Dissertation Data Analysis & Theming
Budget: $250 – $750 USD
I’m preparing Chapter 4 of my dissertation and need an experienced researcher who can work with the raw material I’ve already collected—interview transcripts and supporting documents. The job is to dig into that dataset, extract the most frequently occurring words or phrases, turn those into clear, defensible themes, and present everything in a way that slots straight into the findings chapter.
Both qualitative and quantitative lenses are important here. I want solid word-frequency counts and descriptive statistics on one side, but also rigorous thematic coding and narrative synthesis on the other. If you normally run this kind of mixed-methods workflow in NVivo, ATLAS.ti, MAXQDA, or even R/Python text-mining libraries, let me know what you prefer; I’m open to recommendations as long as the final output is transparent and easy for my committee to verify.
Deliverables I need from you:
• Cleaned dataset ready for audit
• Word-frequency tables (top terms by count and percentage)
• A concise explanation of how cut-offs were chosen
• Thematic map with supporting excerpts or quotes
• Written summary tying those themes back to my research questions
I’ll provide all transcripts, document scans, and my current codebook draft once we start. Looking forward to working with someone who can move quickly yet rigorously so this chapter stands up to peer review.
Both qualitative and quantitative lenses are important here. I want solid word-frequency counts and descriptive statistics on one side, but also rigorous thematic coding and narrative synthesis on the other. If you normally run this kind of mixed-methods workflow in NVivo, ATLAS.ti, MAXQDA, or even R/Python text-mining libraries, let me know what you prefer; I’m open to recommendations as long as the final output is transparent and easy for my committee to verify.
Deliverables I need from you:
• Cleaned dataset ready for audit
• Word-frequency tables (top terms by count and percentage)
• A concise explanation of how cut-offs were chosen
• Thematic map with supporting excerpts or quotes
• Written summary tying those themes back to my research questions
I’ll provide all transcripts, document scans, and my current codebook draft once we start. Looking forward to working with someone who can move quickly yet rigorously so this chapter stands up to peer review.