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SciRate quant-ph

SciRate quant-ph

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Earth and Nature,Education,Standardized Testing,Universities and Colleges,Linguistics,Physics,Research Classification

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    * 以上分析是由系统提取分析形成的结果,具体实际数据为准。

    README.md

    # Context I was curious about the hot topics in quantum physics as reflected by the [quant-ph](https://arxiv.org/archive/quant-ph) category on arXiv. Citation counts have a long lag, and so do journal publications, and I wanted a more immediate measure of interest. [SciRate](http://scirate.com/) is fairly well known in this community, and I noticed that after the initial two-three weeks, the number of Scites a paper gets hardly increases further. So the number of Scites is both immediate and near constant after a short while. # Content The main dataset (`scirate_quant-ph.csv`) is the metadata of all papers published in quant-ph between 2012-01-01 and 2016-12-31 that had at least ten Scites, as crawled on 2016-12-31. It has six columns: - The id column as exported by pandas. - The arXiv id. - The year of publication. - The month of publication. - The day of publication. - The number of Scites (this column defines the order). - The title. - All authors separates by a semicolon. - The abstract. The author names were subjected to normalization and the chances are high that the same author only appears with a unique name. The name normalization was the difficult part in compiling this collection, and this is why the number of Scites was lower bounded. A second file (`scirate_quant-ph_unnormalized.csv`) includes all papers that appeared between 2012-2016 irrespective of the number of Scites, but the author names are not normalized. The actual number of Scites for each paper may show a slight variation between the two datasets because the unnormalized version was compiled more than a month later. # Acknowledgements Many thanks to SciRate for tolerating my crawling trials and not blacklisting my IP address. # Inspiration Unleash topic models and author analysis to find out what or who is hot in quantum physics today. Build a generative model to write trendy fake titles like [SnarXiv](http://snarxiv.org/) does it for hep-th.
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