How to Build a Trend Forecasting Tool with Social Scraping

How to Build a Trend Forecasting Tool with Social Scraping Trends emerge on social media before hitting mainstream. By scraping platforms systematically, you can detect rising trends days before they become obvious. Data Collection import requests from bs4 import BeautifulSoup from datetime import datetime, timedelta import sqlite3, time class TrendCollector: def __init__(self, db_path='trends.db', api_key=None): self.db = sqlite3.connect(db_path) self.api_key = api_key self.session = requests.Session() self.session.headers.update({'User-Agent': 'TrendResearch/1.0'}) self._init_db() def _init_db(self): self.db.executescript(''' CREATE TABLE IF NOT EXISTS mentions ( id INTEGER PRIMARY KEY AUTOINCREMENT, platform TEXT, keyword TEXT, content TEXT, engagement INTEGER, timestamp DATETIME, url TEXT); CREATE INDEX IF NOT EXISTS idx_kw ON mentions(keyword, timestamp); ''') def _fetch(self, url): if self.api_key: return self.session.get( f"http://api.scraperapi.com?api_key={self.api_key}&ur