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    <title>Cosima Meyer on Methods Bites</title>
    <link>https://socialsciencedatalab.mzes.uni-mannheim.de/author/cosima-meyer/</link>
    <description>Recent content in Cosima Meyer on Methods Bites</description>
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      <title>BERT and Explainable AI</title>
      <link>https://socialsciencedatalab.mzes.uni-mannheim.de/article/bert-explainable-ai/</link>
      <pubDate>Tue, 28 Mar 2023 01:00:00 +0100</pubDate>
      
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&lt;p&gt;Natural language processing (NLP) is a fascinating field. Popular NLP techniques for understanding (written) human language include next-sentence predictions, translations, text classifications, or sentiment analysis. Such techniques already permeate our everyday lives: What would the world be without services such as Google Translate, DeepL, or the recently released ChatGPT?
While common &lt;a href=&#34;https://socialsciencedatalab.mzes.uni-mannheim.de/article/advancing-text-mining/#usequanteda&#34;&gt;bag-of-words approaches&lt;/a&gt; can often be a valuable approach for NLP, Google’s release of &lt;a href=&#34;https://ai.googleblog.com/2018/11/open-sourcing-bert-state-of-art-pre.html&#34;&gt;BERT&lt;/a&gt; in 2018 revolutionized the possibilities in NLP.
This &lt;a href=&#34;https://socialsciencedatalab.mzes.uni-mannheim.de/categories/tutorials/&#34;&gt;Methods Bites Tutorial&lt;/a&gt; introduces the logic of large language models (LLM) with a special emphasis on BERT. It provides an applied use case from the social sciences, walks readers through explainable artificial intelligence (AI), and explains how we can leverage explainable AI to explain predictions of our models.
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      <title>How to write your own R package and publish it on CRAN</title>
      <link>https://socialsciencedatalab.mzes.uni-mannheim.de/article/r-package/</link>
      <pubDate>Thu, 16 Jul 2020 00:00:00 +0100</pubDate>
      
      <guid>https://socialsciencedatalab.mzes.uni-mannheim.de/article/r-package/</guid>
      <description>R is a great resource for data management, statistics, analysis, and visualization — and it becomes better every day. This is to a large part because of the active community that continuously creates and builds extensions for the R world. If you want to contribute to this community, writing a package can be one way. That is exactly what we intended with our package overviewR. While there exist many great resources for learning how to write a package in R, we found it difficult to find one all-encompassing guide that is also easily accessible for beginners.</description>
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    <item>
      <title>LaTeX and Overleaf</title>
      <link>https://socialsciencedatalab.mzes.uni-mannheim.de/article/latex-intro/</link>
      <pubDate>Thu, 05 Mar 2020 00:00:00 +0100</pubDate>
      
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      <description>LaTeX is a high quality typesetting system that that facilitates the production of well-formatted document. It has become highly popular in academic settings as an alternative to common typewriting systems (e.g., Word). This Methods Bites Tutorial by our team member Cosima Meyer and Dennis Hammerschmidt walks you through your first steps in LaTeX (using Overleaf) and provides you with a hands-on guide for writing scientific papers using an easily accessible template.</description>
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    <item>
      <title>Efficient Data Management in R</title>
      <link>https://socialsciencedatalab.mzes.uni-mannheim.de/article/efficient-data-r/</link>
      <pubDate>Tue, 18 Feb 2020 01:00:00 +0100</pubDate>
      
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&lt;p&gt;The software environment R is widely used for data analysis and data visualization in the social sciences and beyond. Additionally, it is becoming increasingly popular as a tool for data and file management. Focusing on these latter aspects, this &lt;a href=&#34;https://socialsciencedatalab.mzes.uni-mannheim.de/categories/tutorials/&#34;&gt;Methods Bites Tutorial&lt;/a&gt; by &lt;a href=&#34;https://twitter.com/mneunho&#34;&gt;Marcel Neunhoeffer&lt;/a&gt;, &lt;a href=&#34;https://gess.uni-mannheim.de/doctoral-programs/social-and-behavioral-sciences-cdss/students/people/show/oliver-rittmann.html&#34;&gt;Oliver Rittmann&lt;/a&gt; and our team members &lt;a href=&#34;https://twitter.com/denis_cohen&#34;&gt;Denis Cohen&lt;/a&gt; and &lt;a href=&#34;https://twitter.com/cosima_meyer&#34;&gt;Cosima Meyer&lt;/a&gt; illustrates the workflow and best practices for efficient data management in R. </description>
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    <item>
      <title>Advancing Text Mining with R and quanteda</title>
      <link>https://socialsciencedatalab.mzes.uni-mannheim.de/article/advancing-text-mining/</link>
      <pubDate>Thu, 17 Oct 2019 00:00:00 +0100</pubDate>
      
      <guid>https://socialsciencedatalab.mzes.uni-mannheim.de/article/advancing-text-mining/</guid>
      <description>Everyone is talking about text analysis. Is it puzzling that this data source is so popular right now? Actually no. Most of our datasets rely on (hand-coded) textual information. Extracting, processing, and analyzing this oasis of information becomes increasingly relevant for a large variety of research fields. This Methods Bites Tutorial by Cosima Meyer summarizes Cornelius Puschmann’s workshop in the MZES Social Science Data Lab in January 2019 on advancing text mining with R and the package quanteda.</description>
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    <item>
      <title>Visual Inference with R</title>
      <link>https://socialsciencedatalab.mzes.uni-mannheim.de/article/visinference/</link>
      <pubDate>Sun, 14 Jul 2019 03:03:03 +0100</pubDate>
      
      <guid>https://socialsciencedatalab.mzes.uni-mannheim.de/article/visinference/</guid>
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&lt;p&gt;How can we use data visualization for hypothesis testing? This question lies at the heart of this &lt;a href=&#34;https://socialsciencedatalab.mzes.uni-mannheim.de/categories/tutorials/&#34;&gt;Methods Bites Tutorial&lt;/a&gt; by &lt;a href=&#34;https://twitter.com/cosima_meyer&#34;&gt;Cosima Meyer&lt;/a&gt;, which is based on &lt;a href=&#34;https://www.richardtraunmueller.com&#34;&gt;Richard Traunmüller&lt;/a&gt;’s workshop in the &lt;a href=&#34;https://socialsciencedatalab.mzes.uni-mannheim.de/page/events/&#34;&gt;MZES Social Science Data Lab&lt;/a&gt; in Fall 2017. </description>
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    <item>
      <title>Data Visualization with R</title>
      <link>https://socialsciencedatalab.mzes.uni-mannheim.de/article/datavis/</link>
      <pubDate>Wed, 10 Jul 2019 02:02:02 +0100</pubDate>
      
      <guid>https://socialsciencedatalab.mzes.uni-mannheim.de/article/datavis/</guid>
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&lt;p&gt;How to make the invisible visible was the starting point of &lt;a href=&#34;https://www.richardtraunmueller.com&#34;&gt;Richard Traunmüller&lt;/a&gt;’s one-day workshop in the &lt;a href=&#34;https://socialsciencedatalab.mzes.uni-mannheim.de/page/events/&#34;&gt;MZES Social Science Data Lab&lt;/a&gt; in Fall 2016. This &lt;a href=&#34;https://socialsciencedatalab.mzes.uni-mannheim.de/categories/tutorials/&#34;&gt;Methods Bites Tutorial&lt;/a&gt; by &lt;a href=&#34;https://twitter.com/cosima_meyer&#34;&gt;Cosima Meyer&lt;/a&gt; provides you with some illustrative examples from Richard’s workshop. </description>
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