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#CompSocSci

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Mario Angst<p>📜 We've got a new article out 📜</p><p>*Angst M, Müller NN, Walker V. Automated extraction of discourse networks from large volumes of media data* (open access)</p><p><a href="https://doi.org/10.1017/nws.2025.4" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="">doi.org/10.1017/nws.2025.4</span><span class="invisible"></span></a></p><p>As part of our sustainability.discourses project, we developed an automated method to gather and track discourse networks around urban sustainable mobility, based on media data.</p><p>The article describes the approach in detail and reports an evaluation of the internal validity (do we measure what we ourselves think we measure) of the pipeline. </p><p>tl;dnr: Automating discourse network data gathering can work well to capture broader tendencies. In many cases, it is likely not worth investing in automating data gathering to understand discourse however.</p><p>Want to see the daily updated pipeline in action? Check out the web apps and resources here: <a href="https://sustainability.discourses.ch/en/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">sustainability.discourses.ch/e</span><span class="invisible">n/</span></a></p><p><a href="https://fediscience.org/tags/CompSocSci" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>CompSocSci</span></a> <a href="https://fediscience.org/tags/policystudies" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>policystudies</span></a> <a href="https://fediscience.org/tags/networkscience" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>networkscience</span></a> <a href="https://fediscience.org/tags/nlp" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>nlp</span></a> <a href="https://fediscience.org/tags/nlproc" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>nlproc</span></a></p>
Mario Angst<p>🇪🇺 Want to analyze text from the EU public consultations? EU public consultations are a way in which the EU invites the broader public to publicly comment on upcoming legislation.</p><p>📦 :python: I just published a first version of a Python package {eu-consultations} to scrape and extract text from the EU website: <br><a href="https://github.com/marioangst/eu_consultations" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">github.com/marioangst/eu_consu</span><span class="invisible">ltations</span></a></p><p>- download consultation data as displayed on the EU's frontend into a validated form<br>- download associated files (this is the hard part about analysing this data - lots of feedback is in .docx and .pdf files)<br>- extract text from the files using docling and attach to feedback</p><p>You get all data in validated form and possibly stored in huge (sorry for that) JSON files ;).</p><p>This package is part of an analysis project on feedback the EU has received via the public consultation process on digital policy we plan to present later this year, but I thought let's make some of the tools we use open source way earlier already.</p><p><a href="https://fediscience.org/tags/python" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>python</span></a> <a href="https://fediscience.org/tags/textanalysis" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>textanalysis</span></a> <a href="https://fediscience.org/tags/policyanalysis" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>policyanalysis</span></a> <a href="https://fediscience.org/tags/CompSocSci" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>CompSocSci</span></a></p>
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