Researchers studying YouTube content, media discourse, educational videos, or online communication need large datasets of video transcripts. Manually transcribing videos is impractical for large-scale studies, and existing tools are unreliable or require complex setup.
YouTubeTranscripts.co provides a reliable API for extracting transcripts at scale. Build research datasets from hundreds of videos using our batch API. Export transcripts in structured JSON format compatible with NLP tools, pandas, and statistical software. Our AI fallback ensures you can transcribe videos that lack captions.
import httpx
import pandas as pd
import json
API_KEY = "YOUR_API_KEY"
# Fetch transcripts for a research dataset
video_urls = [
"https://youtube.com/watch?v=VIDEO1",
"https://youtube.com/watch?v=VIDEO2",
# ... add your research corpus
]
dataset = []
for url in video_urls:
resp = httpx.get(
"https://api.youtubetranscripts.co/v1/transcript",
params={"url": url, "format": "text"},
headers={"x-api-key": API_KEY},
)
data = resp.json()
dataset.append({
"url": url,
"title": data["title"],
"channel": data["channel"],
"duration": data["duration"],
"text": data["text"],
"word_count": len(data["text"].split()),
})
# Export to DataFrame for analysis
df = pd.DataFrame(dataset)
df.to_csv("research_corpus.csv", index=False)
print(f"Collected {len(df)} transcripts, {df['word_count'].sum()} total words")Build large transcript datasets for research
Structured JSON output for NLP analysis
Export to CSV, JSON, or pandas DataFrames
AI fallback for videos without existing captions
Batch API for efficient large-scale collection
Timestamps enable temporal analysis of content
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