From bd6d1dbe6b5447d3b0f39d39a006b8a71d684287 Mon Sep 17 00:00:00 2001 From: wea_ondara Date: Mon, 6 Jan 2020 14:00:37 +0100 Subject: [PATCH] wip --- summary | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/summary b/summary index 92000f3..f42660f 100644 --- a/summary +++ b/summary @@ -6,10 +6,10 @@ new users: Users are considered new users if their first contribution (question Data: The data sets are aquired from archive.org [https://archive.org/download/stackexchange]. We analysed following data sets: - electronics.stackexchange.com -- math.stackexchange.com +- math.stackexchange.com (kaputt timeout) - mathoverflow.net - serverfault.com -- stats.stackexchange.com +- stats.stackexchange.com (kaputt analyse_batch letzter plot, 42, 37 datapoints) - stackoverflow.com (not yet) - superuser.com - tex.stackexchange.com @@ -20,7 +20,7 @@ question and answers may contain code sections. These sections should not contri Therefore, code sections are excluded in the analysis. -Familiarizing with the data sets: We created plots for: +Familiarizing with the data sets: We investigated following questions: - How many answers where given to questions in each time interval? (posthist.py) - How many users were active in each time interval? (posthist.py) - What is the distribution of users with exactly X answers in a given time interval? (posthist.py) @@ -30,5 +30,5 @@ Familiarizing with the data sets: We created plots for: - What are the reactions (answer sentiments) to questions of new users and users who post the most (95%tile)? Analysis: -ITS: We performed an ITS with 3 tensors (slope before, slope at change, slope after) on the sentiments of anwers to questions of new users (answers within 7 days of the first contribution). We choose to not aggregate the sentiments to an average per months but rather use every sentiment of an answer to a question individually (better results as number of observations in every time frame many vary greatly, thus skewing the results). +ITS: We performed an interrupted time series (ITS) with 3 tensors (slope before, slope at change, slope after) on the sentiments of anwers to questions of new users (answers within 7 days of the first contribution). We choose to not aggregate the sentiments to an average per months but rather use every sentiment of an answer to a question individually (better results as number of observations in every time frame many vary greatly, thus skewing the results).