Methods Bites

Blog of the MZES Social Science Data Lab

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

2023-09-15 24 min read tutorials [Zaza Zindel Simon Lütkewitte]

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. Continue reading

Social media Survey data Data collection

A Hands-On Introduction to Artificial Neural Networks

2023-07-18 26 min read tutorials John 'Jack' Collins

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. Continue reading

Computational social science Machine learning Python

BERT and Explainable AI

2023-03-28 43 min read tutorials [Andreas Küpfer Cosima Meyer]

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. Continue reading

Python NLP BERT Deep Learning Explainable AI
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