandong University 3 School of Computing, National University of Singapore |
| Pseudocode | No | The paper describes the model and its solution steps mathematically and textually, but does not include any explicitly labeled pseudocode or algorithm blocks. |
| Open Source Code | Yes | Meanwhile, we have released the data to-gether with codes and parameters to facilitate the research community2 . http://stressmeasure.droppages.com/ |
| Open Datasets | Yes | To verify our scheme, we construct a representative dataset from Weibo by an extendable set of seed words, and invite 30 volunteers to manually build the ground truth. [...] Meanwhile, we have released the data to-gether with codes and parameters to facilitate the research community2 . http://stressmeasure.droppages.com/ |
| Dataset Splits | Yes | All the reported results in this paper were based on 10-fold cross validation |
| Hardware Specification | Yes | All experiments were performed on an x64 machine with two 2.6GHz intel E5-2650 CPUs and 128GB RAM. |
| Software Dependencies | No | The paper mentions using 'scikit-learn' and the 'MALSAR package' but does not specify their version numbers. |
| Experiment Setup | Yes | There are two key parameters in our model, which are λ and γ in Eqn.(1) that controls the impact of task relatedness and the generalization error, respectively. [...] the detection performance obtains the best scores when γ is around 10 20 for stressor event detection and 50 80 for stressor subject detection. [...] performance increases with the increase of λ, and tends to be stable when λ reaches 70 for stressor event and 100 for stressor subject detection. |