Notice: 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. Full accuracy metrics and methodology are described in Coakley et alK. L. Coakley, T. Snelleman, H. Hoos, and O. E. Gundersen, "The embrace of open science: An analysis of a decade of AI research and 56 800 conference papers," Under Review, 2026..
Unsupervised Sentiment Analysis for Social Media Images
Authors: Yilin Wang, Suhang Wang, Jiliang Tang, Huan Liu, Baoxin Li
IJCAI 2015 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | With experiments on two large-scale datasets, we show that the proposed method is effective in addressing the two challenges. |
| Researcher Affiliation | Academia | Yilin Wang, Suhang Wang, Jiliang Tang, Huan Liu, Baoxin Li Arizona State University Tempe, Arizona EMAIL |
| Pseudocode | No | The provided text does not contain any pseudocode or clearly labeled algorithm blocks. |
| Open Source Code | No | The paper does not provide any concrete access to source code or explicitly state that the code will be released. |
| Open Datasets | No | The paper mentions 'two large-scale datasets' and 'datasets from real-world social media image-sharing sites' but does not name them or provide concrete access information (e.g., specific links, DOIs, or formal citations) within the provided text. |
| Dataset Splits | No | The paper does not provide specific dataset split information (percentages, sample counts, or citations to predefined splits) needed to reproduce data partitioning. |
| Hardware Specification | No | The paper does not provide specific hardware details (like exact GPU/CPU models or processor types) used for running experiments. |
| Software Dependencies | No | The paper does not provide specific ancillary software details (e.g., library or solver names with version numbers). |
| Experiment Setup | No | The paper does not contain specific experimental setup details such as hyperparameter values or training configurations. |