Materials

Tutorials / Notebooks

• Regular expressions Tutorial in R and Tutorial in Python
• Split-Apply-Combine and Map Reduce in R (R Notebook)
• The Logic of MapReduce in Hadoop Streaming (Bash Notebook)
• Locality-sensitive hashing
• Text data: See Tutorials for Text as Data Course
• Geographic and space-time data
• Network data
  • Recommend for general overview of igraph in R, tutorials by Katya Ognyanova (Rutgers) here: https://kateto.net/tutorials/
  • Networks and Eigenvectors

Explainers

• Locality-sensitive hashing
• Time series primer
• Regularization primer

Figures

• The Social Data Stack

Slides

• Overview - What is Social Data Analytics
• Measurement Reliability and Validity
• Latent Measurement Modeling
• Sampling
• Experiments and Causal Inference
• Ethics and Scientific Responsibility
• Decomposition
• Measuring Distance & Similarity
• Convolution & Kernels
• Eigenstuff
• Split-Apply-Combine / Map-Reduce
• Linkage
• Social data structures: space, time, network, hierarchy
• Social data channels: text, image, audio, video
• Borrowed slides
  • Information retrieval: Manning, et al.: Chapters 1, 2, & 6
  • Embeddings: Jurafsky & Martin, Chapters 15 & 16
  • Hadoop, MapReduce: (some of) Leskovec, et al., Chapter 2
  • Locality-sensitive hashing: (some of) Leskovec, et al. Chapter 3
  • PageRank: (some of) Leskovec, et al. Chapter 5
  • Entity Resolution: (some of) Getoor & Machanavajjhala, “Entity Resolution: Tutorial”
  • Tidyverse: (some of) Wickham,
• Websites / videos / tools shown in class
  • Penn State Office of Research Protections, IRB & Common Rule Changes
  • Markov Chains Explained Visually
  • Trifacta Wrangler