Social media comp chapter

A book chapter that Jeremy, Mako, and Aaron are working on.

Current to-do list

Data collection and preparation

• Get Scopus articles about "online communities" as well

Introduction

• Revise once we have completed the sections and have a story to tell about our findings.
• Incorporate a bit more about how the chapter attempts to point people toward great resources and exemplary work applying computational techniques.

Data Collection and Descriptives (Jeremy)

• Write code to produce descriptive statistics
  • Citation Counts
  • Top Journals
  • Top Countries
  • Papers per year
• Finish writing up benefits/drawbacks section
• Incorporate mentions/citations of instructional texts/resources that interested readers can use.

Topic Models (Jeremy)

• Write code to produce:
  • Overall topic distribution
  • Topic distribution over time
  • Topic distribution in top journals?
• Write discussion of findings
• Write benefits/limitations of approach

Citation Prediction (Aaron)

• Incorporate links/citations to Statistical Learning book and related instructional resources.
• Prepare data for analysis
  • Abstract text
    • Lowercase
    • Remove stop-words
    • Create uni-, bi-, tri- grams.
    • Determine minimum threshhold of phrase occurrence for inclusion across categories/subjects (e.g., Mitra & Gilbert say 50 in their dataset).
  • Control measures
    • n.authors
    • publication year
    • publication type (conference? journal?)
    • agg prior citations for authors (sqrt? log?)
    • author affiliation (fixed effects? maybe just dummy for R1?)
    • venue (fixed effects)
    • subject area (fixed effects — various measures available)
    • affiliation countries
    • language

Citation Networks (Mako)

• Mako will complete detailed outline of his section in .tex file.

Conclusion

• Expand draft conclusion as we go. Revise upon completion.