
Text data used in an article Tatsuya Haga, Yohei Oseki, Tomoki Fukai, "A unified neural representation model for spatial and semantic computations" (preprint in biorxiv doi: https://doi.org/10.1101/2023.05.11.540307). Codes and usage of data are available at https://github.com/TatsuyaHaga/DSI_codes Main dataset (enwiki_processed_pickle): This file contains preprocessed text data of 100,000 articles randomly sampled from English Wikipedia dump taken on 22-May-2020 (https://dumps.wikimedia.org/enwiki/latest/). Additional dataset (wikitext103train_processed_pickle): This file contains preprocessed text data based on WikiText-103 dataset (Stephen Merity, Caiming Xiong, James Bradbury, and Richard Socher. 2016. Pointer Sentinel Mixture Models. http://arxiv.org/abs/1609.07843) Both text data have already been preprocessed: all characters were lowercased, punctuation characters were removed, and all words were tokenized. Data format is python pickle format. We publish data under CC-BY-SA following the license of original datasets.
| citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
