How to Build a Brand Safety Monitor with Web Scraping

Brand safety is a $500M+ industry problem. When your ads appear next to harmful content or your brand gets mentioned in negative contexts, the damage can be immediate. Here's how to build your own monitoring system. What Brand Safety Monitoring Covers Ad placement verification -- are your ads showing on safe pages? Brand mention sentiment -- what context surrounds your brand name? Competitor defamation detection -- is someone attacking your brand? Domain spoofing alerts -- are fake sites using your brand? Core Monitor Implementation pip install requests beautifulsoup4 textblob pandas import requests from bs4 import BeautifulSoup from textblob import TextBlob from datetime import datetime class BrandSafetyMonitor : def __init__ ( self , brand_name , api_key ): self . brand = brand_name self . api_key = api_key self . unsafe_categories = [ " violence " , " hate speech " , " adult content " , " illegal " , " misinformation " , " extremism " ] def search_brand_mentions ( self , search_url