H-Index Manipulation by Merging Articles: Models, Theory, and Experiments
Authors: René van Bevern, Christian Komusiewicz, Rolf Niedermeier, Manuel Sorge, Toby Walsh
IJCAI 2015 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Experiments on Google Scholar profiles of AI researchers show that the H-index can be manipulated substantially only by merging articles with highly dissimilar titles, which would be easy to discover. We implemented the manipulation algorithms exploiting small k and small c. Experimental results show that all of our sample AI authors can increase their H-index by only three merges but that usually merging articles with highly dissimilar titles is required to obtain any improvement. |
| Researcher Affiliation | Academia | Institut f ur Softwaretechnik und Theoretische Informatik, TU Berlin, Germany, {rene.vanbevern,christian.komusiewicz,rolf.niedermeier,manuel.sorge} @tu-berlin.de University of New South Wales and NICTA, Sydney, Australia, toby.walsh@nicta.com.au |
| Pseudocode | Yes | Algorithm 1: Greedy Merge |
| Open Source Code | No | The paper mentions implementing algorithms and running experiments but does not provide any link or explicit statement about the public availability of the source code for the methodology described. |
| Open Datasets | No | The paper states, 'We crawled Google Scholar data of 22 selected authors of IJCAI 13' and '14 authors of IEEE Computer Society’s AI’s 10 to Watch 2011 and 2013,' but it does not provide specific access information, links, or formal citations for these datasets. |
| Dataset Splits | No | The paper describes its data acquisition process but does not specify any training, validation, or test dataset splits. |
| Hardware Specification | Yes | With a time limit of one hour on a 3.6 GHz Intel Xeon E5-1620 processor and a memory limit of 64 GB |
| Software Dependencies | No | The paper mentions implementing algorithms but does not specify any software names with version numbers for dependencies such as programming languages, libraries, or frameworks. |
| Experiment Setup | Yes | With a time limit of one hour on a 3.6 GHz Intel Xeon E5-1620 processor and a memory limit of 64 GB, our algorithms failed to solve many instances with a compatibility threshold t 0.2 or allowing k 11 merges. Instances with k 10 and t 0.3 were usually solved within few seconds and using at most 100 MB of memory. |