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..
Learning and Forecasting Opinion Dynamics in Social Networks
Authors: Abir De, Isabel Valera, Niloy Ganguly, Sourangshu Bhattacharya, Manuel Gomez Rodriguez
NeurIPS 2016 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Experiments on data gathered from Twitter show that our model provides a good fit to the data and our formulas achieve more accurate forecasting than alternatives. |
| Researcher Affiliation | Academia | IIT Kharagpur MPI for Software Systems EMAIL EMAIL |
| Pseudocode | Yes | Appendix H summarizes the overall estimation algorithm. Appendix I summarizes the overall simulation algorithm. |
| Open Source Code | No | The paper does not provide explicit statements or links for open-source code for the described methodology. |
| Open Datasets | No | The paper mentions using 'five Twitter datasets about current real-world events (Politics, Movie, Fight, Bollywood and US)' which were gathered from Twitter, but does not provide specific access information (e.g., URL, DOI, specific citation to a publicly available dataset) for these collected datasets. |
| Dataset Splits | No | The paper mentions 'cross-validation' for setting decay parameters but does not provide specific percentages or sample counts for a distinct validation split. |
| Hardware Specification | Yes | The experiments are carried out in a single machine with 24 cores and 64 GB of main memory. |
| Software Dependencies | No | The paper mentions using 'a popular sentiment analysis toolbox, specially designed for Twitter [13]' but does not provide specific version numbers for this or any other software dependency. |
| Experiment Setup | Yes | Here, we set the decay parameters of the exponential triggering kernels Îș(t) and g(t) by cross-validation. |