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wea_ondara
2020-01-06 14:00:37 +01:00
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@@ -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: Data: The data sets are aquired from archive.org [https://archive.org/download/stackexchange]. We analysed following data sets:
- electronics.stackexchange.com - electronics.stackexchange.com
- math.stackexchange.com - math.stackexchange.com (kaputt timeout)
- mathoverflow.net - mathoverflow.net
- serverfault.com - serverfault.com
- stats.stackexchange.com - stats.stackexchange.com (kaputt analyse_batch letzter plot, 42, 37 datapoints)
- stackoverflow.com (not yet) - stackoverflow.com (not yet)
- superuser.com - superuser.com
- tex.stackexchange.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. 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 answers where given to questions in each time interval? (posthist.py)
- How many users were active 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) - 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)? - What are the reactions (answer sentiments) to questions of new users and users who post the most (95%tile)?
Analysis: 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).