TikTok Comment Scraper: Deep User Engagement and Sentiment Intelligence

import requests
from bs4 import BeautifulSoup

# Headers to mimic a real browser
HEADERS = {
    "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64)",
    "Accept-Language": "en-US,en;q=0.9",
}

def scrape_tiktok_comments(video_url):
    response = requests.get(video_url, headers=HEADERS, timeout=15)

    if response.status_code != 200:
        print("Failed to fetch page:", response.status_code)
        return []

    soup = BeautifulSoup(response.text, "lxml")

    # Locate comment containers (structure may vary)
    comment_blocks = soup.find_all("div", class_="comment-item")

    comments_data = []

    for block in comment_blocks:
        username = block.find("span", class_="user-name")
        comment_text = block.find("p", class_="comment-text")
        likes = block.find("span", class_="like-count")
        timestamp = block.find("span", class_="comment-time")

        comments_data.append({
            "Username": username.text.strip() if username else "Unknown",
            "Comment": comment_text.text.strip() if comment_text else "N/A",
            "Likes": likes.text.strip() if likes else "0",
            "PostedAt": timestamp.text.strip() if timestamp else "N/A"
        })

    return comments_data

# Example TikTok video URL (Replace with a real video URL)
tiktok_video_url = "https://www.tiktok.com/@exampleuser/video/1234567890"

comments = scrape_tiktok_comments(tiktok_video_url)
for item in comments[:5]:
   print(item)