crawling tweets and proccess NLP

nlp-data-twitter.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "import tweepy\n",
    "from textblob import TextBlob"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# set requirement\n",
    "# get your own key from https://developer.twitter.com/en/apps\n",
    "consumer_key = \"< SECRET >\"\n",
    "consumer_secret = \"< SECRET >\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "# login to API twitter\n",
    "auth = tweepy.AppAuthHandler(consumer_key, consumer_secret)\n",
    "api = tweepy.API(auth)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# docs of query :  https://developer.twitter.com/en/docs/twitter-api/tweets/search/integrate/build-a-query\n",
    "tweets = api.search_tweets(q=\"< QUERY >\", count=100)\n",
    "for tweet in tweets:\n",
    "    analysis = TextBlob(tweet.text)\n",
    "    print(tweet.text+\" : \"+str(analysis.sentiment.polarity))"
   ]
  }
 ],
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