| |
| """Agreement between keyword coding and manual judgement. |
| Usage: python3 -I scripts/agreement.py coded_kw.jsonl manual/judgement.csv |
| judgement.csv: idx (row order in coded file) or url, relevant (yes/adjacent/no), then optional |
| manual codes; empty code = not coded by hand (relevance only).""" |
| import csv, json, sys, collections |
|
|
| coded = [json.loads(l) for l in open(sys.argv[1])] |
| by_url = {c["url"]: c for c in coded} |
| rows = list(csv.DictReader(open(sys.argv[2]))) |
| FIELDS = ["target_host", "app_type", "framework", "model_provider", "topic", |
| "error_type", "resolution_type", "ai_generated_app"] |
|
|
|
|
| def get(r): |
| if r.get("url"): |
| return by_url.get(r["url"]) |
| return coded[int(r["idx"])] |
|
|
|
|
| rel = collections.Counter() |
| for r in rows: |
| c = get(r) |
| if c is None: |
| continue |
| rel[(c["kw_relevant"], r["relevant"])] += 1 |
| n = sum(rel.values()) |
| print(f"relevance (kw, manual) on {n}: {dict(rel)}") |
| yes_kw = sum(v for (k, m), v in rel.items() if k == "yes") |
| print(f" precision of kw 'yes' vs manual yes: {sum(v for (k, m), v in rel.items() if k == 'yes' and m == 'yes')}/{yes_kw}") |
| man_yes = sum(v for (k, m), v in rel.items() if m == "yes") |
| print(f" recall of kw 'yes' over manual yes: {rel[('yes', 'yes')]}/{man_yes}") |
| print(f" manual precision of the collected set: {man_yes}/{n} = {man_yes / n:.2f}") |
|
|
| coded_rows = [r for r in rows if r["relevant"] == "yes" and r.get("app_type")] |
| print(f"\nfield agreement on {len(coded_rows)} hand-coded relevant threads:") |
| for f in FIELDS: |
| ok = tot = 0 |
| for r in coded_rows: |
| c = get(r) |
| kw = c["kw_" + f] if "kw_" + f in c else c.get(f) |
| if f == "topic" and kw is None: |
| kw = c.get("kw_problem_category") |
| man = r.get(f) if f in r else r.get("problem_category", "") |
| if f == "model_provider": |
| ok += set((kw or "").split(";")) == set(man.split(";")) |
| else: |
| ok += (kw or "") == man |
| tot += 1 |
| print(f" {f:18s} {ok}/{tot} = {ok / tot:.2f}") |
|
|
