newms-data-analysis
Use when conducting and reporting the analysis of a New Media & Society (NM&S) manuscript across qualitative, content/discourse, computational, and mixed methods — making inference transparent and defensible on each tradition's own terms. Strengthens analysis and reporting; it does not collect data.
Profile →npx skills add brycewang-stanford/Awesome-Journal-Skills --skill newms-data-analysis --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Data & Analysis (newms-data-analysis) NM&S spans interpretive, content-analytic, and computational analysis under one interdisciplinary roof. The standard is the same across them: the analysis must be **transparent**, **credible to a reader from another tradition**, and matched to what the evidence can support. This skill is about *inference and reporting*, not study design (`newms-research-design`). ## When to trigger - Moving from collected data to claims, themes, measures, or results - A reviewer asked for reliability, robustness, validation, or a clearer analytic trail - You need to report uncertainty or limits honestly for a cross-method audience ## Qualitative inference (interviews / ethnography) - **Analytic transparency**: show the path from data to claim — coding/memoing process, how themes were built, and how many informants/instances support each theme (avoid "many participants felt…"). - **Negative cases and disconfirmation**: report instances that cut against the reading and how they were handled — the strongest signal of credible qualitative work. - **Quote-to-claim discipline**: each claim is anchored to specific evidence, not an isolated vivid quote. ## Content /
- When to trigger
- Qualitative inference (interviews / ethnography)
- Content / discourse analysis
- Computational analysis
- Inference honesty (all methods)
- Robustness & reliability checklist by method
- Worked micro-example (illustrative)
- Referee pushback → NM&S-specific fix
- Calibration anchors
- Anti-patterns
- Output format
- Supplementary resources
What does the newms-data-analysis skill do?
Use when conducting and reporting the analysis of a New Media & Society (NM&S) manuscript across qualitative, content/discourse, computational, and mixed methods — making inference transparent and defensible on each tradition's own terms. Strengthens analysis and reporting; it does not collect data.
How do I install it?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill newms-data-analysis --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From brycewang-stanford/Awesome-Journal-Skills, a repository with 909 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.