tutorials on Methods Bites

Survey Recruitment on LinkedIn: A Step-by-Step Guide to Targeted Outreach

Wed, 25 Mar 2026 00:00:00 +0000

LinkedIn’s professional user base and precise targeting capabilities present social science researchers with a valuable opportunity to recruit survey participants from highly specific populations, particularly those relevant to research on employment and industry dynamics. While platforms such as Facebook and Instagram are commonly used for recruitment of survey participants, LinkedIn’s potential in survey participant recruitment remains underutilized. Its professional focus, career-centric context, and only minimal off-topic content make it ideal for reaching the potential labor force population. This is particularly relevant for studies requiring insights from specific industries, occupations, or education levels. In this Methods Bites Tutorial Dr. Zaza Zindel (German Centre for Integration and Migration Research (DeZIM)) and Dr. Lisa de Vries (FernUniversität in Hagen) provide a step-by-step guide on how to use LinkedIn ads to recruit participants for survey research.

Computationally Analyzing Politicians’ Body Language Using Pose Estimation

Fri, 10 Jan 2025 02:00:00 +0100

Politicians can increase the appeal of their speeches through nonverbal cues such as gestures and vocal emphasis. Understanding the factors that make political speech appealing is central to political science research, yet studying nonverbal cues during political speech is difficult due to their audiovisual nature. Pose estimation models—a class of computer vision models that locate and trace human body key points, such as hands, ellbows, and shoulders throughout videos—offer a valuable opportunity to computationally assess politicians’ body language in video recordings.

Using TikTok ads for survey recruitment: a step-by-step approach

Fri, 15 Sep 2023 01:00:00 +0100

TikTok’s rapid growth and diverse user base present social science researchers with a unique opportunity to study a large and varied population, gaining valuable insights into their attitudes and behaviors. Unlike platforms such as Facebook and Instagram, TikTok’s potential in survey recruitment has been relatively underexplored. The platform’s cost-effective reach and detailed targeting parameters make it particularly appealing for reaching traditionally hard-to-reach or rare populations. Furthermore, with its video-centric format and predominantly young user base, TikTok provides a means to engage and attract respondents from younger generations to participate in online surveys. In this Methods Bites Tutorial, Zaza Zindel and Simon Lütkewitte (Bielefeld University) provide a step-by-step guide on how to use TikTok ads for survey recruitment.

A Hands-On Introduction to Artificial Neural Networks

Tue, 18 Jul 2023 01:00:00 +0100

Neural networks are powerful machine learning algorithms that form the basis of many important technologies, including generative AI and computer vision. However, they are not as straight-forward to implement as many other machine learning techniques, like random forest or logistic regression. If you are a researcher interested in applying neural networks, this Methods Bites Tutorial by John ‘Jack’ Collins demonstrates how to get started with Artificial Neural Networks (ANN) and helps you easily prototype a neural network for your own use-case.

BERT and Explainable AI

Tue, 28 Mar 2023 01:00:00 +0100

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 bag-of-words approaches can often be a valuable approach for NLP, Google’s release of BERT in 2018 revolutionized the possibilities in NLP. This Methods Bites Tutorial 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.

Collection, Management, and Analysis of Twitter Data

Thu, 02 Jun 2022 01:00:00 +0100

As a highly relevant platform for political and social online interactions, researchers increasingly analyze Twitter data. As of 01/2021, Twitter renewed its API, which now includes access to the full history of tweets for academic usage. In this Methods Bites Tutorial, Andreas Küpfer (Technical University of Darmstadt & MZES) presents a walkthrough of the collection, management, and analysis of Twitter data.

Using Geospatial Data in R

Fri, 11 Jun 2021 01:00:00 +0100

The use of geospatial data – data that can be mapped using geographic information systems (GIS) – has become increasingly widespread in the social sciences. Applications not only extend to the analysis of classical geographical entities (e.g., policy diffusion across spatially proximate countries) but increasingly also to analyses of micro-level data, including respondent information from georeferenced surveys or user trace data from Tweets. In this Methods Bites Tutorial, Stefan Jünger (GESIS) and Denis Cohen (MZES) show how to retrieve, manage, and visualize geospatial data in R.

Generalized Additive Models: Allowing for some wiggle room in your models

Mon, 10 May 2021 01:00:00 +0100

Generalized additive models (GAMs) have become an important tool for modeling data flexibly. These models are generalized linear models where the outcome variable depends on unknown smooth functions of some predictor variables, and where the interest focuses on inference about these smooth functions. In this Methods Bites Tutorial, Sara Stoudt (Smith College) offers a hands-on recap of her workshop “Generalized Additive Models: Allowing for some wiggle room in your models” in the MZES Social Science Data Lab in March 2021.

Extracting Emotions from Faces with Face++ (and Microsoft Azure)

Fri, 23 Apr 2021 01:00:00 +0100

Images are an increasingly used data source in the social sciences. One application is to extract features from human faces using machine learning algorithms. This blog post provides a guide on using APIs for this task, specifically how to access the services offered by Face++ and the Microsoft Face API. The post walks you through (1) how to gain API access credentials, (2) how to call the Face++ API from R, and (3) how to handle the output. It is based on the talk by Theresa Küntzler, who introduced the participants of the MZES Social Science Data Lab on May 12, 2020, to Extracting Emotions (and more) from Faces with Face++ and Microsoft Azure.

regplane3D: Plotting 3D regression predictions in R

Fri, 19 Mar 2021 01:00:00 +0100

The interpretation and presentation of empirical findings from (generalized) linear models has come a long way in the social sciences. Researchers increasingly visualize substantively meaningful quantities of interest such as expected values, first differences, and average marginal effects and consistently include uncertainty estimates in the form of analytical, simulation-based, or bootstrapped confidence intervals. However, existing interpretations and presentations are typically restricted to bivariate patterns which show (changes in) expected values as function of a single predictor, holding all else constant. This can be a significant limitation, especially when substantive inquiries focus on the interplay of two variables in predicting an outcome. To interpret and visualize such applications effectively, researchers must extend their presentations to include a third dimension. In this Methods Bites Tutorial, Denis Cohen and Nick Baumann introduce and showcase the regplane3D package, a tool for plotting 3D regression predictions in R.

Teaching Quantitative Social Science in Times of COVID-19: How to Generate and Distribute Individualized Exams with R and RMarkdown

Tue, 09 Feb 2021 01:00:00 +0100

The COVID-19 pandemic has forced universities around the globe to switch from on-site teaching to online teaching. As a consequence, quantitative social science classes that previously relied on closed-book in-class exams now have to administer open-book take-home exams. A downside of this switch is that it becomes impossible to monitor compliance with no-collaboration rules. Individualizing exam prompts can prevent students from sharing digital answers while taking the exam. Yet generating, distributing, and correcting individualized exams can be highly time consuming unless the procedure is automated. In this Methods Bites Tutorial, Denis Cohen, Marcel Neunhoeffer and Oliver Rittmann present an approach for the automated generation of individualized exam prompts and solution sheets, along with their automated distribution via email, using R and RMarkdown.

How to write your own R package and publish it on CRAN

Thu, 16 Jul 2020 00:00:00 +0100

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.

LaTeX and Overleaf

Thu, 05 Mar 2020 00:00:00 +0100

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.

Efficient Data Management in R

Tue, 18 Feb 2020 01:00:00 +0100

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 Methods Bites Tutorial by Marcel Neunhoeffer, Oliver Rittmann and our team members Denis Cohen and Cosima Meyer illustrates the workflow and best practices for efficient data management in R.

Applied Bayesian Statistics Using Stan and R

Thu, 30 Jan 2020 01:00:00 +0100

Whether researchers occasionally turn to Bayesian statistical methods out of convenience or whether they firmly subscribe to the Bayesian paradigm for philosophical reasons: The use of Bayesian statistics in the social sciences is becoming increasingly widespread. However, seemingly high entry costs still keep many applied researchers from embracing Bayesian methods. Next to a lack of familiarity with the underlying conceptual foundations, the need to implement statistical models using specific programming languages remains one of the biggest hurdles. In this Methods Bites Tutorial, Denis Cohen provides an applied introduction to Stan, a platform for statistical modeling and Bayesian statistical inference.

Shiny Apps: Development and Deployment

Tue, 17 Dec 2019 01:00:00 +0100

Shiny Apps allow developers and researchers to easily build interactive web applications within the environment of the statistical software R. Using these apps, R users can interactively communicate their work to a broader audience. In this Method Bites Tutorial, Konstantin Gavras and Nick Baumann present a comprehensive recap of Konstantin Gavras’ (University of Mannheim) workshop materials to illustrate how Shiny Apps enable vivid data presentation as well as its usefulness as an analytical tool.

Advancing Text Mining with R and quanteda

Thu, 17 Oct 2019 00:00:00 +0100

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.

Studying Politics on and with Wikipedia

Mon, 26 Aug 2019 01:00:00 +0100

The online encyclopedia Wikipedia, together with its sibling, the collaboratively edited knowledge base Wikidata, provides incredibly rich yet largely untapped sources for political research. In this Methods Bites Tutorial, Denis Cohen and Nick Baumann offer a hands-on recap of Simon Munzert’s (Hertie School of Governance) workshop materials to show how these platforms can inform research on public attention dynamics, policies, political and other events, political elites, and parties, among other things.

Quantitative Analysis of Political Text

Mon, 22 Jul 2019 00:00:00 +0100

How can we infer actors’ positions, substantive topics, or sentiments from (political) texts? This Methods Bites Tutorial by Julian Bernauer summarizes Denise Traber’s workshop in the MZES Social Science Data Lab in Spring 2018. Using exemplary sets of political documents (election manifestos and coalition agreements), it showcases tools of QTA for a variety of analytical objectives and demonstrates how to create, process, and analyse a text corpus through a series of hands-on applications.

Collecting and Analyzing Twitter Data Using R

Mon, 15 Jul 2019 01:01:01 +0100

How do you access Twitter’s API, collect a stream of tweets, and analyze the retrieved data? Which potentials, challenges, and limitations for social scientific research come along with using Twitter data? This Methods Bites Tutorial by Denis Cohen, based on a workshop by Simon Kühne (Bielefeld University) in the MZES Social Science Data Lab in Spring 2019, aims to tackle these questions.

Visual Inference with R

Sun, 14 Jul 2019 03:03:03 +0100

How can we use data visualization for hypothesis testing? This question lies at the heart of this Methods Bites Tutorial by Cosima Meyer, which is based on Richard Traunmüller’s workshop in the MZES Social Science Data Lab in Fall 2017.

Data Visualization with R

Wed, 10 Jul 2019 02:02:02 +0100

How to make the invisible visible was the starting point of Richard Traunmüller’s one-day workshop in the MZES Social Science Data Lab in Fall 2016. This Methods Bites Tutorial by Cosima Meyer provides you with some illustrative examples from Richard’s workshop.