Keyword frequencies in arXiv and SSRN working papers

<p>The dataset contains the raw results of the trend analysis performed on two working paper repositories: ArXiv and SSRN.</p> <p>ArXiv: the dataset consists of working papers acquired via ArXiv&rsquo;s API (<a href="https://arxiv.org/help/api/index">https://arxiv.org/help/api/index</a>). Working papers have been collected from the Computer Science discipline (all CS categories)</p> <p>SSRN (The Social Science Research Network): Working papers have been collected from two broad categories: 1. Information Systems &amp; eBusiness, 2. Innovation.&nbsp;</p> <p>For each repository, there are two separate analyses: for the period 2016.01-2019.12 and for 2020.01-2020.06 (COVID-19).</p> <p>Methodology:</p> <ul> <li>Frequency of appearances for all unigrams and bigrams in the texts</li> <li>Frequency: number of appearances of every term divided by the number of all terms&nbsp;(for every month and in case of COVID - every week due to the shorter time period)&nbsp;</li> <li>Average monthly / weekly&nbsp;change in the analised term&#39;s frequency is calculated by OLS regressions</li> <li>The dependent variable of the estimation is the frequency index, while the number of months&nbsp;since the beginning of the analysed period (January 2016) is the independent variable (in the case of COVID: weeks since January 2020)</li> <li>The regression coefficient (referred to as coef) shows by how much on average the analysed expression&rsquo;s frequency changed with every observed week&nbsp;(marginal change of the frequency), revealing which keywords had the biggest weekly&nbsp;growth</li> </ul> <p>&nbsp;</p> <p>&nbsp;</p>