wip

text/2_relwork.tex

@@ -71,7 +71,7 @@ In their book on ''Building successful online communities: Evidence-based social
 % - encouraging contribution: online communities need contributions by users (not lurking), content is foundation of community, contributions by users follows power law (usally, also confirmed in my results)
 % - regualting behavior: maintain a funtioning community, prevent troll, inappropiate behavior, limit damage if it occurs, ease of entry & exit -> high turnover
 
-All these criteria are heavily intertwined, so for the purposes of this thesis, these criteria can be grouped into two main categries: 1) onboaring of new users, 2) keeping users engaged, contributing, and well behaved. 
+All these criteria are heavily intertwined, kso for the purposes of this thesis, these criteria can be grouped into two main categries: 1) onboaring of new users, 2) keeping users engaged, contributing, and well behaved. 
 
 \subsection{Onboarding of new users}
 The onboarding process is a permanent challenge for online communities. The onboarding process differs from one platform to another. \citeauthor{slag2015one} investigated why many users on StackOverflow only post once after their registration \cite{slag2015one}. They found that 47\% of all users on StackOverflow  posted only once. They suggest that code example quatilty is lower than that of more involved users, which often leads to answers to first improve the question and code instead of answering the stated question. This likely discorages new users from using the site further. Negative feedback instead of constructive feedback is another cause for discontinuation of usage. The StackOverflow staff also conducted their own research on negative feedback of the community \cite{silge2019welcome}. They investigated the comment sections of questions by recruting their staff members to rate a set of comments and they found more than 7\% of the reviewed comments are unwelcoming.

text/3_method.tex

@@ -1,18 +1,18 @@
 \chapter{Methodology}
 
-% sentiment calculation via vaderlib, write whole paragraph
-% data sets as xml from archive.org
+% sentiment calculation via vaderlib, write whole paragraph and explain, also add ref to paper \cite{hutto2014vader}
+% data sets as xml files from archive.org \cite{archivestackexchange}
 
 %cleaning data
 % broken entries, missing user id
-% answers in html -> strip html and remove code sections, not contribution to sentiment
+% answers in html -> strip html and remove code sections, no contribution to sentiment
 
 
 % calc sentiment for answers
 
 % about the change 
-% https://meta.stackexchange.com/questions/314287/come-take-a-look-at-our-new-contributor-indicator?cb=1
-% https://meta.stackexchange.com/questions/314472/what-are-the-exact-criteria-for-the-new-contributor-indicator-to-be-shown  ; change date = 2018-08-21T21:04:49.177
+% https://meta.stackexchange.com/questions/314287/come-take-a-look-at-our-new-contributor-indicator \cite{post2018come}
+% https://meta.stackexchange.com/questions/314472/what-are-the-exact-criteria-for-the-new-contributor-indicator-to-be-shown \cite{sonic2018what} ; change date = 2018-08-21T21:04:49.177
 % new user indicator visible for 1 week ...
 
 
@@ -23,10 +23,10 @@
 
 
 %interrupted time series
-% ref tutorial paper
+% ref tutorial paper \cite{bernal2017interrupted}
 % often used in medical fields to see if changes have an effect
 % used same tensors as describe in paper, show formula and how it works, 3 tensors describe tensors and what they capture
-% explain why i cose this model, captures the change, more complex model would capture more but also get more complicated, these 3 tensors are enough to see the impact
+% explain why i chose this model, captures the change, more complex model would capture more but also get more complicated, these 3 tensors are enough to see the impact
 % fitting every value not aggregated values, aggregated values would have different weights, weights are too far spread, contrary to paper where person years are more or less constant
 % single value fitting is better, no weight issues, as weights are taken care of via more values
 % if one month has more values than another then that month affects its more as more values are present

text/4_datasets.tex

@@ -1,7 +1,7 @@
 \chapter{Datasets}
 
 %general
-% from archive.org
+% from archive.org \cite{archivestackexchange}
 % list of datasets
 % selected largest dataset, smaller datasets data to sparse to take concolusions, statistcal change of outliner to big, outlines would effect the outcome by too much
 % larger data sets yield in more consistent results
@@ -22,6 +22,7 @@
 
 
 % general information
+% dataset from to dates
 % #user, #questions, #answers, #votes, #avg answer/question
 
 %plots

text/bib.bib

@@ -245,6 +245,18 @@
   journal={\url{https://meta.stackexchange.com/questions/240839/the-new-new-be-nice-policy-code-of-conduct-updated-with-your-feedback}},
   year={2014}
 }
+@article{post2018come,
+  title={Come Take a Look at our New Contributor Indicator!},
+  author={Post, Tim},
+  journal={\url{https://meta.stackexchange.com/questions/314287/come-take-a-look-at-our-new-contributor-indicator}},
+  year={2018}
+}
+@article{sonic2018what,
+  title={What are the exact criteria for the “new contributor” indicator to be shown?},
+  author={Sonic the Anonymous Hedgehog and Nickel, Brian},
+  journal={\url{https://meta.stackexchange.com/questions/314472/what-are-the-exact-criteria-for-the-new-contributor-indicator-to-be-shown}},
+  year={2018}
+}
 @inproceedings{yanovsky2019one,
   title={One Size Does Not Fit All: Badge Behavior in Q\&A Sites},
   author={Yanovsky, Stav and Hoernle, Nicholas and Lev, Omer and Gal, Kobi},
@@ -365,3 +377,25 @@
   pages={143--154},
   year={2014}
 }
+@inproceedings{hutto2014vader,
+  title={Vader: A parsimonious rule-based model for sentiment analysis of social media text},
+  author={Hutto, Clayton J and Gilbert, Eric},
+  booktitle={Eighth international AAAI conference on weblogs and social media},
+  year={2014}
+}
+@article{archivestackexchange,
+  title={Files for stackexchange},
+  author={},
+  journal={\url{https://archive.org/download/stackexchange}},
+  year={}
+}
+@article{bernal2017interrupted,
+  title={Interrupted time series regression for the evaluation of public health interventions: a tutorial},
+  author={Bernal, James Lopez and Cummins, Steven and Gasparrini, Antonio},
+  journal={International journal of epidemiology},
+  volume={46},
+  number={1},
+  pages={348--355},
+  year={2017},
+  publisher={Oxford University Press}
+}

text/main.tex

@@ -196,7 +196,8 @@
     url=false, 
     doi=false,
     eprint=false,
-    hyperref=true
+    hyperref=true,
+    sorting=none
 ]{biblatex}
 \usepackage[T1]{fontenc}
 

text/template/pdf_settings.tex

@@ -57,6 +57,7 @@ anchorcolor=DispositionColor, %%
 colorlinks=\mycolorlinks, % turn on/off colored links (on: better for
                           % on-screen reading; off: better for printout versions)
 ]{hyperref}
+\urlstyle{same}
 
 %% all strings need to be loaded after hyperref was loaded with unicode support
 %% if not the field is garbled in the output for characters like ČŽĆŠĐ